Download The Effect of Long-Term Drainage on Plant Community Composition

The Effect of Long-Term Drainage on Plant Community Composition,
Biomass, and Productivity in Boreal Continental Peatlands
by
Courtney A. Miller
A Thesis
presented to
The University of Guelph
In partial fulfilment of requirements
for the degree of
Master of Science
in
Integrative Biology
Guelph, Ontario, Canada
© Courtney A. Miller, September, 2011
ABSTRACT
THE EFFECT OF LONG-TERM DRAINAGE ON PLANT COMMUNITY
COMPOSITION, BIOMASS, AND PRODUCTIVITY IN BOREAL CONTINENTAL
PEATLANDS
Courtney A. Miller
University of Guelph, 2011
Advisor:
Dr. M.R. Turetsky
This thesis is an investigation of the effects of long-term drainage on plant
community composition, biomass and productivity in boreal continental peatlands. Because
bogs are ombrotrophic, I hypothesized that bog plant community composition, biomass and
productivity would be affected by drainage less than fens. I identified six Alberta peatlands
(2 bogs, 4 fens) that were affected by long-term drainage through road construction or
drainage ditches. I found that understory species composition in fens changed more in
response to drainage than in bogs, and was related to the degree of canopy closure. Woody
biomass increased in all poor fens sites with drainage, while understory biomass was not
affected. I investigated the influence of drainage on primary productivity in two sites, and
found that tree and moss productivity responded differently.
These results have
implications for peatland carbon cycling, as an increase in woody biomass will affect litter
quality and future fire risk.
iii
AKNOWLEDGEMENTS
It is my great honour to thank my advisor, Dr. Merritt Turetsky, as this thesis would
not have been possible without her support, guidance, and patience. I would also like to
thank my committee members, Drs. Shelley Hunt and Steven Newmaster for their
thoughtful comments and edits. I’d like to extend my gratitude to Dr. Brian Benscoter,
whose good humour made fieldwork and writing a pleasure.
I am indebted to my many colleagues at the University of Guelph, McMaster
University, and the Meanook Biological Research Station, who have provided help and
words of encouragement in the field, laboratory, and while writing this thesis. Thank you
to Andrew Baisley, Dan Greenacre, Abra Martin, Tom Schicks, Katie Neufield, Arielle
Garrett, Agnieszka Kotowska, Katie Shea, James Sherwood, Dan Thompson, Nick
Kettridge, Brandon Nichols, Sara Klapstein, and Paul Van Hooren.
Lastly, I owe my deepest appreciation to my parents, Tim and Heather Miller, for
their support and for instilling in me a sense of curiosity about the natural world. I hope I
have made you proud.
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Table Of Contents
Abstract ............................................................................................................................... ii
Aknowledgements.............................................................................................................. iii
Table Of Contents .............................................................................................................. iv
List of Tables ...................................................................................................................... v
List Of Figures ................................................................................................................... vi
Chapter 1 Introduction..................................................................................................... 1
1.1 Brief rationale ........................................................................................................... 1
1.2 Background information ........................................................................................... 2
1.3 Peatlands and the Global C Cycle ............................................................................. 4
1.4 Study Objectives and Hypotheses ........................................................................... 10
1.5 Introduction to study sites and site establishment................................................... 10
1.6 Literature Cited ....................................................................................................... 14
1.7 Tables ...................................................................................................................... 19
1.8 Figures..................................................................................................................... 20
Chapter 2 The Effect of Long-Term Drainage on Plant Community Composition in
Boreal Continental Peatlands ........................................................................................ 22
2.1 Introduction ............................................................................................................. 22
2.2 Methods................................................................................................................... 25
2.3 Results ..................................................................................................................... 29
2.4 Discussion ............................................................................................................... 33
2.6 Tables ...................................................................................................................... 41
2.7 Figures..................................................................................................................... 51
Chapter 3 The Effect of Long-Term Drianage on Plant Biomass and Productivity in
Boreal Continental Peatlands ........................................................................................ 59
3.1 Introduction ............................................................................................................. 59
3.2 Methods................................................................................................................... 61
3.3 Results ..................................................................................................................... 64
3.4 Discussion ............................................................................................................... 65
3.5 Literature Cited ....................................................................................................... 71
3.6 Tables ...................................................................................................................... 73
3.7 Figures..................................................................................................................... 76
Chapter 4 Conclusions.................................................................................................... 80
4.1 Effects of drainage on plant community composition, biomass, and productivity in
boreal continental bogs and fens ................................................................................... 80
4.2 Comparing peatland drainage in boreal regions: Canada vs. Finland ................... 82
4.3 Implications of peatland drainage for net ecosystem productivity ......................... 83
4.4 Study limitations and suggestions for future research ............................................ 85
4.5 Literature Cited ....................................................................................................... 89
v
List of Tables
Table 1.1 Site information including description, stand age, dominant species, location,
direction of water flow and road/ditch, and approximate date of disturbance. ........ 19
Table 2.1 Predicted shifts of A) vascular and B) non-vascular plant group abundance to
long-term water table draw down. ............................................................................ 41
Table 2.2 Study site design for road-impacted sites. ....................................................... 43
Table 2.3 Average depth to water table relative to the moss surface at the control and
treatment plots for each site. ..................................................................................... 44
Table 2.4 Canopy variables at the control and treatment plots at each site, including tree
density, basal diameter, total basal area and canopy openness. ............................... 45
Table 2.5 The Pearson’s correlation coefficients (r) for environmental and canopy
variables that occurred with drainage. ...................................................................... 46
Table 2.6 The Simpson’s Diversity Index, Sørensen quantitative dissimilarity index (SI),
and MRPP result for each fen and bog site. ............................................................. 47
Table 2.7 Results of the NMDS analysis of understory species composition at each site,
including the coefficients of determination (R2) for correlations between ordination
distances and distances in the original n-dimensional space. ................................... 48
Table 2.8 The Sørensen quantitative similarity index (SI) for each microform with
drainage at the RMF, RB1, and RB2 sites. ............................................................... 49
Table 2.9 The Pearson’s correlation coefficients (r) for the change in environmental and
canopy variables that occurred with drainage for the Sørensen quantitative similarity
index (SI) and the MRPP T statistic. ........................................................................ 50
Table 3.1 Mean plant group and total biomass for plot at each site. ............................... 73
Table 3.2 The Sørensen quantitative similarity index (SI) for biomass at each fen and bog
site. ............................................................................................................................ 74
Table 3.3 The productivity over two years at the McLennan ditched fen and the Roadimpacted Moderate Fen (RMF). ............................................................................... 75
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List Of Figures
Figure 1.1 Transect community composition based on crude vegetation surveys of moss
cover and tree cover classes. ..................................................................................... 21
Figure 2.1 Relationship between the SI and the MRPP statistic between control and
treatment plots within each site (r = 0.92010; p = 0.0083). ...................................... 51
Figure 2.2 The McLennan NMDS joint-plot depicting differences in understory species
composition between microforms in treatment and control plots. ........................... 52
Figure 2.3 The RMF NMDS joint-plot depicting differences in understory species
composition between microforms in treatment and control plots............................. 53
Figure 2.4 The RPF NMDS joint-plot depicting differences in understory species
composition between microforms in treatment and control plots. ........................... 54
Figure 2.5 The RB1 NMDS joint-plot depicting differences in understory species
composition between microforms in treatment and control plots. ........................... 55
Figure 2.6 The RB2 NMDS joint-plot depicting differences in understory species
composition between microforms in treatment and control plots. ........................... 56
Figure 2.7 Average percent cover of understory vascular plant groups within the control
and treatment plots in each site. ............................................................................... 57
Figure 2.8 Average percent cover of non-vascular plant groups for the control and
treatment plots at each site. ....................................................................................... 58
Figure 3.1 Average tree ANPP (g C/year) of P. mariana and L. laricina at the McLennan
site. ............................................................................................................................ 76
Figure 3.2 Average tree ANPP (g C/year) of L. laricina at the RMF site. ...................... 77
Figure 3.3 Average ANPP (g C/m2/year) for each plot of the McLennan site. ............... 78
Figure 3.4 Average ANPP (g C/m2/year) for each plot of the RMF site. ........................ 79
1
CHAPTER 1
INTRODUCTION
1.1 Brief rationale
Peatland plant community composition and carbon (C) cycling are closely
linked to site hydrology. Water inputs determine nutrient availability, which has
strong controls on floral community composition. Additionally, water table position
is an important regulator of peat accumulation, vegetation productivity, and
decomposition.
Warmer and drier climates are expected to lower water table
positions in the Canadian boreal continental ecosystem, and this may compromise the
ability for peatlands to serve as a long-term net C sink (Hogg, 1997; Tarnocai, et al.,
2006; Christensen, et al., 2007), both by potentially reducing plant productivity under
increased soil moisture deficits but also by increasing decomposition rates.
Depending on site and vegetation characteristics, water table drawdown in
peatlands can have either negative (i.e., net cooling; Minkkinen & Laine, 1998;
Weltzin, et al., 2000; Minkkinen, et al., 2002) or positive (i.e., net warming; Moore &
Dalva, 1997; Freeman, et al., 1997) effects on peatland radiative forcing. Over the
last decade, several water table manipulation experiments have been conducted in
European and North American peatlands to examine the effects of drought and
drainage on peatland C cycling. These studies have provided insight into the shortterm (i.e., seasonal to years) effects of climate change on peatlands (i.e., Weltzin, et
al., 2003; Strack, et al., 2004; Turetsky, et al., 2008a), but are unable to predict the
long-term response of peatland C cycling to water table drawdown. While lower
water tables generally are expected to increase decomposition rates in the short-term,
longer-term studies have shown that drainage of Finnish peatlands ultimately
increased carbon stocks in aboveground biomass and soils through increased woody
production and inputs to soils (c.f. Minkkinen, et al., 2002; Laiho, et al., 2003).
2
Understanding how peatland succession and C cycling responds to drainage
is fundamental to understanding the potential effects of climate change on peatlands
and the global C cycle. Although Finnish long-term experiments have provided
insight on the decadal impacts of drainage, boreal Fennoscandinavian peatlands differ
from boreal continental Canadian peatlands.
For example, peatlands in
Fennoscandinavia are often open or sporadically treed with Pinus sylvestrus and
Picea abies versus the Picea mariana and Larix laricina canopies found in North
American boreal continental peatlands (Vitt, 2006). Continental Canadian peatlands
also typically have lower water table position relative to the moss surface than
Fenoscandinavian peatlands (Vitt, 2006). Studies exploring the impact of drainage on
boreal continental peatlands tend to be focused on forestry (c.f. Lieffers, 1987;
Hillman, et al., 1990; Hillman & Roberts, 2006).
Consequently, the ecosystem
response to drainage in boreal continental peatlands remains unknown.
1.2 Background information
1.2.1 Peatlands in the boreal forest region
The circumboreal region covers approximately 1.5 x 107 km2 of land across
North America and Eurasia between 50°N and 60°N (Taggart & Cross, 2009). Boreal
regions tend to be characterized by short growing seasons (approximately three
months) and long, cold winters. In part, the tree community is adapted to these
conditions, with large extents of coniferous forests, with dominant species including
spruce (Picea), fir (Abies), and pine (Pinus). Though some deciduous broad leafs are
also present (i.e., poplar (Populus) and birch (Betula)).
Boreal and subarctic peatlands cover ~3.46 x 106 km2 of the global land mass
and represent ca. 87% of the world’s peatlands (Joosten & Clarke, 2002).
Approximately one quarter of the boreal biome is occupied by peatlands, covering
nearly 1.1 million km2 in Canada alone (Wieder, et al., 2009). In continental Western
3
Canada (i.e., Alberta, Saskatchewan, and Manitoba), peatlands cover 21% of the
land-base (~365,200 km2; Vitt, et al., 2000). Half of these peatlands occur in the high
Boreal region, where 63% of peatlands are fens, 9% are non-permafrost bogs, and
28% are permafrost-bogs (Vitt, et al., 2000).
Peatlands are defined as ecosystems that have accumulated more than 40 cm
of peat, which is partially decayed plant material. Peat accumulates when C fixation
through net primary production (NPP) at the surface exceeds losses from
decomposition, leaching, and disturbance throughout the entire peat profile.
Peatlands are classified either as bogs or fens using five primary factors: hydrology,
climate, substrate, chemistry, and vegetation (Vitt, 2006). Bogs are ombrotrophic and
receive nutrient and water inputs solely from precipitation, while fens are
minerotrophic and receive surface runoff and/or ground water recharge from
surrounding mineral-soil sources (Vitt, 2006). This difference in hydrology affects
nutrient availability and plant community composition.
Bogs are typically
characterized by low nutrient availability, acidic conditions, and low biodiversity
(Belland & Vitt, 1995). Bog plant communities are characterized by Sphagnum
mosses, lichens, feather mosses (i.e., Pleurozium schreberi), ericaceous shrubs such
as Ledum groenlandicum, Vaccinium vitis-ideae, and Oxycoccus microcarpus, as well
as P. mariana. Fens vary in their nutrient concentrations and acidity levels, and thus
can support a variety of vegetation types. Consequently, fens can be further classified
as either poor or rich. Poor fens are acidic, minerotrophic and Sphagnum moss
dominated, while rich fens can be alkaline, basic to neutral and typically are
dominated by true moss species (Vitt, 1994; Vitt, 2006). Boreal continental Canadian
fens often contain emergent vegetation such as Carex spp., while woody vegetation is
often L. laricina, Betula pumila, and Salix spp..
Peat formation occurs when dead vegetation is added to the peat surface at a
rate faster than the microbial community can break it down.
Thus peat can
accumulate as a result of fast vegetative inputs or slow decomposition rates. While
rates of plant productivity are comparable between upland forests and peatlands, rates
4
of soil C turnover in deep peat layers are much slower in peatlands than in uplands
(Trumbore & Harden, 1997; Turetsky, et al., 2005). However, among peatland types,
Vitt et al. (2009) concluded that peat accumulated faster in rich fens than in bogs
mostly because C inputs to soils were greater than in bogs as a result of high plant
productivity.
Decomposition can be slow in peatlands due to low temperatures, anaerobic
conditions, and/or poor substrate quality (see section 1.3 for more).
Most
decomposition of peat occurs in the acrotelm, the aerobic surface peat layer. Longterm peat accumulation depends on peat being transferred from the aerobic acrotelm
to the saturated catotelm, where peat is protected from rapid decomposition by cold
temperatures and a lack of oxygen (Clymo, 1984). The ‘enzyme latch’ hypothesis,
however, states that lower water table position as a result of drying could stimulate
decomposition by alleviating the constraints posed by anaerobic conditions on
microbial activity, thereby stimulating the breakdown of phenolic rich peat through
phenol oxidase activity (Freeman, et al., 1997).
While northern peatlands have
provided a net cooling effect on the Earth’s climate because of long-term peat
accumulation (Frolking, et al., 2006), changes in climate that disrupt either plant
productivity or decomposition could alter this function and potentially promote the
release of stored C back to the atmosphere.
1.3 Peatlands and the Global C Cycle
Due to historical peat accumulation, peatlands today represent a large
reservoir of soil C and are estimated to store approximately 320 ± 50 Pg C or 30% of
the world’s soil C pool, despite covering only 3-5% of the earth’s terrestrial surface
(Zoltai & Martikainen, 1996). About 85% of North America’s soil C is stored within
peatlands (Bridgeham, et al., 2006). This C stock exceeds the C stored in forest soils
as well as agricultural soils, and the annual global wetland C burial rate exceeds
oceanic sequestration (Dean & Gorham, 1998).
Western Canadian continental
peatlands comprise 0.25% of the earth’s land base and store 48.0 Pg C, equivalent to
5
approximately 2% of the world’s terrestrial carbon (Vitt, et al., 2000). Of this C pool,
about half is located in the boreal regions of Manitoba, Alberta, and Saskatchewan
(Vitt, et al., 2000).
In addition to the C storage capacity of peatlands, they can also act a source
for atmospheric greenhouse gases through the release C as methane (CH4) and carbon
dioxide (CO2). Methane has a stronger radiative forcing capacity than CO2, and is
produced in the anaerobic regions of the peat column through methanogenesis. Much
of the CH4 produced in deeper saturated peat is oxidized as it diffuses upwards
through the aerobic region of the peat column via methanotrophic bacteria. However,
even in peatlands with a thick aerobic surface peat layer, CH4 can bypass microbial
oxidation by plant mediated transport and ebullition (bubbling) events (Shea, et al., in
prep).
Peat accumulation and greenhouse gas emissions from peatlands also are
affected by a number of natural disturbances. The occurrence of natural wildfire in
boreal peatlands is the largest emitter of atmospheric C, releasing approximately 6 Tg
C year-1 from western Canadian peatlands (Turetsky, et al., 2002). Peat fires cause a
net warming effect on the Earth’s climate through 1) C losses to the atmosphere
during combustion, 2) decreases in surface albedo, and 3) reductions in plant
productivity and increases in decomposition due to warmer soil temperatures. Wieder
et al. (2009) found that bogs are a net C source for about 13 years post-fire, after
which Sphagnum moss recolonizes and can initiate peat accumulation (Wieder, et al.,
2009). A number of other disturbances also affect peatland vegetation and C cycling,
including permafrost thaw, peat harvesting, forestry, and agriculture.
In both pristine and disturbed peatlands, C cycling is primarily controlled by
temperature, water table position, and plant community composition (Whiting &
Chanton, 1993; Updegraff, et al., 1995; Hobbie, 1996; Moore & Dalva, 1997; Yavitt,
et al., 1997; Blodau, 2002; Wieder et al., 2009). Below I describe these controls in
more detail.
6
1.3.1 Edaphic controls on peatland C cycling
The position of the water table directly affects microbial respiration rates by
altering the availability of oxygen and other terminal electron acceptors in the peat
column. Microbes preferentially use oxygen (O2) as a terminal electron acceptor
(TEA), but under anaerobic conditions microbes also can utilize a variety of TEAs
such as nitrate and sulphate, though these reactions yield less energy (McLatchey &
Reddy, 1998). Moore and Dalva (1997) found that rates of CO2 production during
laboratory incubations of peat were almost 2.5 times higher under aerobic versus
anaerobic conditions. Additionally, they found that rates of C mineralization were
related to the depth of the peat column: the highest decomposition rates occurred in
surface peat and decreased with depth (Moore & Dalva 1997). In situ water table
drawdown experiments have increased soil CO2 production due to increased C
mineralization when the water table is lowered by as little as 1 cm (Silvola, et al.,
1996). In drier peatland sites, however, it is possible that C flux is more affected by
temperature than by water table (Lafleur, et al., 2005). Blodau et al. (2007) found
that soil CO2 fluxes were strongly dependent on temperature and not water table.
Generally, for every 10°C temperature increase in peat temperature, the rate of CO2
production in peat can increase 2-3 times (Blodau, 2002; McKenzie, et al., 1998).
1.3.2 Vegetative controls on peatland C cycling
In some peatlands, litter quality can be more important in controlling
decomposition rates than abiotic factors such as water table position and temperature
(Hobbie, 1996; Szumigalski & Bayley, 1996; Updegraff, et al., 1996; Moore & Dalva,
1997; Yavitt, et al., 1997). Peatland vegetation communities are often dominated by
ericoid shrubs, which tend to be tolerant of cold, waterlogged, and low-nutrient
environments.
Woody biomass is high in lignin and low in nitrogen (N)
concentrations, and thus tends to break down slowly in soils, particularly in anaerobic
conditions, as phenol oxidase requires oxygen (Freeman, et al., 1997). Mosses are
7
responsible for approximately half of the total peat in continental boreal Canada and
thus are important to long term peat accumulation (Turetsky, 2003). Mosses in
general have decomposition rates similar to coarse woody debris (Turetsky, et al.,
2010).
Sphagnum mosses in particular are N poor, due in part to high N use
efficiency, and they contain insoluble phenolic compounds like Sphagnic acid, which
make tissue resistant to decomposition (Aerts, et al., 1999). However, though there
are considerable differences in litter quality and decomposition rates among
Sphagnum species, with slower decomposition rates generally associated with species
that live in hummocks and faster decomposition rates in hollow species (Turetsky,
2003).
In western Canada, vegetation in peatlands is strongly influenced by
secondary succession, in particular succession post-fire. Benscoter and Vitt (2008)
identified three distinct moss communities that vary with time since fire 1) feather
moss dominant communities in mature bogs (greater than 80 years since fire), 2)
Sphagnum dominant communities in mid-successional bogs (20-80 years since fire),
and 3) true moss communities in recently burned stands (less than 20 years since fire).
P. schreberi is a photo-inhibited moss and tends to increase in abundance with stand
closure, while Sphagnum species prefer high light and thrive in open canopies
(Brisbee, et al., 2001), including recently burned sites with high tree mortality.
Feather moss dominated ground covers have slower soil inputs (Trumbore & Harden,
1997), and feather mosses do not have the lignin-like compounds found in Sphagnum.
Consequently, as the peatland stand ages and the bryophyte community shifts from
Sphagnum to feather moss, the potential for peat accumulation likely declines.
1.3.3 Interactions between biotic and abiotic controls on peatland C cycling
The relationship between biotic and abiotic controls on C and water cycling is
perhaps most apparent through examination of peatland microtopography.
Hummocks are mounds and hollows are depressions, while lawns are neither
mounded nor depressed in the peat surface. Water-transport and storage is different
8
among peatland microtopographical features due to Sphagnum species composition
(Kellner & Halldin, 2002). The presence of dead hyaline cells in Sphagnum mosses
allows them to store large amounts of water and enhance their ability to withstand
drought and alter soil moisture levels (Vitt, 2000). Although the acrotelm is thickest
within hummocks, hummock species in general have better capillary water transport
ability than hollow species, which prevents them from experiencing desiccation
(Rydin, 1993; Rydin, et al., 2006).
Sphagnum fuscum is found primarily on
hummocks due to competition and an intolerance to flooding, while Sphagnum
angustifolium, a common lawn or hollow species, performs best close to the water
table and is consequently excluded from hummocks (Hayward & Clymo, 1982; Titus,
et al., 1983; Vitt, et al., 1988). As mentioned above, hummock sphagna tend to
decompose slowly relative to hollow species. On the other hand, hollows tend to be
associated with higher biodiversity and higher vascular plant production than
hummocks (Rochefort, et al., 1990; Belyea, 1996; Malmar & Wallén, 1999). This
makes Sphagnum mosses integral in the formation and maintenance of
microtopography.
Additionally, because of high surface moisture in hummocks,
these microforms often escape severe combustion during wildfire, and unburned
Sphagnum hummocks often are the only fuel type to escape deep burning in peatlands.
Thus, vegetation controls on soil C losses (decomposition and combustion) help
sustain microtopography in peatlands.
1.3.4 Climate change and peatland C cycling
Changes in peatland CO2 and CH4 emissions due to water table drawdown
will likely have consequences for atmospheric C concentrations, and could initiate
either positive or negative feedbacks to future warming.
While peatlands have
historically served as a long-term sink for atmospheric CO2, warmer temperatures and
drier soil conditions associated with climate change may shift peatlands from a net C
sink to a net C source. On the other hand, drying of surface soils could increase C
uptake in woody biomass. Many global climate models (GCMs) project an increase
9
in mean temperature and precipitation in North America due to an increase in
atmospheric CO2 concentrations (Christensen, et al., 2007). Warmer conditions are
expected to increase evapotranspiration (ET) rates in boreal ecosystems, and at least
in western Canada this is expected to more than compensate for any increases in
precipitation.
In general, lower water table positions with climate change are expected to
increase decomposition rates by promoting aerobic microbial respiration (Freeman, et
al., 2004). Lower water table positions will cause increases in soil temperature as the
heat capacity of nearly saturated peat is approximately 4.02 x 106 Jm−3 K−1 versus that
of dry peat, which is approximately 0.58 x 106 Jm−3 K−1 (Oke, 1987). Therefore, drier
conditions could indirectly stimulate decomposition rates by affecting thermal
regimes (Lieffers, 1988; Laine, et al., 2006). Increased nutrient availability with
faster soil mineralization rates under warmer, drier soil conditions also could have
consequences for vegetation. Given that mosses are competitive under low nutrient
concentrations, increased N availability could favor vascular species.
Increased
shading from vascular plants could reduce total moss cover, and also cause changes in
the composition of the nonvascular community.
On the other hand peatland water tables may be unaffected by climate change
because of some of the unique properties of peat. Because peat is a non-rigid soil
surface, it tends to subside with lowered water table positions. Subsidence effectively
maintains high water table positions relative to the peat surface, which could limit
decomposition rates. Peat subsidence also increases peat bulk density, which affects
hydraulic conductivity and capillary fringe due to decreased pore size (Boelter, 1964;
Silins & Rothwell, 1998; Laine, et al., 2006). These changes would promote water
retention in surface peat layers, which effectively would maintain wet conditions
despite conditions that promote drying or drainage. Additionally, feedbacks between
vegetation and peat type may contribute to the C cycling response of peatlands
climate change. Some Sphagnum species, for example, can maintain high moisture
levels even during drought. Increases in tree cover with drainage leads to cooler
10
temperatures in deeper peat layers, which decreased decomposition rates and
promoted peat accumulation (Minkkinen, et al., 1999). Clearly, the interactions
between biotic and abiotic controls on peatland water table and other aspects of
peatland hydrology will in part determine the overall response of peatland C cycling
to climate change.
1.4 Study Objectives and Hypotheses
This thesis describes changes in community composition, biomass, and
productivity in boreal continental peatlands due to drainage. I identified sites in north
central Alberta, Canada that were drained as a result of road construction or
experimental ditching. While my results are directly applicable to understanding the
influence of land use and linear disturbance on peatlands, I was also interested in
using these results to explore the possible effects of long-term drying in peatlands
with climate change.
In Chapter 2 of this thesis, I examined the effect of drainage on tree cover and
understory plant composition (see section 2.1.2). In Chapter 3, I examined the effect
of drainage on tree and understory aboveground biomass and productivity (see
section 3.1.2).
1.5 Introduction to study sites and site establishment
In this thesis, I used two types of drainage to study the long-term
consequences of water table drawdown for boreal peatland plant community
composition, productivity, and biomass in Alberta, Canada. These two approaches
included i) the influence of roads, which alter peatland hydrology and ii) an
experimentally drained site implemented by the Canadian Forest Service (CFS) and
Alberta Land and Forest Service (ALFS) in the early 1980’s. More detail on these
two approaches is provided below.
11
1.5.1 Road-impacted sites
Roads transect many peatlands throughout the boreal region of Alberta.
Despite efforts to limit hydrological impacts on the peatland through the use of
culverts within the roadbed, roads often impound water on the upstream face resulting
in drying of the peatland downstream of the road. This may lead to a change in local
plant community composition. Water levels return to pre-construction conditions
usually within about 100 meters of the road, thereby creating a water table gradient
that could influence plant community assembly as well as peatland C and nutrient
cycling. Several studies have examined the impact of roads transecting peatland
complexes (Lieffers & Rothwell, 1987; Lieffers and MacDonald, 1990). However,
these studies focused on tree responses to altered water table depth, and did not make
comparisons with ‘control’ or pre-road construction conditions.
I selected five road-impacted sites in north-central Alberta through extensive
aerial photograph analysis and ground reconnaissance. The sites included two bogs
(Road Bog 1 and 2, hereafter referred to as RB1 and RB2, respectively), a poor treed
fen (Road Poor Fen or RPF), a poor open fen (Road Open Fen or ROF), and a
moderate treed fen (Road Treed Fen or RMF; Table 1.1).
Aerial photographs
(Government of Alberta Sustainable Resource Development’s Air Photo Library,
Edmonton, Alberta) were examined to determine the direction of water flow, the
shape of the peatland, and pre-road landscape homogeneity. Based on air photo
interpretation and ground truthing at each site, I established a drained plot (hereafter
referred to as the “treatment plot”) approximately 30 m perpendicular from the road.
I also established a control plot located further from the road where hydrology and
plant community composition was no longer impacted by road construction. Both
control and treatment plots were selected so as to avoid potential impacts of ditching
or mounding relics from road construction, as well as transmission poles.
At each site, I conducted botanical surveys along a transect perpendicular to
the road to help validate the location of each control plot. The length of each transect
12
depended on the site (Figure 1.1). Every 20 meters, I established a 10 m2 survey plot
and quantified moss and tree cover in the following classes: absent (0% cover), rare
(0-10% cover), patchy (10-40% cover), common (40-70% cover), and dominant
(>70% cover). Mosses were classified as true moss, Sphagnum moss, or feather moss.
True mosses were grouped into wet (i.e., Drepanocladus spp., Meesia triquetra, etc.)
or dry (i.e., Tomenthypnum nitens, Dicranum undulatum, etc.) categories. At each
site, I deemed the control plot as acceptable if community composition at the control
plot was similar to transect survey plots further away from the road (i.e., vegetation
composition did not continue to change further away from the control plot, indicating
that the control plot was representative of the larger undisturbed portion of the
peatland).
1.5.2 Experimental ditched site
In the mid 1980’s, the CFS and the ALFS established a network of drainage
ditches in several forested peatlands (including the Fort McMurray, Salteaux, Goose
River, McLennan, and Wolf Creek sites) as part of the Wetlands Drainage and
Improvement Program (Hillman, et al., 1990; Hillman, et al., 1997). Ditches were
0.9 m deep and approximately 1.4 m wide (Hillman, et al., 1990; Hillman, et al.,
1997). Immediately following ditching, a decrease in water table position of 20-50cm
occurred (Hillman, et al., 1990), as well as a reduction soil moisture (Rothwell &
Silins, 1990 in Macdonald & Yin, 1999), increased rates of decomposition (Lieffers,
1988), and elevated surface temperatures (Swanson & Rothwell 1989). Additional
studies examined differences in tree response to drainage (MacDonald and Yin 1999;
Hillman and Roberts 2006) and peat physical properties such as oxygen diffusion
rates and subsidence (Silins & Rothwell, 1998; Silins & Rothwell, 1999). Four of the
five sites are inappropriate for this study: two sites have experienced further
disturbance through fire or road construction (Salteaux and Fort McMurray,
respectively), the Goose river site contains less than 40 cm of peat, and the Wolf
13
creek site does not fall within the boreal biome. Consequently, I chose to focus on
the McLennan site in this study.
The McLennan site, ditched in 1986, is a treed poor fen located north of
McLennan, Alberta.
The treatment location is on the southwest portion of the
drainage network, while the control plot is located 40 m from the ditches on the south
side. The location of the control plot was determined through air photo interpretation:
considering direction of water flow and vegetation type prior to drainage (i.e. tree vs.
open and shade), as well as its proximity to the treatment plot for ease of access. Due
to the extreme nature of the disturbance vegetation community between the control
and treatment plots are visibly different from one another, although there is L.
laricina and P. mariana at both plots. The control plot is predominantly S. fuscum, T.
nitens, Salix spp., and L. groenlandicum, while the treatment plot is chiefly P.
schreberi with very little shrub cover, likely due to thick canopy cover (Table 1.1).
Using the five road-impacted sites as well as the experimental ditched site
described in this section, the goals of my thesis were to quantify the effects of
drainage (i.e. lowering of water table position and subsequent drying) on peatland
plant community composition (see Chapter 2) as well as biomass and productivity
(see Chapter 3). In Chapter 4, I synthesize these results and summarize a few main
conclusions.
14
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competition in a peatland stand of black spruce Picea mariana. Holarctic Ecology,
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areas of an Alberta peatland. Canadian Journal of Soil Science, 68, 755-761.
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tamarack in relation to depth of water table. Canadian Journal of Botany, 65, 817821.
16
Macdonald, S. E., & Yin, F. (1999). Factors influencing size inequality in peatland
black spruce and tamarack: evidence from post-drainage release growth. Journal of
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temperature on production of CH4 and CO2 from peat in a natural and flooded
boreal forest wetland. Climatic Change, 40, 247–266.
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decomposition and nutrient release in a wetland soil. Journal of Environmental
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17
Silins, U., & Rothwell, R. L. (1999). Spatial patterns of aerobic limit depth and
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19
1.7 Tables
Table 1.1 Site information including description, stand age, dominant species, location, direction of water flow and road/ditch, and
approximate date of disturbance determined by air photo interpretation. Stand age was determined by tree ring analysis using
WinDENDRO V 6.1 (Regent Instruments, Quèbec, Canada).
Location
(Latitude,
longitude)
Direction of
water flow
relative to
road
Direction of
road
Approximate
date of
disturbance
T. nitens, Drepanocladus spp., M.
triquetra, B. pumila , Andromeda
polifolia, L. laricsina
55°14’58.01”N,
111°19’21.45”W
SW
N-S
1990-1994
Road-impacted open
poor fen
S. angustifolium, Sphagnum
capillifolium, B. pumila, Carex spp.
55°48’54.72”N,
115°9’7.2”W
SW
E-W
1977-1983
RPF
Road-impacted treed
poor fen, 100 years
S. angustifolium, P. schreberi, Ledum
groenlandicum, P. mariana
55°45’20.52”N,
115°7’45.42”W
NW
SW-NE
1965-1971
RB1
Road-impacted bog,
130 years
S. fuscum, P. schreberi, L.
groenlandicum, V. vitis-ideae, P.
mariana
55°54'33.54"N,
115°4'56.70”W
W
N-S
1965-1971
RB2
Road-impacted bog, 70
years
S. fuscum, Cladina mitis, L.
groenlandicum, V. vitis-ideae, P.
mariana
55°52'36.42"N,
115°6'31.20"W
SE
N-S
1977-1983
McLennan
Drained poor fen, 90
years
S. fuscum, T. nitens, P. schreberi, Salix
spp., L. groenlandicum, L. laricina, P.
mariana
55°52'10.00"N,
116°54'53.57"W
NA
NA
1986
Description
(Minerotrophy and
stand age)
Dominant species present
RMF
Road-impacted treed
moderate fen, 90 years
ROF
Site Name
20
1.8 Figures
A) RMF
Wet true moss
Dry true moss
Sphagnum moss
Tree Cover
Cover Class
4
3
2
1
0
30-40m
70-80m
110-120m
170-180m
Distance from Road
210-220m
B) ROF
True moss
Feather Moss
Sphagnum moss
Tree cover
Cover Class
4
3
2
1
0
30-40m
50-60m
70-80m
Distance from Road
90-100m
C) RPF
Cover Class
4
3
2
1
0
30-40m
50-60m
Distance from Road
70-80m
21
D) RB1
Cover Class
4
3
2
1
0
30-40m
50-60m
70-80m
Distance from Road
90-100m
30-40m
50-60m
70-80m
Distance from Road
90-100m
E) RB2
Cover Class
4
3
2
1
0
Figure 1.1 Transect community composition based on crude vegetation surveys of moss
cover and tree cover classes where 4 is ‘dominant’ (>70% cover), 3 is ‘common’ (4070& cover), 2 is ‘patchy’ (10-40% cover), 1 is ‘rare’ (0-10% cover), and 0 is where
species are absent (0% cover). The control verification plot (plot farthest from the road)
was typically similar to the control plot (second farthest plot from the road) in all sites
(RMF (A), ROF (B), RPF (C), RB1 (D), RB2 (E)).
22
CHAPTER 2
THE EFFECT OF LONG-TERM DRAINAGE ON PLANT COMMUNITY
COMPSOITION IN BOREAL CONTINENTAL PEATLANDS
2.1 Introduction
2.1.1 Brief rationale
The manipulation of water table depth in peat mesocosms or in situ experiments
has provided insight on the effects of water table draw down on peatland vegetation
composition over time frames of seasons to years. These experiments suggest that drying
increases shrub as well as hummock moss productivity (Weltzin, et al., 2003; Strack &
Waddington, 2007; Breeuwer, et al., 2009). However, because of the short time frame of
these experiments, results are likely focused on the effects of changing hydrology on
plant physiology rather than exploring patterns of succession in response to changing
hydrology.
Relative to these short-term experiments, few studies have examined changes in
vegetation following long-term peatland drying or wetting. These studies have shown
that while drainage immediately increases shrub productivity, it takes several years
before tree productivity increases from drying (Minkkinen, et al., 1999; Laiho, et al.,
2003). Consequent canopy closure can initiate secondary succession in the understory
vascular and bryophyte communities (Laine, et al., 1995, Minkkinen, et al., 1999, Laiho,
et al., 2003). Reductions in light availability typically involve a decrease in shrub and
graminoid abundance accompanied by the replacement of Sphagnum by feather moss,
which tend to be light inhibited (Laine, et al., 1995; Minkkinen, et al., 1999, Laiho, et al.,
2003).
Changes in vegetation composition in response to drying or drainage can have
consequences for peatland water, nutrient, and C cycling. Increases in water loss through
23
evapotranspiration and interception likely will occur with increasing tree density (Seters,
1999 in Van Seters & Price 2001; Sarkkola, et al., 2010), which could facilitate further
drying.
Increased tree productivity also increases nutrient turnover-time through
increases in the standing biomass, which could reduce the quality of litter deposited to
soils and ultimately favour plant species that have high nutrient use efficiency.
Additionally, woody biomass is higher in lignin and low in N concentrations, and thus
decomposes slower than other litter types, which may result in peat accumulation
increases. Increases in tree density after drainage has decreased temperatures through
canopy shading and increased root inputs to soils (Minkkinen, et al., 1999; Murphy, et al.
2009), both of which have implications for rates of peat accumulation. In terms of
changing ground-layer composition, Sphagnum mosses usually have higher rates of
photosynthesis than feather moss (Williams & Flanagan, 1996), and have slower
decomposition rates because of poor substrate quality and high water retention (Hobbie,
et al., 2000; Turetsky, et al., 2010; see section 1.3 for a more thorough discussion of
controls of peatland C cycling). A significant reduction of Sphagnum cover in response
to drying or drainage is generally expected to reduce long-term peat accumulation both
by increasing decomposition rates and by affecting fire vulnerability, as Sphagnum
reduces combustion during burning (Johnstone, et al., 2010; Turetsky, et al., 2010).
In general, the expected response of peatland vegetation to drying would include
increased trees, shrubs, and mosses that prefer drier microhabitats such as hummock
Sphagnum and feather moss species. However, there are several reasons why this general
response may not be realized. First, bogs may be more impervious to drainage than fens
as bog has little to no lateral flow under pristine conditions. Furthermore, bog plant
species are adapted to low nutrient availability and are typically drier than fens. An
increase in nutrient turnover times has been observed with drainage due to increases in
tree biomass (Laiho, et al., 2003), which may not have an effect of bog plant species
composition. It is not surprising that 30 years following drainage, Minkkinen et al.
(1999) found that plant community composition had stayed relativity constant at bogs but
changed considerably in fens.
Second, subsidence of the peat surface can occur
24
following water removal, which increases bulk density, thereby increasing water
retention and decreasing hydraulic conductivity (Minkkinen & Laine, 1998; Silins &
Rothwell, 1998; Laine, et al., 2006).
Third, the presence of dead hyaline cells in
Sphagnum mosses allows them to maintain moist conditions even during soil moisture
deficits (Vitt, 2000). Hummock sphagna (i.e. Section Acutifolia, such as S. fuscum and S.
capillifolium) are more desiccation tolerant than hollow Sphagnum as they have better
capillary water transport (Rydin 1993, Rydin, et al., 1993). Because Sphagnum mosses
dominate bogs in continental Canada, this physiological control may also make bogs
more tolerant of to drying or drainage relative to fens.
The majority of research on the decadal response of peatlands to drainage has
been conducted in Finland, where draining peatlands for forestry was once a common
practice. Western Canadian peatlands typically are drier than Finnish peatlands, likely
due to differences in climate and tree cover. Peatlands in western Canada persist under
high rates of evapotranspiration due to dense canopies of P. mariana and L. laricina, tend
to have thick acrotelms, and experience a continental climate.
Conversely,
Fennoscandinavian peatlands experience a maritime climate and are often open or
sporadically treed with P. sylvestris or P. abies.
2.1.2 Objectives and Hypotheses
The objectives of this study were to quantify the effects of drainage on peatland
plant community composition. I tested the following hypotheses:
H2.1: Because of an increase in root zone depth, trees will increase in size and
density in forested bogs and fens.
H2.2: Increased canopy closure with drainage will reduce light in the understory
and will thus affect understory community composition.
H2.3: Because of differences in hydrology between bogs and fens, canopy closure
and understory plant species composition will change more in fens than in bogs.
25
In addition to these hypotheses made at the community level, I formulated hypotheses
specific to individual plant groups. These are provided in Table 2.1.
2.1.3 Study sites
In the mid-1980s the Canadian Forest Service and Alberta Environmental
Protection, Land and Forest Service (formerly Forestry Canada and the Alberta Forest
Service, respectively) drained a series of peatlands in Alberta for enhanced forestry yields.
Research to explore the effects of this project has focused primarily on tree responses to
drainage (i.e. Hillman, et al., 1997; Hillman & Roberts, 2006). I chose the McLennan
poor fen for this study. See Chapter 1 for a thorough description of the McLennan
drainage site.
This study also capitalized on linear features (roads) that commonly transect
peatlands in Alberta. Roads typically impound surface and ground water in peatlands
with wet conditions upslope and dry conditions down slope.
A few studies have
investigated the impact of roads on peatlands and in general have found P. mariana and L.
laricina growth rates are positively correlated with the decrease in water table on the dry
side of the road, and that growth was slowed on the wet side (Lieffers & Rothwell, 1987;
Lieffers & MacDonald, 1990). For this study, I used air photo analysis to select an open
poor fen (hereafter abbreviated as ROF), a treed moderate fen (RMF), a treed poor fen
(RPF), and two bogs (RB1 and RB2) in north-central Alberta. Each of these sites is
described in detail in Chapter 1.
2.2 Methods
2.2.1 Overall sampling design
Each site consisted of two plots (treatment vs. control). Within the treatment and
control plots at each site, I established a 10 x 10 m tree quadrat (Table 2.2). In each tree
26
quadrat, I sampled tree density and average basal diameter of every stem larger than 25
cm in height.
Because the tree sampling was destructive to the understory community and
surface soils, I established replicate 50 x 50 cm understory quadrats adjacent to the tree
quadrat for assessing understory species composition (moss, herbaceous, shrub; Table
2.2). These quadrats were located randomly. In most sites, I established six of these
species composition quadrats within the treatment and control plots, as species-area curve
analysis showed that this number was sufficient to characterize species composition at
each plot.
However, at the McLennan control plot, I established nine species
composition quadrats, which was sufficient as determined by a species-area curve
analysis.
Finally, in each plot, I established triplicate 0.25 m2 biomass quadrates (see
Chapter 3) for destructive sampling of understory biomass and productivity.
2.2.2 Environmental variables
Water table relative to the moss surface was measured in 3 cm diameter polyvinyl chloride wells established in each plot (3 per plot x 2 plots x 6 sites = 36). The
canopy cover at each understory species composition quadrat was obtained using a
camera with a fish-eye lens about 25 cm above the moss surface, and images were
analyzed using Gap Light Analyzer (GAP; Simon Fraser University & Institute of
Ecosystem Studies, 1999). Photographs were taken in July to quantify maximum canopy
cover. A temperature profile at depths of 10, 20, and 30 cm below the moss surface was
measured at each understory species composition quadrat. The microtopography in each
species composition quadrat also was noted (hummock, hollow, lawn).
27
2.2.3 Plant species composition and percent cover
Tree species identity, density, and basal diameter were surveyed in 100 m2 tree
quadrats at each the treatment and control plot of each site. The only exception was at
the McLennan treatment plot, where tree composition was surveyed in a 25 m2 tree
quadrat due high tree density (Table 2.2).
In each understory species composition quadrat, I visually estimated the percent
cover of all vascular and nonvascular plant species. Percent cover was noted separately
for two strata: 1) ground species including bryophytes and lichens, and 2) herbaceous and
shrub species. Species were identified using field guides (Vitt, et al., 1988; Johnson, et
al., 1999) and confirmed by Dr. Brian Benscoter or the Alberta Biodiversity Monitoring
Institute reference collection.
Some species were placed into broader groups: all
individuals from the genera Cladina or Cladonia were grouped into the Family
Cladoniaceae as they are from the same plant group (lichen). Individuals from the genera
Drepanocladus and Campylium were grouped into Drepanocladus spp. and Campylium
spp., respectively, as some samples were difficult to identify to species level due to
phenotypic plasticity. All individuals from the genera Carex, Poa, or Calamagrotis were
grouped together by genus as vegetation surveys occurred after flowering, making it
difficult to confirm species identities.
2.2.4 Statistical Analysis
To determine the effects of drainage on tree characteristics, I used a Student’s ttest to compare canopy openness and tree basal diameter between plots (treatment vs.
control plots) at each site. I also used Student’s t-tests to determine drainage effects on
Simpson’s diversity index values between the understory species composition quadrats at
each site. For sites with data that failed to meet normality using the Shapiro-Wilks
statistic, I transformed canopy openness or diversity index data prior to analysis, using a
natural log (ln) transformation. Data that could not be transformed to meet normality
assumptions were evaluated using Mann-Whitney non-parametric tests.
I used
28
correlation analyses to explore plot variable (i.e. total basal area, water table position,
canopy openness, diversity, average temperature at 10 cm, 20 cm and 30 cm)
relationships. In these correlations, I used the total basal area, which combines both
mean tree quadrat basal diameter and tree density. This was calculated as the sum of the
basal area of all trees in each tree quadrat based on the basal diameter measurements and
the assumption that each tree was roughly circular. All analyses were performed in SAS
version 9.2 (SAS Institute Inc., Cary, NC, USA) using an alpha value of 0.05 to
determine significance.
I calculated the Sørensen quantitative similarity index (SI) between plots
(treatment and control) as well as differences among microforms with drainage within
each site using EstimateS version 8.2.0 (Coldwell, 2006).
This index uses species
abundances to estimate similarity between two samples, where dissimilarity implies that
species composition in the treatment (drained) plots deviates from the control (pristine)
plots. Values close to 1 are considered most similar, while values close to 0 are most
dissimilar. I explored relationships between the SI and changes in environmental and tree
canopy variables using correlation analyses.
I used Nonmetric Multi-Dimensional Scaling (NMDS) as an ordination method
with the Bray-Curtis (Sørensen) distance measure in PC-ORD version 5.31 (Kruskal,
1964; Mather, 1976; McCune & Mefford, 2006) to detect patterns in species composition
and abundance between plots (control vs. treatment) within each site. This ordination
method avoids assumptions of linear relationships as it finds the arrangement of sample
units in ordination space where the ordination distance is in best rank agreement with the
dissimilarity between sample units (McCune & Grace, 2002). Ordination solutions were
obtained for each site to explore differences in species composition between the treatment
and control plots, as well as differences between hummocks and hollows (denoting the
spatial microforms present in some of my sites), within each site.
The starting
configuration for each analysis was random to obtain 250 runs of real data.
Dimensionality of a final ordination was determined using a scree plot (number of
dimensions vs. the minimum stress obtained) and a Monte Carlo test assessed the
29
probability that the final stress would have occurred by chance. The proportion of
variance represented by each axis was determined by the coefficient of determination (r2)
for the correlations between ordination distances and distances in the Sørensen distances
in space.
Joint-plots were constructed in PC-ORD to explore the relationships among
various environmental variables (i.e. canopy openness, tree density, median basal tree
diameter, water table, soil temperature throughout the peat profile) and species
composition. The degree of correlation of the vector to each axis in ordination spaces
was obtained from the Pearson’s correlation coefficient (r).
To determine statistical differences between a priori groups (treatment versus
control plots), I used a multi-response permutation procedure (MRPP). This approach
has no distributional assumptions about normality and homogeneity of variance, which
are rarely true in ecological data sets. A type one error rate of α = 0.05 was used. The
agreement statistic (A) in an MRPP is used to describe within group homogeneity: if
groups are homogenous (i.e. identical species composition quadrats within groups) then
A=1. McCune and Grace (2002) suggest an A> 0.3 is high in community ecology and
values are often <0.1. The test statistic (T) is a measure of distance between groups; a
strongly negative T value indicates a strong separation between groups.
I used
correlation analyses in SAS Version 9.2 to explore relationships between environmental
variables and the MRPP T statistic across plots at each site.
I also explored the
correlation between the MRPP T statistics and the SI of each plot across sites.
2.3 Results
2.3.1 Effects of drainage on environmental and canopy variables
Though my measurements of water table position were not frequent enough to
allow me to calculate a mean seasonal value, water table position during my site visits
were consistently lower in the treatment plot than in the control plot at most of the fen
30
sites (Table 2.3). At the RMF, water table position remained near the moss surface in
hollows in both the control and treatment plot. However, in hummocks, the water table
was deeper relative to the moss surface in the treatment plot than in the control plot. Data
on water table position at the RPF were collected only once, and were higher in the
control plot than in the treatment plot. However, this measurement occurred during a
heavy precipitation event and may not be representative of site conditions. At both roadimpacted bogs (RB1 and RB2), the water table position was similar between the control
and treatment plots (Table 2.3).
Canopy openness did not differ between plots at the RMF, ROF, and RB1 sites
(Table 2.4). However, it was lower (representing more canopy closure) in the treatment
plot than in the control plot at the treed poor fens (McLennan: t(13)=8.32, p<0.0001; RPF:
t(10)=4.44, p = 0.0012) and the RB2 site (t(10)=3.83, p=0.0033; Table 2.4).
In the treed fens, tree density and basal area were consistently greater in the
treatment plots than in control plots (Table 2.4). In both bog sites, tree density was
higher in the control than in the treatment plot (Table 2.4). However, while basal area
was greater in the treatment plot than in the control at the RB2 site (Table 2.4), it was
greater in the control plot at the RB1 site (z=-2.6396, p=0.0043; Table 2.4).
Across the control and treatment plots at each site, water table position was
positively correlated to basal area (Table 2.5), but not to canopy openness (Table 2.5).
Canopy openness was negatively correlated with basal area (Table 2.5).
Soil
temperatures at any depth below the moss surface were not correlated with other
environmental or canopy variables (Table 2.5).
2.3.2 Effects of drainage on plant community composition
At the RMF, ROF, RB1, and RB2 sites, there were no significant differences
between the control and treatment plots in the Simpson’s Index of Diversity (Table 2.6).
The McLennan treatment plot was less diverse than the control plot (t(5.8764)=2.85, p =
0.03), due primarily to fewer Sphagnum and deciduous shrub species in the treatment plot.
31
The RPF site was more diverse in the treatment plot than the control plot (t(10)=-2.18, p =
0.0539). At this site, although species richness was similar between plots (7.8 ± 0.41 and
7.3 ± 1.37, for the control and treatment plots, respectively), species evenness was higher
in the treatment plot (0.8 ± 0.04) than in the control plot (0.7 ± 0.08; t(10)=-3.19, p =
0.0097), generally due to increases in feather moss and ericaceous shrub abundance in the
treatment plot. According to the SI, species composition at the McLennan, RPF, RB1 and
RMF were most affected by drainage, while the ROF and the RB2 sites were the least
affected by drainage (Table 2.6). This is also true for the MRPP T statistic, which was
positively correlated with the SI (Figure 2.1).
Individual site ordinations produced solutions with low stress (i.e. < 8) and
usually accounted for a large portion of variation in understory species composition (i.e.
>80%; Table 2.7 and Figures 2.2-2.6). This excludes the ROF site, where final stress was
approximately 19.5 and accounted for 79% of the variation in species composition (Table
2.7). The MRPP results showed a significant plot (treatment vs. control) effect at the two
treed poor fens (McLennan and RPF sites) but showed no plot effect at the ROF or RB1
sites (Table 2.6).
However, the RB1 site ordination (Figure 2.5) showed a clear
distinction between treatment and control species composition quadrats across Axis 3.
According to the SI, there were differences between microforms with drainage at
the RB1, RB2 and RMF sites (Table 2.8). Hollow community composition changed
more than hummock community composition at all three sites with drainage. Vascular
plant cover increased only in hollows with drainage at the bog sites, while it increased
only at hummocks at the RMF site. The non-vascular community did not respond
similarly in hollows across sites with drainage. At the RB1 site, hollows experienced a
decrease in S. fuscum cover and an increase in lichen cover, while at the RB2 site P.
schreberi was replaced with S. fuscum in hollows. Hummocks at both the control and
treatment plots consisted entirely of T. nitens at the RMF site. However, hollows at the
control plot at this site consisted of Drepanocladus spp., M. triquetra, and Campylium
spp., while the treatment plot was dominated by Drepanocladus spp. only.
32
While the diversity index, SI and MRPP results provide assessments of whether
the overall plant community was affected by drainage at each site, I also investigated the
response of individual plant groups to drainage. Overall, these results agreed with the
multivariate analyses, and supported my hypothesis that bogs would experience an
increase in forb, shrub, and Sphagnum cover and a decrease in sedge cover with drainage,
while fens had increases in feather moss, and ericoid shrub cover accompanied by
decreases in deciduous shrub, sedge and Sphagnum hollow cover.
In the RMF and ROF sites, there was no overall change in total shrub abundance
with drainage. At the bogs and RPF sites, shrub cover was greater in the treatment plot
than the control plot (Figure 2.7), due to changes in L. groenlandicum at the RPF and
RB2 sites and V. vitis-ideae at the RB1 site. Shrub cover of both ericaceous (i.e. L.
groenlandicum) and deciduous (i.e. B. pumila) species was lower in the treatment than
the control plot at the McLennan poor fen.
Forb and sedges did not respond consistently to drainage across sites (Figure 2.7).
Forb cover was lower in the treatment plots than control plots at the treed poor fen sites
(McLennan and RPF) but was highest in the treatment plots of the RB1, RB2, and ROF
sites. At the RMF site, there was no difference in forb abundance between plots, though
the treatment plot had higher abundance of Menyanthese trifoliate, Caltha palustris, and
Potentilla palustris and lower abundance of Pedicularis parviflora than the control plot.
Sedge cover was lower in the treatment plot than the control plot at the McLennan, RPF
and RB2 site and did not differ between plots at the ROF and RMF sites (Figure 2.7).
In all sites, there was no overall change in total moss abundance with drainage. In
the two bog sites, feather moss cover was lowest while hummock Sphagnum (S. fuscum
and Sphagnum magellanicum) and lichen cover was highest in the treatment plot than the
control plot (Figure 2.8). At the McLennan and RPF sites, feather moss cover was higher
in the treatment plot than the control plot, while Sphagnum (hummock and hollow) cover
was lower in the treatment relative to the control plot. At the ROF site, Sphagnum cover
was similar between plots.
33
2.3.3 Environmental and canopy controls on understory species composition
The SI and the MRPP T statistic were both negatively correlated with the change
in tree basal area between plots at each site as well as the change in canopy openness
(Table 2.10). The SI, but not the MRPP T statistic, was negatively correlated to the
change in water table position I quantified across sites (Table 2.9).
In the individual site ordinations, tree basal area and water table position were
correlated with understory species composition at the McLennan, RPF, RMF, and RB1
sites (where the MRPP results showed significant plot (treatment vs. control) effects). At
the poor fen sites (McLennan and RPF), canopy closure increased significantly with
drainage, and was a strong predictor of understory species composition (Figures 2.2 and
2.4, respectively). At the RB1 site, canopy openness was also a strong predictor of
understory species composition, although the MRPP results showed no plot effect at this
site.
Temperature at 10 cm below the moss surface was correlated with species
composition at the RMF and RB1 sites. At the RMF site, this vector was associated with
a microtopography gradient and suggested that hummocks were typically warmer than
hollows. At the RB1 site, the temperature gradient indicates that hollows in the treatment
plot were typically warmer at 10 cm below the peat surface than hummocks in the
treatment plot or both hummocks and hollows in the control plot. Overall, there were no
strong environmental gradients associated with understory species composition at the
RB2 site.
2.4 Discussion
This study investigated the effects of several decades of drainage on peatland
plant community composition. I capitalized on two different types of drainage (drainage
occurring as a result of ditching versus drainage caused by road-impacts) on both bog and
fen plant species composition. While exploring the impact of anthropogenic disturbance
on peatland vegetation composition is interesting in of itself, I also was interested in
34
using these disturbances as a surrogate for the declines in water table position expected to
occur in boreal peatlands under future climate change scenarios (Hogg, 1997; Tarnocai,
et al., 2006). Modelling of water table position of a typical boreal bog under a range of
climate change scenarios shows that a reduction in water table position of up to one metre
is possible within a 100 year time frame (Waddington, pers. comm.).
Water table
position between treatment and control plots differed by less than 10 cm at the road
impacted sites and more than 2 m at the drainage site (Table 2.3). Also, the actual
response of water table position in peatlands to changing climate conditions also will
depend on vegetation. Increases in tree transpiration with increased tree productivity can
lead to even further drying.
Effects of drainage on trees
Peatland drainage has led to increases in tree biomass in Fennoscandinavia (Laine,
et al., 1995; Laiho & Laine, 1997; Minkkinen, et al., 1999; Laiho, et al., 2003). My
results show that the effect of drainage on tree cover and size is variable across sites. For
example, the two bogs diverged in their response to drainage. Canopy cover increased
with drainage at the RB2 site, but not at the RB1 site. This might be due to stand age, as
the RB2 site was 40 years at the time of drainage while the RB1 site was approximately
85 years old at the time of drainage. Biomass accumulation for P. mariana in Alberta
bogs peaks around 100 years post-fire (Wieder, et al., 2009). It is possible that younger
trees with more rapid primary production would respond more strongly to changes in
rooting zone with drainage compared to older trees.
Changes in canopy cover with drainage were variable at my fen sites.
For
example, tree basal area increased at two of the three treed fen sites, and did not change
with drainage at the RMF site. However, the tree community at the RMF site was likely
constrained by the water table position and likely did not experience significant increases
in soil aeration from drainage, as the water table position was at or above the peat surface
in hollows in the treatment (drained) plot.
35
Relationships between tree and understory responses following peatland drainage
My results in general support H2.2, which states that canopy closure as a result of
drainage would impact light availability and understory species composition. Both the T
statistic and the SI across sites were negatively correlated with the change in canopy
cover and total basal area with drainage (Table 2.9), meaning that the communities that
diverged the most between treatment and control plots were associated with the largest
increase in canopy closure. Interestingly, while the SI also was negatively correlated
with the change in water table, there was no relationship between the T statistic and
change in water table. While I was not able to test the influence of moisture versus light
as controls on understory species composition, these results clearly indicate that canopy
closure and its associated impacts on light availability is an important change with
peatland drainage.
Typically, feather moss cover increases at the expense of Sphagnum cover with
drainage (Minkkinen, et al., 1999). This is not consistent with my results in the bog sites.
Generally, S. fuscum and lichen cover replaced feather moss cover in the RB1 site with
drainage. Conversely, feather moss was replaced with S. fuscum cover in hollows but
lichen cover in hummocks with drainage at the RB2 site. An increase in Sphagnum is
consistent with my prediction, however the decrease in feather moss is not. Though
increases in hummock Sphagnum and lichen are consistent with lowered water table
positions, both tend to be found in areas with low canopy cover; while feather mosses (i.e.
P. schreberi) are often found under dense tree canopies. It is likely that canopy closure
was not sufficient at the RB1 and RB2 sites to increase the competitive advantage of the
photo-inhibited feather mosses (i.e. P. schreberi) as sites that experienced significant
increases in canopy closure (>70% closure in the treatment plot), experienced increases
in feather moss abundance.
In other studies, drainage has been shown to decrease understory species richness
due to canopy closure and declining light as well as changes in water table position (i.e.
Laine, et al., 1995; Grootjans, et al., 2005; Mälson, et al., 2008). I found this to be true
36
in the McLennan site as the treatment plot had a 30% lower diversity index than the
control plot. However, this did not occur in all the road-impacted fen sites. The RPF site
experienced a ~10% increase in canopy closure with drainage, and Simpson’s Diversity
was higher in the treatment plot than in the control plot. However, at the RMF site, the
treatment plot had similar canopy closure and similar diversity between plots.
Effects of drainage on bogs versus fens
Overall, the SI and T statistic values showed a stronger response to drainage at the
fen sites than at the two bogs. The multivariate statistics (SI and MRPP) show that the
RB2 site was not impacted by drainage (Table 2.6). The SI and MRPP results are
contradictory for the RB1 site, as the SI shows an effect of drainage on understory
species composition, whereas the MRPP results do not (Table 2.6). The SI and T statistic
resulted in similar trends at the fen sites, for example, the McLennan and RPF site were
the two most affected sites, while the ROF and RMF sites, were the least affected by
drainage. These results are consistent with my prediction that bog vegetation would be
impacted less by drainage than fens (H2.3).
However, my results suggest that community structure in hollows in general is
impacted by drainage more than in hummocks. The RB1 site ordination illustrates a clear
distinction in understory species composition quadrats between treatment and control
plots (Figure 2.5). While the MRPP showed no significant differences in bog vegetation
with drainage, interpretation of the site ordination and the SI indicate that hollows are
more dissimilar than hummocks between the control and treatment plots (Table 2.8). For
example, vascular cover increased in hollows with drainage (mostly due to increases in
shrub cover), but it was less affected by drainage in hummocks.
In fens, the MRPP and SI agreed that the understory species composition at the
McLennan, RMF and RPF site were affected by drainage, although differences in
understory species composition at the RMF site also varied by a microform x drainage
interaction. Hummocks at both plots of the RMF site consisted entirely of T. nitens moss,
37
while the hollow moss community was composed of Drepanocladus spp. in the treatment
plot but Drepanocladus spp., M. triquetra, and Campylium spp. at the control plot.
Additionally, vascular cover, particularly shrub cover, increased on hummocks with
drainage yet not hollows. It is likely that the change in water table position in hollows
was not sufficient to increase vascular root depth, thereby increasing cover. All sites
experienced a decrease in sedge cover, which appeared to be the most vulnerable
understory plant group to change post-drainage. It is likely that their well-developed
arenchymous tissue would become less advantageous with lower water table positions.
Other drainage experiments also have also found a decrease in sedge cover (Laine, et al.,
1995; Minkinnen, et al., 1999, Laiho, et al., 2003). In terms of moss cover, hollow
Sphagnum species declined in abundance and were replaced with feather mosses at the
treed poor fen sites (RPF and McLennan).
Conclusions
This study examined the response of community composition in two bogs and
four fens to long-term drainage. Results show that overall vegetation in fens responded
more strongly to drainage than in bogs. In the treed poor fens, canopy cover increased by
approximately 15% on average, which likely resulted in an increase in feather moss cover
and a concomitant reduction in Sphagnum moss cover. Vegetation in one bog site was
unaffected by drainage, while in the other bog vegetation changed more in hollows than
in hummocks. Overall, my results show that changes in canopy conditions with drainage
is important as an influence on boreal understory plant communities.
38
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Tarnocai, C. (2006). The effect of climate change on the carbon in Canadian peatlands.
Global and Planetary Change, 53: 222-232.
Turetsky, M. R., Mack, M. C., Hollingsworth, T. N., Harden J. W. (2010). The role of
mosses in ecosystem succesion and fucntion in Alaska’s boreal forest. Canadian
Journal of Forest Research, 40, 1237-1264.
Van Seters, T. E., & Price, J. S. (2001). The impact of peat harvesting and natural
regeneration on the water balanace of an abandoned cutover bog, Quèbec. Hydrological
processes, 15, 233-248.
Vitt, D. H. (2000). Peatlands: ecosystems dominated by bryophytes. In A. J. Shaw & B.
Goffinet (Eds.), Bryophyte Biology (pp. 312-343). United Kingdom: Cambridge
University Press.
Vitt, D. H., Marsh, J. E., & Bovey, R. B. (1988). Mosses, Lichens, and Ferns of
Northwest North America. Edmonton, Alberta, Canada: Lone Pine Publishing.
Weltzin, J. F., Bridgham, S. D., Pastor, J., Chen, J., & Harth, C. (2003). Potential effects
of warming and drying on peatland plant community composition. Global Change
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Wieder, R. K., Scott, K. D., Kamminga, K., Vile, M. A., Vitt, D. H., Bone, T., et al.,
(2009). Postfire carbon balance in Boreal bogs of Alberta, Canada. Global Change
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Pleurozium and Sphagnum. Oecologia 108, 38–46.
41
2.6 Tables
Table 2.1 Predicted shifts of A) vascular and B) non-vascular plant group abundance to long-term water table draw down. Arrow
direction indicates direction of plant group abundance changes.
A)
Overall prediction
of response
Plant group
Species examples
Trees
P. mariana,
L. laricina
Ericoid shrubs
L. groenlandicum,
A. polifolia,
V. vitis-ideae
Bogs and Fens
Deciduous shrubs
Fens only:
Salix spp,.
B. pumila
Fens
Bogs and Fens
Key Drivers
Sedges
Forbs
Carex spp.,
Eriophorum vaginatum
R. chamaemorus,
Smilacina trifolia,
Galium trifidum
Bogs and Fens
Bogs
no changeFens
increase in soil aeration
increase nutrient availability immediately following water
table draw down
outcompete deciduous as they dominate in dry, infertile
sites
increase in soil aeration
increase in tree canopy cover
competition with ericoid shrubs
soil aeration
increase in tree canopy cover
increase in nutrient turnover with increased tree
productivity
increase in soil aeration
competition with forbs because arenchymous tissue is no
longer advantageous
increase in tree canopy cover
increase in nutrient turnover with increased tree
productivity
competition with sedges
increase in soil aeration
typically higher biodiversity in fens than bogs
increase in tree canopy cover
increase in nutrient turnover with increased tree
productivity
42
B)
Plant group
Species examples
Overall prediction
of response
Feather Moss
P. schreberi,
Hylacomnium splendens,
Ptillium crista-castrensis
Bogs and Fens
Lichen
Cladina spp., Cladonia spp.
no change
Key Drivers
decrease in soil moisture
increase in tree canopy cover
decrease in soil moisture
increase in tree canopy cover
desiccation tolerance
increase in tree canopy cover
decrease in soil moisture
increase in tree canopy cover
decrease in soil moisture
less desiccation tolerance than hummock species
therefore increased competition from encroaching
hummocks, feather moss, and lichen
decrease in soil moisture
increase in tree canopy cover
increase competition from encroaching Sphagnum,
feather moss, and lichen if minerotrophy is appropriate
Bogs and Fens
no change
Hummock
Sphagnum
S. fuscum, S. capillifolium
Hollow Sphagnum
S. angustifolium
Bogs and Fens
Hummock True
Moss
T. nitens, Polytrichum
strictum, Aulicomnium
palustre
no change
Hollow True moss
Fens only: Drepanocladus
spp.
Campylium spp.
M. triquetra
Bogs and Fens
Bogs and Fens
Fens
soil moisture
canopy cover
competition from hummock species
43
Table 2.2 Study site design for the road-impacted sites. The McLennan ditched poor fen site contained a drained plot within the
southwest portion of the experimental drainage ditch network, while the control plot was located 40 m from the ditches on the south
side. For detailed site descriptions see section 1.5 and Table 1.1.
Site
Five road-impacted sites (2 bogs, 3 fens).
Drained
(Treatment) Plot
Located 30 m from road.
Understory species composition
quadrat
Tree quadrat
Understory biomass quadrat
Pristine
(Control) Plot
Understory species composition
quadrat
Tree quadrat
Understory biomass quadrat
50 x 50 cm quadrats for quantifying percent cover of understory plant
species composition. The number of these quadrats in each plot at each
site was determined by species-area curve analysis of sampling
effectiveness.
A 10 x10 m quadrat to estimate tree density, and each individual’s
basal diameter.
Triplicate 50 x 50 cm destructive understory quadrats to determine
biomass and productivity estimates of vascular vegetation.
Location varied between sites and was determined by the transect data
described in section 1.5.1 and Figure 1.1
50 x 50 cm quadrats for quantifying percent cover of understory plant
species composition. The number of quadrats was determined by
species-area curve analysis of sampling effectiveness.
A 10 x10 m quadrat to estimate tree density, and each individual’s
basal diameter.
Triplicate 50 x 50 cm destructive understory quadrats for determining
biomass and productivity estimates of vascular vegetation.
44
Table 2.3 Average depth to water table relative to the moss surface at the control and
treatment plots for each site. Positive values are below the moss surface, while negative
values represent a water table positive above the moss surface. * The McLennan
treatment plot water table was below the mineral soil, which was 3 m below the moss
t
surface. Depth to ice.
Site
McLennan Ditched Fen
Road-impacted Moderate Fen (RMF)
Road-impacted Open Fen (ROF)
Road-impacted Poor Fen (RPF)
Road-impacted Bog 1 (RB1)
Road-impacted Bog 2 (RB2)
Date of
sample
(d/m/y)
11-Jul-09
04-Sep-09
29-May-10
25-Jul-10
07-Aug-10
01-Sep-10
23-Jun-09
12-Jul-09
12-Sep-09
27-May-10
17-Jun-10
30-Aug-10
02-Jul-10
03-Aug-10
28-Aug-10
28-Aug-10
09-Jun-10
02-Jul-10
11-Aug-10
29-Aug-10
09-Jun-10
07-Aug-10
29-Aug-10
Water table position relative
to the moss surface (cm)*
Control
Treatment
3.5 ± 3.5
39.5 ± 4.5
9.0 ± 2.0
300*
20.5 ± 3.5
48.5 ± 6.5
24.0 ± 4.0
-5.9 ± 1.4
1.6 ± 3.9
-5.7 ± 3.7
0.7 ± 0.7
5.3 ± 1.8
14.7 ± 3.1
1 ± 0.6
6.0 ± 5.5
-4 ± 1.2
5.3 ± 4.8
0.0 ± 0.0
3.2 ± 3.2
t
t
42.0 ± 4.0
36.0 ± 0.0
0.3 ± 0.3
1.8 ± 0.8
1.3 ±1.3
6.5 ± 3.5
16.3
23.0
13.5 ± 0.5
14.0 ± 4.0
12.5 ± 0.5
20.0 ± 7.0
14.8 ± 1.3
13.8 ± 0.3
16.0 ± 5.0
10.3 ± 2.8
7.5 ± 0.5
11.0 ± 1.0
12.0 ± 4.0
12.5 ± 1.5
13.3 ± 1.8
18.8 ± 0.3
45
Table 2.4 Canopy variables at the control and treatment plots at each site, including tree density, basal diameter, total basal area and
canopy openness. Data are means ± 1 SE. Data marked with a * indicate plots that differed significantly according to Student’s t-tests
or Mann-Whitney tests (p<0.05). Tree density includes measurement of all trees greater than 25 cm in height.
Site
Plot
Control
Treatment
Road-impacted Moderate
Control
Fen (RMF)
Treatment
Road-impacted Open Fen
Control
(ROF)
Treatment
Road-impacted Poor Fen
Control
(RPF)
Treatment
Control
Road-impacted Bog 1 (RB1)
Treatment
Control
Road-impacted Bog 2 (RB2)
Treatment
McLennan Ditched Fen
Tree density
(stems/m2)
1.3
8.0
0.5
0.7
0
0
1.2
1.6
2.0
1.6
1.4
1.0
Basal diameter
(cm)
4.0 ± 0.1
*
11.5 ± 1.5
4.0 ± 0.3
3.77 ± 0.2
0
0
4.2 ± 0.3
4.7 ± 0.2
3.5 ± 0.1
*
3.0 ± 0.2
3.0 ± 0.1
*
4.2 ± 0.2
Total tree quadrat
basal area (m2)
0.4097
0.9179
0.2041
0.2207
0
0
0.2355
0.3787
0.2541
0.1635
0.1263
0.1762
Mean canopy
openness (%)
45.9 ± 1.5
*
25.1 ± 2.2
42.8 ± 2.6
37.3 ± 1.7
69.1 ± 3.4
70.3 ± 3.0
30.3 ± 2.3
*
19.0 ± 1.1
43.2 ± 1.1
39.7 ± 3.2
49.5 ± 1.9
*
38.1 ± 2.3
46
Table 2.5 The Pearson’s correlation coefficients (r) for environmental and canopy variables that occurred with drainage. Italicized
values are the respective p values.
Total tree
quadrat basal
area
2010 Water table
position
Total tree quadrat
basal area
Average plot
canopy openness
Mean plot soil
temperature 10 at
cm below moss
the surface
Mean plot soil
temperature 20 at
cm below moss
the surface
0.8943
<0.0001
1
Average plot
canopy openness
-0.4029
0.1940
-0.6767
0.0157
1
Mean plot soil
Mean plot soil
Mean plot soil
temperature at 10 temperature 20 at temperature at 30
cm below moss
cm below moss
cm below moss
the surface
the surface
the surface
0.3354
0.2798
0.2177
0.2865
0.3785
0.4966
0.5206
0.4571
0.3281
0.0827
0.1352
0.2977
-0.2458
-0.3319
-0.3552
0.4412
0.2920
0.2573
0.9351
0.7698
1
<0.0001
0.0034
0.9289
1
<0.0001
47
Table 2.6 The Simpson’s Diversity Index, Sørensen quantitative dissimilarity index (SI), and MRPP result for each fen and bog site (n
= 6 species composition quadrats for each plot except the McLennan control plot where n = 9). Data are means ± 1 SE. Data marked
with a * indicate plots that differed significantly according to Student’s t-tests (p<0.05).
Site
McLennan Ditched Fen
Road-impacted Moderate Fen (RMF)
Road-impacted Open Fen (ROF)
Road-impacted Poor Fen (RPF)
Road-impacted Bog 1 (RB1)
Road-impacted Bog 2 (RB2)
Plot
Species
Richness
Average Simpson’s
Diversity Index
Control
23
Treatment
11
Control
19
0.78 ± 0.05
Treatment
17
0.7 ± 0.03
Control
16
0.69 ± 0.05
Treatment
15
0.73 ± 0.03
Control
16
Treatment
15
Control
9
0.65 ± 0.08
Treatment
12
0.71 ± 0.03
Control
10
0.68 ± 0.04
Treatment
9
0.68 ± 0.02
*
*
0.77 ± 0.03
0.55 ± 0.08
0.61 ± 0.03
0.69 ± 0.
SI
MRPP
T
A
P
0.326
-3.1066
0.0913
0.0131
0.686
-0.4220
0.0235
0.2510
0.813
0.8829
-0.0298
0.8435
0.552
-2.8222
0.1992
0.0238
0.658
-0.2349
0.0097
0.3206
0.808
0.3043
-0.0164
0.4979
48
Table 2.7 Results of the NMDS analysis of understory species composition at each site, including the coefficients of determination
(R2) for correlations between ordination distances and distances in the original n-dimensional space.
Site
Number of
dimensions
Final
stress
McLennan Ditched Fen
3
Road-impacted Moderate Fen (RMF)
Instability
Monte
Carlo (p)
Total
variance
Variance Variance Variance
(axis 1) (axis 2) (axis 3)
7.55933
0.0412
0.004
0.836
0.495
0.122
2
5.66838
0.08439
0.004
0.95
0.701
0.249
Road-impacted Open Fen (ROF)
1
19.61929 0.08418
0.0438
0.787
0.787
Road-impacted Poor Fen (RPF)
2
3.79991
0.0572
0.012
0.972
0.877
0.095
Road-impacted Bog 1 (RB1)
3
4.21472
0.04562
0.0398
0.9
0.359
0.073
Road-impacted Bog 2 (RB2)
2
7.55826
0.06641
0.0279
0.927
0.057
0.87
0.22
0.469
49
Table 2.8 The Sørensen quantitative similarity index (SI) for each microform with
drainage at the RMF, RB1, and RB2 sites.
Site
RMF
RB1
RB2
Microform
SI
Hollow
0.319
Hummock
0.383
Hollow
0.538
Hummock
0.619
Hollow
0.624
Hummock
0.737
50
Table 2.9 The Pearson’s correlation coefficients (r) for the change in environmental and
canopy variables that occurred with drainage for the Sørensen quantitative similarity
index (SI) and the MRPP T statistic. Italicized values are the respective p values.
SI
T
-0.8274
-0.6245
0.0421
0.1850
-0.7887
-0.7986
0.0623
0.0567
-0.8528
-0.7879
0.0309
0.0627
0.6515
0.4872
0.1610
0.3270
0.1138
0.0339
0.8300
0.9492
-0.4513
-0.3124
0.3690
0.5467
Change in 2010 water table position
Change in average plot canopy openness
Change in total tree quadrat basal area
Change in average plot temperature at 10
cm below the moss surface
Change in average plot temperature at 20
cm below the moss surface
Change in average plot temperature at 30
cm below the moss surface
51
2.7 Figures
McLennan
RMF
ROF
RPF
RB1
RB2
0.9
0.8
0.7
SI
0.6
0.5
0.4
0.3
0.2
0.1
0
-4
-3
-2
-1
T statistic
0
1
2
Figure 2.1 Relationship between the SI and the MRPP statistic between control and
treatment plots within each site (r = 0.92010; p = 0.0083).
52
A)
Canopy openness
1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
-1
Simpson's
diversity
Axis 2
Total basal area &
water table
B)
Control Hummock
Treatment
Hummock
Treatment Hollow
-1.5
-1
-0.5
0 1
Axis
0.5
1
1.5
-1.5
-1
-0.5
Axis
0 1
0.5
1
1.5
1.5
1
Axis 3
0.5
0
-0.5
-1
Figure 2.2 The McLennan NMDS joint-plot depicting differences in understory species
composition between microforms in treatment and control plots (final stress = 7.55933,
n=15 with 25 taxa). See Table 2.6 and 2.7 for more ordination and MRPP details. The
angle and length of the lines that radiate from the centre of the ordination indicates the
direction and magnitude of the relationship. Only vectors that exceed the 0.4 total cutoff
are shown.
Axis 2
53
1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
-1
-1.2
-2
Total basal area &
water table
Temperature (10cm)
Simpson's diversity
Control Hummock
Control Hollow
Treatment Hummock
Treatment Hollow
-1
Axis
0 1
1
2
Figure 2.3 The RMF NMDS joint-plot depicting differences in understory species
composition between microforms in treatment and control plots (final stress = 5.66838, n
= 12 with 23 taxa). See Table 2.6 and 2.7 for more ordination and MRPP details. The
angle and length of the lines that radiate from the centre of the ordination indicates the
direction and magnitude of the relationship. Only vectors that exceed the 0.4 total cutoff
are shown.
54
Canopy openess
1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
-1
Total basal area
Water table
Axis 2
Control Hummock
Control Lawn
Treatment
Hummock
Treatment Hollow
-1.5
-1
-0.5
0 1
Axis
0.5
1
1.5
Figure 2.4 The RPF NMDS joint-plot depicting differences in understory species
composition between microforms in treatment and control plots (final stress = 3.79991,
n= 12 with 17 taxa). See Table 2.6 and 2.7 for more ordination and MRPP details. The
angle and length of the lines that radiate from the centre of the ordination indicates the
direction and magnitude of the relationship. Only vectors that exceed the 0.4 total cutoff
are shown.
55
A)
1.5
Canopy openess
Total basal area
1
Water table
Axis 1
0.5
Temperature (10cm)
0
Simpson's diversity
-0.5
Control Hummock
Control Hollow
Treatment Hummock
-1
Treatment Hollow
-1.5
-1.1
-0.6Axis 3-0.1
-1.5
-1
-0.5Axis 3 0
0.4
0.9
1
0.8
0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
-1
Axis 2
B)
-1.6
0.5
1
Figure 2.5 The RB1 NMDS joint-plot depicting differences in understory species
composition between microforms in treatment and control plots (final stress = 4.21472, n
=12 with 14 taxa). See Table 2.6 and 2.7 for ordination and MRPP details. The angle
and length of the lines that radiate from the centre of the ordination indicates the direction
and magnitude of the relationship. Only vectors exceed the 0.4 total cutoff are shown.
56
1.5
Control Hummock
0.5
Control Hollow
Axis 2
1
Treatment Hummock
-0.5
Treatment Hollow
0
-1
-1.5
-1
-0.5
0 Axis 1 0.5
1
1.5
Figure 2.6 The RB2 NMDS joint-plot depicting differences in understory species
composition between microforms in treatment and control plots (final stress = 7.55826, n
= 12, with 11 taxa). See Table 2.6 and 2.7 for more ordination and MRPP details.
57
Sedge
Grass
Forb
Ericaceous shrub
Deciduous shrub
Percent cover of vascular understory species
100
80
60
40
20
0
C
T
McLennan
C
T
RMF
C
T
ROF
C
T
RPF
C
T
RB1
C
T
RB2
Figure 2.7 Average percent cover of understory vascular plant groups within the control
and treatment plots in each site. The control plot is represented as ‘C’, while the
treatment plots are represented as ‘T’. Sedges include species from the genus Carex and
Eriophoram, while grasses include Poa spp. and Calamagrotis spp.. Forbs include R.
chamaemorus, S. trifolia, Stellaria longipies, C. palustris, Equisetum fluvitale, M.
trifoliata, P. palustris, and P. parvifolra. Ericaceous shrubs are Empetrum nigrum, A.
polifolia, O. microcarpus, V. vitis-ideae, L. groenlandicum, and Chamaedaphne
calyculata, while deciduous shrubs include Salix spp. and B. pumila.
58
Percent cover of understory non-vascular species
Lichen
Hummock Sphagnum
Hollow Sphagnum
Hollow true moss
Feather moss
Mid-hummock Sphagnum
Hummock true moss
100
80
60
40
20
0
C
T
McLennan
C
T
RMF
C
T
ROF
C
T
RPF
C
T
RB1
C
T
RB2
Figure 2.8 Average percent cover of non-vascular plant groups for the control and
treatment plots at each site. The control plot is represented as ‘C’, while the treatment
plots are represented as ‘T’. Lichen includes species from the genera Cladonia and
Cladina. Feather mosses include P. schreberi, P. crista-castrensis, and H. splendens.
Hummock Sphagnum includes species from section Acutifolia (i.e. S. fucsum, S.
capilifolium). Mid-Hummock Sphagnum includes S. magellanicum, while hollow
Sphagnum is S. angustifolium. Hummock true mosses include T. nitens, A. palustre, D.
undulatum, P. strictum, and Pohlia nutans, while hollow true mosses include M. triquetra,
Campylium spp., Drepanocladus spp., Caliergon giganteum, and Plagmonium ellipticum.
59
CHAPTER 3
THE EFFECT OF LONG-TERM DRAINAGE ON PLANT BIOMASS AND
PRODUCTIVITY IN BOREAL CONTINENTAL PEATLANDS
3.1 Introduction
3.1.1 Brief rationale
Ecosystem C fluxes are regulated by inputs such as gross primary productivity
and outputs such as soil respiration. Peatlands typically have positive net ecosystem
productivity (NEP) because plant productivity exceeds decomposition.
However,
according to the enzyme latch hypothesis, warmer temperatures and drier soil conditions
associated with climate change may shift peatlands from positive to negative NEP
(Freeman, et al., 2004). A lower water table position increases phenol oxidase activity,
an important microbial enzyme involved in phenolic mineralization, and stimulates
decomposition of peat (Freeman, et al., 2001). On the other hand, sustained drying will
affect ecosystem C balance by influencing plant community composition and
productivity as well as the amount and quality of C entering soils, all of which can also
influence decomposition. In Finland, where approximately 60% of peatlands have been
drained for forestry, Minkkinen et al. (2002) found that the drainage increased NEP,
predominantly by increasing tree biomass, and decreasing CH4 emissions. Thus, whether
or not peatlands remain a net C sink under drainage through land-use or drying through
climate change is uncertain, and will depend largely on plant responses in community
composition, NPP, and litter quality.
In Chapter 2, I show that plant community composition responded more strongly
to drainage in fens than in bogs.
Responses, however, were partly dependent on
microform, as plant community composition in hollows was more sensitive to changes in
water table position than in hummocks. While bog understory community composition
60
was more tolerant to drainage than fens, bog vegetation could respond more strongly to
drainage by altering rates of new growth and/or biomass allocation. In this study, I
quantified changes in aboveground plant biomass in response to drainage in the
McLennan poor fen (ditched site) as well as the road-impacted moderate fen, open fen,
poor fen, and two bog sites (RMF, ROF, RPF, RB1, and RB2, respectively). I also
quantified aboveground plant productivity (ANPP) at two of these sites, the McLennan
fen and the RMF.
3.1.2 Hypotheses and predictions
Bog species, particularly hummock species, are more adapted to soil-moisture
deficits than fen species, as fens are typically wetter than bogs. Additionally, species
composition in bogs is constrained by low nutrient availability and high pH, while fens
are less constrained by nutrient availability. While in the short-term, soil mineralization
rates and nutrient availability might increase with drainage (see section 1.3.4), on a
decadal scale understory productivity, and thus biomass, could decline due to decreases
in nutrient turnover rates with afforestation. Thus, I tested the following hypotheses:
H3.1: Forested bogs and fens will experience an increase in tree biomass due to
increases in root zone depth owing to water table drawdown. In the ROF, I
predicted that shrub biomass would increase with drainage.
H3.2: Because of differences in hydrology between bogs and fens, I hypothesized
that understory biomass would decline after drainage in fens but would not be
impacted by drainage in bogs.
The ANPP of the moss, understory vascular and tree community was measured at
the McLennan and RMF sites only. I focused on these sites because 1) they were
forested, allowing me to examine changes in both tree and understory productivity, 2)
because I expected community composition and long-term biomass accumulation to
change in fens moreso than in bogs, I wanted to focus on fens, and 3) the McLennan and
61
RMF sites represent two fen types (McLennan=poor fen; RMF=moderate rich fen).
Therefore, I hypothesized that:
H3.3 Due to increases in root zone depth from lowered a water table position,
drainage will increase tree productivity in fens thereby reducing light resources to
the understory and decrease understory productivity.
3.2 Methods
3.2.1 Effects of drainage on aboveground biomass
I sampled understory and tree biomass in the control and treatment plots at the
McLennan, RMF, ROF, RPF, RB1 and RB2 sites.
Using the basal diameter data
collected in tree quadrats at each site (see section 2.2.1), I used allometric equations to
determine total tree biomass. L. laricina biomass was determined using Equation 1,
which was developed for L. laricina in Alberta fens (Schicks, unpublished data). For P.
mariana greater than 1.6 cm in diameter, biomass was determined using equation 2
(Wieder, et al., 2009). However, this equation is not suitable for small stems as it yields
negative biomass values. Thus, for P. mariana smaller than 1.6 cm in diameter, total
biomass was determined using equation 1.
.
.. Equation 1
!." #169.1 '( ) 146.5 '( Equation 2
To sample the understory biomass (including forb, sedge, and shrub components),
destructive biomass quadrats (0.25m2) were established in each plot described in section
2.2.1 (3 quadrats x 2 plots x 6 sites, n = 6). Plant material was removed at the ground
level in August of 2010 and sorted in the laboratory. Live biomass was separated from
litter, and forb, sedge, and shrub biomass was separated, dried to a constant mass, and
weighed.
62
3.2.2 Effects of drainage on ANPP
Measurements of bryophyte and understory ANPP measurements of bryophyte
and understory NPP occurred in the summer of 2009 and 2010 at the RMF and
McLennan sites. Trees were harvested in 2009 and 2010 at the McLennan and RMF
sites, respectively. The ANPP for each plant group was scaled to the plot level using data
on percent cover from Chapter 2.
I destructively harvested basal tree disks for ring width measurements. I used
data on tree basal diameter (section 2.2.1) to select trees that represented the range of
stem size present in each tree quadrat. I sampled 20 basal disks from each species
present at each control and treatment plot.
Ring widths were analyzed using
WinDENDRO V6.1 (Regent Instruments, Quèbec, Canada) and used to calculate tree
biomass for each annual ring based on the above allometric equations. Annual changes
in ANPP were estimated by subtracting the biomass (using Equations 1 and 2) of year n-1
from year n.
Overstory ANPP was estimated for pre-drainage (15 year average
immediately prior to ditching or road construction) and post-drainage timeframes (the
most recent 15 years, all post-drainage) based on estimates of the timing of linear feature
construction and cross-dating with tree rings.
Understory aboveground biomass was collected from triplicate randomly located
50 x 50 cm destructive biomass quadrats in the control and treatment plot at each site
during both 2009 and 2010 (3 biomass quadrats in 2009 + 3 biomass quadrates in 2010).
Because sedges and forbs are ephemeral plants, any live biomass was considered to be
the current years ANPP and sampling occurred in early August to capture peak growing
season production.
Estimates of shrub NPP were defined as terminal growth only
(leaves, flowers, new twigs), as radial stem growth is difficult to obtain, especially in
dwarf shrubs (c.f. Bond-Lomberty, 2004). All samples were dried at approximately 75°C
to a constant mass and weighed. Data were averaged by plot.
Bryophyte NPP was quantified using Clymo’s (1970) cranked wire approach. A
5 m linear transect containing 50 wires was established at the treatment and control plots
63
of the McLennan and RMF sites (1 transect x 2 plots x 50 wires x 3 sites n=300). Yearly
growth rates were determined through the vertical incremental growth relative to the wire
(cm year-1) in both 2009 and 2010. Surface cores for each moss type that occurred within
the transects were collected to obtain a stem bulk density value, or productivity
coefficient, to convert the vertical incremental growth to NPP (g m2 year-1). For the
Sphagnum moss productivity coefficient I assumed the capitula mass remained constant
(Vitt, 2007), therefore I removed the uppermost 1 cm of the stem and branches of each
individual of the surface core. To obtain a productivity coefficient for true mosses, I
removed and weighed the top 1 cm portion and I used a 1 cm portion after lateral branch
length remained constant for feather moss (P. schreberi; Benscoter and Vitt, 2007). I
scaled each species of moss NPP to the plot level using the proportion of wires that each
species comprised.
3.2.3 Statistical Analyses
All weights were converted to units of C by assuming a C concentration of 50%
dry biomass (Minkkinen, et al., 1999). Differences in aboveground biomass as well as
aboveground biomass specific to each plant group were evaluated between plots within
each site using Student’s t-tests (α = 0.05) in SAS version 9.2 (SAS Institute Inc., Cary,
NC, USA). Data that failed to meet normality, using the Shapiro-Wilks statistic, were
transformed using the natural logarithm (ln). Data that could not be transformed to meet
normality assumptions were evaluated using the Mann-Whitney non-parametric test.
Relationships between aboveground biomass for each plant group and average seasonal
water table position as well as canopy openness (see Chapter 2 for water table and
canopy openness) were explored using correlation analyses. To determine the effect of
drainage on the change in biomass between plots within sites, I calculated the Sørensen
quantitative similarity index (SI) using EstimateS version 8.2.0 (Coldwell, 2006). The
ANPP data were analyzed similarly with 2009 and 2010 measurements grouped together
for each plot, as I was interested in average differences between plots and not the interannual variability within plant groups of each plot.
64
3.3 Results
3.3.1 Aboveground Biomass
Total aboveground biomass was higher at the treatment plot compared to the
control plot at all sites except the RB1 site (Table 3.1). At the McLennan, RPF, and RB2
sites, tree biomass was greater at the treatment plot than at the control plot (Table 3.1).
However, tree biomass was greater at the control plot than the treatment plot at the RB1
site (Table 3.1), due to larger basal diameters and higher tree density in the control plot.
There was no difference in tree biomass between the control and treatment plots at the
RMF site (Table 3.1). Total understory aboveground biomass was higher in the treatment
plot than the control plot only at the ROF site, due to increased shrub biomass (t(4) = -4.26,
p = 0.0131; Table 3.1). Forb biomass did not differ between the treatment and control
plots at any sites. Sedge biomass was lower in the treatment plot than in the control plot
in the RMF site (Table 3.1). Across the plots at each site, tree biomass was negatively
correlated to both shrub and sedge aboveground biomass (shrub: r=-0.5758, p=0.0501;
sedge: r=-0.5903, p=0.0433). Tree aboveground biomass was positively correlated with
the data on water table position (r = 0.6457, p=0.0233) while shrub aboveground biomass
was positively correlated with canopy openness (r=0.5819, p=0.0471).
The SI found that biomass at bogs as well as the RMF and RPF sites did not
change much with drainage, while biomass the ROF and McLennan site was drastically
different between plots (Table 3.2).
3.3.2 Aboveground net primary productivity (ANPP)
Prior to drainage at the McLennan site, mean tree ANPP was slightly higher in the
control plot than the treatment plot (Figure 3.1). Tree species varied in their response to
drainage at this site, as P. mariana ANPP increased approximately 6-7 years after
drainage, while L. laricina ANPP showed no increases following drainage (Figure 3.1).
65
At the RMF site, there were no differences in tree ANPP in the control and treatment
plots prior to or following drainage (Figure 3.2).
Understory vascular ANPP was greater in the treatment plot than the control plot
at the McLennan site. This was due to increases in forb (z = 2.8526, p = 0.0043) and
sedge (z= 2.5736, p = 0.0101) ANPP (Table 3.2). At the RMF site, total understory
ANPP did not differ between the control and treatment plots, though a decrease in sedge
productivity occurred (Table 3.2).
Moss productivity was higher in the control plot than the treatment plot at the
McLennan site (Figure 3.3). Moss NPP was attributed to Sphagnum at the control and P.
schreberi at the treatment plot. At the RMF site, the hummock moss (T. nitens) had
higher NPP at the treatment plot than the control plot (Figure 3.4), while moss NPP in
hollows (mostly Drepanocladus spp.) was higher at the control plot than the treatment
plot.
Canopy openness was not related to understory vascular ANPP, or NPP of any
understory plant groups, including moss. However, a correlation of the log-transformed
values of the moss and tree ANPP fractions of total ecosystem ANPP at the RMF and
McLennan sites, reveal a significant negative relationship (r = -0.9777, p = 0.0223).
There was a strong positive correlation between tree productivity and water table position
(r=0.9992, p=0.0004) and the SI revealed that the McLennan site aboveground
productivity was more impacted by drainage than the RMF site (0.423 and 0.826,
respectively).
3.4 Discussion
The overall objective of this study was to quantify the effects of drainage on
peatland plant biomass and productivity. I expected that drainage would increase rooting
zone depth, thus leading to more tree productivity and canopy closure in forested sites.
Reduced light availability and other environmental changes associated with canopy
66
closure can affect understory plant composition; however, I expected that plant biomass
would be reduced by drainage in fens more than in bogs.
3.4.1 Impact of drainage on tree aboveground biomass and ANPP
In this study, increases in tree biomass with drainage occurred at both poor fen
sites as well as the RB2 site. This finding is similar to other drainage experiments (Laiho,
et al., 1999; Minkkinen et al., 1999; Minkkinen et al., 2002; Laiho et al., 2003).
However, there are differences in the degree of increase between my sites and those
drainage experiments in Fennoscandinavia.
The RB1 and RB2 sites both have
considerably higher tree biomass than Finnish bogs as reported in Minkkinen et al. (1999;
Table 3.4). Drainage caused an increase in tree biomass of approximately 400 g C/m2 at
the RB2 site, which was similar to the drainage impact on tree productivity in a
Sphagnum bog in Finland. However, aboveground tree biomass was considerable higher
in the control plot than the treatment plot at the RB1 site. The RB1 site was older than
the RB2 site, with trees approximately 130 and 85 years old, respectively. Stand age may
in part explain why my two bog sites responded different to drainage as biomass
accumulation in P. mariana in Alberta bogs was shown to decline after 100 years
(Wieder, et al., 2009). However, the position of road construction relative to water flow
at this site may also have influenced changes in tree biomass.
Laiho and Laine (1997) found that in treed mesotrophic peatlands, Picea abies
biomass increased by ~230% 22 years after drainage and ~300% 30 years after drainage.
In open peatlands, drainage experiments show significant increases in tree biomass
(~3000g C/m2; Minkkinen, et al., 1999). Similar increases (230%) of aboveground tree
biomass occurred at the McLennan site, which was drained 25 years ago. However,
despite drainage occurring approximately 40 years ago, the observed increase in
aboveground tree biomass at the RPF site is considerably lower (170%) than the Finnish
drainage experiments, and the ROF site experienced no tree recruitment with drainage.
This is likely due to the degree of water table drawdown with drainage between ditching
67
sites and road-impacted sites as well as the impact of trees as a positive feed back to
drainage.
L. laricina and P. mariana appeared to respond differently to drainage. Similar
results have been observed by Lieffers and Rothwell (1987), who explored the effects of
lowered water table positions through road construction on P. mariana and L. laricina
growth. They found that in dry sites, where canopy closure was highest, P. mariana
growth increased while L. laricina growth decreased due to shade intolerance. In more
mesic sites, where canopy closure was intermediate, L. laricina productivity was higher
than P. mariana (Lieffers & Rothwell, 1987). My results partially agree with these
results. At the McLennan poor fen, P. mariana responded to drainage while L. laricina
did not. Although I did not explore productivity at the bog sites, it is likely that the tree
productivity increased with drainage at the RB2 site as Chapter 2 reveals increases in
canopy closure as well as basal diameter in the treatment plot from the control plot and a
reasonable increase in aboveground tree biomass with drainage. Even after drainage, the
water table position at the RMF site was still at or above the peat surface in hollows,
which likely explains the lack of a drainage effect on tree biomass. The RMF site was
wetter than my other sites or those studied by Lieffers and Rothwell (1987). The RMF
site was entirely L. laricina and productivity showed no response to road construction. In
their wettest site, Lieffers and Rothwell (1987) found that L. laricina roots were confined
to the top 20cm in of the peat profile and productivity was reduced four fold relative to
the productivity rates at the optimum water table position and intermediate canopy cover.
Despite changes in species composition shown in Chapter 2, it is likely that drainage was
not sufficient at the RMF site to stimulate increases in tree biomass accumulation.
Tree aboveground biomass was positively correlated with the average water table
position across the plots at each site. This suggests that the degree of the tree response to
climate change will depend on the effect of climate change on the water table position.
The degree of drying with climate change could push the tree community to initiate
significant positive feedbacks, such as increases evapotranspiration and interception (Van
Seters, 1999 in Van Seters and Price, 2001; Sarkkola, et al., 2010), thereby increasing the
68
drop in water table position.
For example, immediately following drainage at the
McLennan site, water table position dropped approximately 37 cm (Hillman, et al., 1990).
Current estimates of water table position are greater than 300 cm below the moss surface
(Chapter 2). This is likely due increased evapotranspiration and interception by the tree
canopy.
It is likely that the road-impacted sites also experience increased
evapotranspiration and interception due to increases in tree biomass and canopy closure.
However, the drop in water table may not have been sufficient to initiate the strong
feedbacks observed in the McLennan site.
3.4.2 Impacts of trees on understory community biomass and productivity
Understory biomass was not correlated with the water table position, but some
plant groups were correlated with tree and canopy characteristics. This implies that
drainage did not impact understory biomass and that understory aboveground biomass
reflects the tree response to drainage. Because understory biomass did not change with
drainage or the associated increases in tree canopy, it is possible that the understory in
treed peatlands is adapted to lower light conditions.
This explains the increase in
understory biomass at the ROF site, as it is unforested.
However, tree size or canopy openness was not related to ANPP of any
understory plant groups, including moss. This may be a result of small samples size, or it
could suggest that drivers other than aboveground tree biomass and canopy closure are
governing the observed differences in productivity between plots. There was discrepancy
between shrub ANPP and aboveground biomass at the McLennan site, as shrub biomass
did not change with drainage while shrub ANPP decreased. Immediately following
drainage, the plant community can take up nutrients that were formerly immobilized in
deeper peat layers (Laiho, et al., 1999; Laine, et al., 2006). This would increase shrub
biomass in the short-term, but over time shrub productivity may begin to decline as
canopy closure and increased competition limits new growth. Although not statistically
significant, shrub productivity was also lower at the RMF treatment plot than the control
plot, despite no change in biomass between plots, which suggests that shrubs were
69
perhaps also impacted by increases in nutrient pools immediately following drainage. It
is also possible that observed increases in shrub biomass at the ROF site occurred due to
this initial increase in nutrient availability. Because this site was open (unforested), the
understory community had no light limitation or other constraints on growth imposed by
the tree community. Shrub biomass accumulation at this site may have occurred at an
accelerated pace until excess nutrient pools were tied up in standing woody-shrub
biomass.
Drainage led to replacement of Sphagnum moss by feather moss at the McLennan
and RPF sites (Chapter 2). Feather mosses become better competitors with Sphagnum
with high degrees of canopy closure. Sphagnum moss productivity in the control plot
was 1.5 times higher than Pleurozium productivity in the treatment plot at the McLennan
site. This is not surprising, as Sphagnum moss has higher rates of productivity than
feather moss (Swanson & Flanagan, 2001). However, this has implications for peat
accumulation rates, as Sphagnum mosses are recalcitrant due to low N concentrations and
sphagnic acid (Aerts, et al., 1999) and have higher soil inputs than feather mosses
(Trumbore & Harden, 1997).
Goulden and Crill (1997) proposed that trade-offs between moss and tree
productivity would occur with drying, meaning that vascular and non-vascular
components of the plant community would respond in opposite directions with changing
soil moisture conditions. If true, this would minimize spatial variation in ecosystem-level
productivity across boreal ecosystems (Turetsky, et al., 2010). In this study, I found that
tree productivity increased while moss productivity decreased at the McLennan site.
Even if increases in tree productivity compensated for declines in moss productivity with
drying, increasing amounts of woody biomass and productivity in peatlands have
implications for other aspects of ecosystem ecology. For example, increases in woody
biomass would affect soil quality by increasing lignin-rich litter.
There are also
implications for wildfire risk in peatlands. Increases in tree biomass would have obvious
implications for canopy fuels, which is likely to increase fire risk. However, in addition,
70
a replacement of Sphagnum moss by feather moss will reduce soil moisture in peatlands,
and could increase the burning of ground fuels.
3.4.3 Conclusions
Unlike the Finnish drainage results (c.f. Minkkinen, et al., 1999; Laiho, et al.,
2003), which showed that biomass of peatland mosses, forbs, and shrubs, decreased with
drainage, this study shows that non-woody vascular biomass was not affected by drainage
at any of my sites. Across all sites, except for the RB1 and RMF sites, tree or shrub
biomass increased with drainage. For example, tree biomass increased by 210% and
150% at the McLennan and RB2 sites, while shrub biomass increased by 400% at the
ROF. The SI showed that total aboveground vascular biomass varied the most between
the treatment and control plots at the ROF and the McLennan ditched fen. My results
supported the hypothesis that woody biomass would increase with drainage (H3.1).
However, my hypothesis that fen biomass would be reduced more strongly than bog
biomass (H3.2) following drainage was not supported.
71
3.5 Literature Cited
Aerts, R., VerHoeven, J. T., & Whigham, D. F. (1999). Plant-mediated controls on
nutrient cycling in temperatre fens and bogs. Ecology, 80, 2170-2181.
Benscoter, B. W., & Vitt, D. H. (2007). Evaluating feathermoss growth: a challenge to
traditional methods and implications for the boreal carbon budget. Journal of Ecology,
95, 151.158.
Bond-Lomberty, B., Wang, C., & Gower, S. T. (2004). Net primary production and net
ecosystem production of boreal black spruce wildfire chronosequence. Global Change
Biology, 10, 473-497.
Clymo, R. S. (1970). The growth of Sphagnum: methods of measurements. Journal of
Ecology, 58, 13-49.
Coldwell, R. K. (2006) Estimates: Statistical estimate of species richness and shared
species from samples. Version 8.2.0. University of Connecticut. Storrs, Connecticut,
U.S.A.
Freeman, C., Ostle, N., Fenner, I., & Kang, H. (2004). A regulatory role for phenol
oxidase during decomposition in peatlands. Soil and Biochemistry, 36, 1663-1667.
Freeman, C., Ostle, N. & Kang, H. (2001). An enzymatic ‘latch’ on global carbon store.
Nature, 409, 149.
Goulden, M. L., & Crill, P. M. (1997). Automated measurements of CO2 exchange at the
moss surface of a black spruce forest. Tree physiology, 17, 537-542.
Hillman, G. R., Johnson, J. D., & Takyi, S. K. (1990). The Canada-Alberta Wetlands
drainage and improvement for forestry program. Edmonton: Foresty Canada and the
Alberta Forest Service.
Laiho, R., & Laine, J. (1997). Tree stand biomass and carbon content in age sequence of
drainaged pine mires in southern Finland. Forest Ecology and Management, 93, 161169.
Laiho, R., Sallantaus, T., & Laine, J. (1999). The effect of forestry drainage on vertical
distributions of major plant nutrients in peat soils. Plant and Soil, 207, 169-181.
Laiho, R., Vasander, H., Pentillä, T., & Laine, J. (2003). Dynamics of plant-mediated
organic matter and nutrient cycling following water-level drawdown in Boreal peatlands.
Global Biogeochemical Cycle, 17, 1053.
Laine, J., Laiho, R., Minkkinen, K., & Vasander, H. (2006). Forestry and Boreal
Peatlands. In R. K. Wieder, & D. H. Vitt (Eds.), Ecological Studies 188: Boreal
Peatlands (pp. 330-357). Berlin, Germany: Springer.
Lieffers, V. J., & Rothwell, R. L. (1987). Rooting of peatland black spruce and tamarack
in relation to depth of water table. Canadian Journal of Botany, 65, 817-821.
72
Minkkinen, K., Vasander, H., Jauhiainen, S., Karsisto, M., & Laine , J. (1999). Postdrainage changes in vegetation composition in carbon balance in Lakkasuo mire,
Central Finland. Plant and Soil, 207, 107-120.
Minkkinen, K., Korhonen, R., Savolainen, I., & Laine, J. (2002). Carbone balance and
radiate forcing of Finnish peatlands 1900-2100 - the impact of forestry drainage. Global
Change Biology, 8, 785-799.
Regent Instruments (2008). WinDENDRO Version 6.1. Quèbec, Canada.
Sarkkola, S., Hökkä, H., Koivusalo, H., Nieminen, M., Ahti, E., Päivänen, J., et al.,
(2010). Role of tree stand evapotranspiration in maintaining satisfactory drainage
conditions in drained peatlands. Canadian Journal of Forest Research, 40, 1485-1496.
SAS Institute Inc.
Institute.
(2008).
SAS Version 9.2. Cary, North Carolina, U.S.A.: SAS
Swanson, R. V. & Flanagan, L. B. (2001). Environmental regulation of carbon dioxide
exchange at the forest floor in a boreal black spruce ecosystem. Agricultural and Forest
Meteorology, 108, 165-181.
Trumbore, S. E., & Harden, J. W. (1997). Accumulation and turnover of carbon in
organic and mineral soils of the BOREAS northern study area. Journal of Geophysical
Research, 102, 817-828.
Turetsky, M. R., Mack, M. C., Hollingsworth, T. N., Harden J. W. (2010). The role of
mosses in ecosystem succesion and fucntion in Alaska’s boreal forest. Canadian
Journal of Forest Research, 40, 1237-1264.
Van Seters, T. E., & Price, J. S. (2001). The impact of peat harvesting and natural
regeneration on the water balance of an abandoned cutover bog, Quèbec. Hydrological
processes, 15, 233-248.
Vitt, D. H. (2007). Estimating moss and lichen ground layer net primary production in
tundra, peatlands, and forests. In T. J. Fahey & A. K. Knapp (Eds.), Principles and
standards for measuring primary production (pp. 82-105). New York, New York, U.S.
A.: Oxford University Press.
Wieder, R. K., Scott, K. D., Kamminga, K., Vile, M. A., Vitt, D. H., Bone, T., et al.,
(2009). Postfire carbon balance in Boreal bogs of Alberta, Canada. Global Change
Biology, 15, 63-81.
73
3.6 Tables
Table 3.1 Mean plant group and total biomass for plot at each site (n= 1 for tree biomass, n=3 for shrub, sedge, and forb biomass).
Same letter superscripts denote non-significant differences within plant groups for each site (p>0.05). Data are means ± 1 SE. Total
biomass SE is compounded.
Site
McLennan ditched fen
Road-impacted Moderate Fen (RMF)
Road-impacted Open Fen (ROF)
Road-impacted Poor Fen (RPF)
Road-impacted Bog 1 (RB1)
Road-impacted Bog 2 (RB2)
Plot
Control
Treatment
Control
Treatment
Control
Treatment
Control
Treatment
Control
Treatment
Control
Treatment
Tree
biomass
(g of C/m2)
1383.5a
3160.0b
628.4a
624.1a
0
0
1709.1a
2892.4b
1791.4a
1122.9b
824.4a
1274.3b
Shrub
biomass
(g of C/m2)
95.6 ± 70.3a
37.7 ± 7.3a
125.7 ± 84.1a
166.6 ±70.0a
100.1 ±18.6a
420.7 ± 74.2b
85.9 ± 46.4a
100.6 ± 25.1a
92.1 ± 44.2a
129.7 ± 44.3a
105.7 ± 31.0a
137.6 ± 23.3a
Sedge
biomass
(g of C/m2)
9.3 ± 4.1a
0b
21.1 ± 2.2a
7.5 ± 2.0a
8.7 ± 2.9a
12.4 ± 1.6a
0a
0.1 ± 0.1a
0.34 ± 0.34a
0a
0a
0a
Forb biomass
(g of C/m2)
3.1 ± 1.4a
0.1 ± 0.1a
5.4 ± 2.6a
26.8 ± 11.0a
0.1 ± 0.1a
0.7 ± 0.4a
15.2 ± 3.6a
6.5 ± 2.3a
4.66 ± 1.2a
2.86 ± 1.7a
9.1 ± 4.6a
3.6 ± 1.7a
Total biomass
(g of C/m2)
1488.4 ± 70.4
3197.8 ± 7.3
780.6 ± 84.2
825.0 ± 70.9
108.9 ± 18.3
433.8 ± 74.2
1810.3 ± 46.5
2999.7 ± 25.2
1888.5 ± 44.2
1255.5 ± 44.4
939.2 ± 31.4
1415.5 ± 23.4
74
Table 3.2 The Sørensen quantitative similarity index (SI) for biomass at each fen and bog
site.
Site
SI
McLennan Ditched Fen
0.579
Road-impacted Moderate Fen (RMF)
0.860
Road-impacted Open Fen (ROF)
0.384
Road-impacted Poor Fen (RPF)
0.921
Road-impacted Bog 1 (RB1)
0.830
Road-impacted Bog 2 (RB2)
0.856
75
Table 3.3 The productivity (means ± SE) over two years at the McLennan ditched fen (tree and moss n = 1; understory vascular n=12)
and the Road-impacted Moderate Fen (RMF; tree and moss n = 1; understory vascular n=12). Same letter superscripts denote nonsignificant differences in plant group ANPP between plots at each site (p>0.05).
Site
McLennan
Plot
Control
Tree ANPP
2
2
2
Forb ANPP
2
Total understory
vascular ANPP
Moss
(g C/m2/yr)
(g C/m /yr)
(g C/m /yr)
(g C /m /yr)
(g C/m /yr)
47.7 ± 8.0
24.9 ± 7.5a
7.1 ± 2.3a
3.3 ± 0.8a
35.3 ± 5.8a
66.6 ± 10.1
9.8 ± 3.7b
0.8 ±0.8b
0.04 ± 0.03b
10.6 ± 3.9b
44.2 ± 6.8
Treatment 278.4 ± 64.4
RMF
Shrub ANPP Sedge ANPP
2
(g C/m /yr)
Control
26.1 ± 11.9
41.3 ± 11.7a
12.3 ± 4.1a
11.8 ± 3.3a
65.5 ± 11.6a
150.8 ± 32.4
Treatment
24.3 ± 6.5
30.0 ± 5.3a
7.7 ± 1.3a
26.2 ± 7.1a
63.9 ± 8.1a
214.7 ± 59.7
76
3.7 Figures
Control L. laricina
Treatment L. laricina
Control P. mariana
Treatment P. mariana
Average tree productivity (g C/year)
160
140
120
100
80
60
40
20
0
2010
2005
2000
1995
1990
1985
1980
Figure 3.1 Average tree ANPP (g C/year) of P. mariana and L. laricina at the McLennan
site where drainage occurred in 1986 (n=6). Error bars are ±1 standard error of the mean.
77
Control
Treatment
Average tree productivity
(g C/year)
80
60
40
20
0
2010
2005
2000
1995
1990
1985
1980
Figure 3.2 Average tree ANPP (g C/year) of L. laricina at the RMF site where road
construction occurred in 1991 (n=6). Error bars are ±1 standard error of the mean.
78
Tree
Shrub
Sedge
Forb
Moss
400
ANPP (g C/m2/year)
350
300
250
200
150
100
50
0
Control
Treatment
Figure 3.3 Average ANPP (g C/m2/year) for each plot of the McLennan site. Error bars
are ±1 standard error of the mean.
79
Tree
Shrub
Sedge
Forb
Moss
400
ANPP (g C/m2/year)
350
300
250
200
150
100
50
0
Control
Treatment
Figure 3.4 Average ANPP (g C/m2/year) for each plot of the RMF site. Error bars are ±1
standard error of the mean.
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CHAPTER 4
CONCLUSIONS
4.1 Effects of drainage on plant community composition, biomass, and productivity in
boreal continental bogs and fens
The first objective of this thesis was to quantify the effects of drainage on
peatland plant community composition.
Using NMDS ordinations of plant species
abundance followed by MRPP tests and measurement of the SI, I quantified the effect of
drainage on community composition in two forested bogs and four fens. Generally, I
found that vegetation responses to drainage in bogs were limited. At the RB1 site, there
was no difference in canopy closure between the treatment and control plots. Although
the RB2 site experienced approximately a 30% increase in canopy closure with drainage,
both bog sites also experienced an increase in lichen and Sphagnum cover with drainage.
Given that both of these ground-layer groups are associated with high light and open
canopy conditions, it is likely that bog trees did not respond strongly enough to drainage
to limit light availability for the understory community. My results also suggest that
plant communities in hollows changed more than those on hummocks following drainage
in the two bogs. For example, shrub cover increased in hollows but not hummocks with
drainage, while sedge and forb cover did not vary by microtopography.
Relative to bogs, I found larger changes in species composition in response to
drainage in forested fens. The SI values in forested fens were generally lower than those
in bogs. Although the change in canopy closure between the RPF and RB2 sites was
similar (i.e. a 10% increase in closure with drainage), the treed poor fen sites (McLennan
and RPF) had greater than 70% canopy cover after drainage, while the bog sites were
approximately 10% less. The change in canopy cover in the forested fens after drainage
likely lead to reduced light availability for understory species, and also could have
affected soil temperatures and nutrient availability due to changing litter quality inputs to
soils. I found that Sphagnum moss cover decreased while feather moss cover increased at
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the poor fen sites. These sites also experienced a decrease in forb and sedge cover with
drainage. These changes are consistent with understory communities responding to the
reduced light availability. While my results suggest that most of the fen sites included in
this study experienced significant changes in vegetation, drainage did not influence plant
composition in the open (unforested) poor fen site (ROF). I found little evidence of
change in either vascular or understory vascular plant abundance with drainage at this site.
Across both bog and fen sites, the T statistic and SI values were negatively
correlated with the change in tree basal area occurring with drainage. The T statistic and
SI values as also were negative correlated with the change in canopy openness. Together,
results from this study suggest that changes in tree and canopy characteristics with
drainage serve as a dominant control on understory community composition, and thus are
important in understanding the resilience (i.e. the capacity to recover after disturbance) of
peatland vegetation to environmental change.
My second objective was to quantify the effects of drainage on aboveground
biomass and ANPP. I hypothesized that tree biomass would increase in all sites with
drainage, but that understory biomass would decrease in fens but not in bogs postdrainage. My results did not support my hypotheses. I found that tree biomass increased
at the McLennan, RPF, and RB2 sites but did not change at the RMF and RB1 sites.
Understory aboveground biomass was unaffected by drainage across most sites, except
for increases in shrub biomass at the ROF site.
I quantified ANPP at the McLennan and RMF sites, and hypothesized that
drainage would increase tree productivity and decrease understory productivity. At the
McLennnan site, tree productivity increased and understory productivity decreased with
drainage. At the RMF, tree productivity and total vascular understory productivity did
not change with drainage, however, hollow moss productivity decreased by 30% while
hummock productivity was similar between plots. While I only quantified the effects of
drainage on productivity in two sites, my results in general suggest that drainage
increases tree productivity and decreases moss productivity. Changing the ratio of of
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woody to moss biomass in peatlands will influence other aspects of ecosystem behavior,
such as decomposition and combustion losses due to wildfire.
4.2 Comparing peatland drainage in boreal regions: Canada vs. Finland
In Finland, drainage has led to increases in tree biomass in both bogs and fens,
even on sites that were unforested prior to drainage (Laine et al., 1995; Laiho, et al.,
1999; Minkkinen et al., 1999; Minkkinen et al., 2002; Laiho et al., 2003; Murphy, et al.,
2009a). This typically caused a complete replacement of Sphagnum mosses by feather
mosses, as well as a shift in understory species composition towards forest vegetation
(Laine, et al., 1995; Minkkinen, et al., 1999; Murphy et al., 2009a). However, in bog
sites, species that are known to tolerate drier conditions (such as feather mosses) persisted
after drainage (Minkkinen, et al., 1999; Murphy, et al., 2009a). In terms of changes in
biomass, drainage decreased understory vascular biomass, particularly shrubs, in fens but
resulted in no change or increases in understory biomass in bogs (Laine, et al., 1995;
Minkkinen, et al., 1999; Murphy, et al., 2009a).
In pristine, undrained peatlands, nutrient fluxes are dominated by bryophytes and
graminiods (Laiho, et al., 2003). However, after drainage, nutrient fluxes are governed
by woody inputs due to the increase in tree above- and belowground biomass, which
decreases nutrient turnover rates (Laiho, et al., 2003). Overall, drainage of Finnish
peatlands increases the carbon storage of peat due to more acidic soils, colder soil
temperatures, and poorer litter quality, all associated with increased conifer cover (Laine,
et al., 1995; Laiho & Laine, 1996 in Minkkinen, et al., 2002; Minkkinen and Laine,
1998; Minkkinen, et al., 2002). On a decadal scale, drainage of Finnish peatlands has
resulted in net cooling (i.e., decreases in radiative forcing of about -2.6 MW m-2) due to
increased tree biomass, increased C storage in surface peat, and decreases in CH4
emission (Minkkinen, et al., 2002).
Boreal continental peatlands in western Canada tend to have thick acrotelms and
are often forested, while Finnish peatlands have higher water table positions and are often
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unforested. Tree biomass and canopy cover increased with drainage at most of my sites,
which is similar to the Finnish results. However, unlike the Finnish experiments where
forest shrubs and mosses replaced peatland vegetation, the understory communities in my
sites were still dominated by typical peatland species after drainage.
I did not see
peatland species displaced with drainage at any of my sites. Species in boreal continental
peatlands are adapted to the drier, forested conditions and thick acrotelms contrary to
those found in the maritime climate of Finnish peatlands. This may explain why changes
in peatland species composition in this thesis did not mimic the changes observed in
Finnish drainage experiments.
Similar to the plant community results, non-woody understory aboveground
biomass did not seem to be affected by drainage. These results show that boreal peatland
responses to drainage vary not only by peatland type (see section above), but also by
region. Western Canadian peatlands are drier and more forested than Finnish peatlands,
and thus may be more resistant to drainage, at least in terms of plant community
composition and aboveground productivity.
4.3 Implications of peatland drainage for net ecosystem productivity
Changes in plant community composition with drying may influence ecosystem C
cycling by affecting soil climate, root productivity and biomass, as well as litter quality,
all of which can influence soil organic matter quality and nutrient cycling. Laiho et al.
(2003) found that the major litter sources prior to drainage were from Sphagnum, sedges,
and shrubs. After drainage, however, tree litter (i.e. fine roots and foliage) was the major
source of litter incorporated into the peat soils (Laiho et al. 2003). My results similarly
show that drainage of both bogs and fens increased aboveground tree biomass, while
shrub biomass increased after drainage at the ROF site. Tree productivity increased with
drainage at the McLennan site but not the RMF. Because woody biomass is high in
lignin, low in N, and tends to decompose slowly, an increase in tree soil inputs could
affect peatland nutrient cycling and peat accumulation rates.
This may increase C
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sequestration in the aboveground standing biomass as well as the belowground soil C
stores.
My results have implications for future fire risk in Canadian peatlands. Wildfire
is arguably the most important natural disturbance in Canadian forests and peatlands.
During fire, C is lost to the atmosphere during combustion of surface peat, moss, and
aboveground fuels. Surface albedo tends to increase post-fire, particularly in winter
months, and fire increases ecosystem respiration by increasing root respiration and
decomposition. Wieder et al. (2009) found that peatlands remained a net source of C for
about 10 years post-fire, after which recolonization of vegetation led to a recovery of C
uptake.
Kasischke and Turetsky (2006) found the frequency of large fire disturbances has
increased in boreal North American from the 1960’s to 1990’s. These large fires are also
occurring more frequently late in the growing season (Kasischke & Turetsky, 2006).
Flannigan et al. (2009) suggest that changing fire patterns as a result of climate change
may make peatlands more vulnerable to deep soil consumption, as burning is more likely
to occur during the period of maximum water table drawdown and fuel exposure late in
the growing season. Changes in community composition associated with drainage and
potentially climate change can influence the type and quantity of fuels available for
wildfires. I observed an increase in tree or shrub biomass, which increases the quantity
of canopy and fine fuels. I also observed a decrease in Sphagnum, which reduces soil
moisture levels and could lead to deeper peat smoldering. Furthermore, Benscoter et al.
(2011) found that peat can smolder in wet conditions if the soil bulk density was
sufficiently high.
An increase in bulk density of the peat through subsidence and
increased decomposition as a result of decreased water table position, could lead to more
deeper burning into the peat. Overall, increases in soil moisture deficits and fine fuels,
may result in high density, dry fuels for wildfire, which could increase the radiative
forcing of peatlands.
85
4.4 Study limitations and suggestions for future research
This study examined changes in plant community composition and productivity a
few decades after drainage following road construction or experimental ditching. There
is little information available on how the sites were affected immediately by these
drainage events. For example, it would be useful to know whether or not my treatment
plots were affected by subsidence. Subsidence occurs when the peat soil matrix collapses
and compresses in response to water removal.
This affects bulk density, thereby
increasing water retention and decreasing hydraulic conductivity (Minkkinen & Laine,
1998; Silins & Rothwell, 1998; Laine, et al., 2006). The increasing mass of trees may
further subsidence through soil compaction (Minkkinen & Laine, 1998). Subsidence
could reduce the distance of the peat surface to the water table after drainage, minimizing
the effects of drainage on acrotelm thickness. This could cause a rewetting of the
community, which would marginalize the overall effect of drainage, although peat
properties would be fundamentally altered from pristine conditions.
A better
understanding of whether indeed subsidence occurred in any of my sites and how this
influenced surface peat properties could have been useful in terms of interpreting plant
community responses.
Continuous measurements of water table position at each plot across sites would
have provided useful data for this thesis. I was only able to quantify water table position
in each plot at my sites several times in 2009 and 2010. I used water table position
information collected at the end of the growing season (September, 2010) across plots
and sites as an environmental vector in the joint-plots. Water table fluctuations (i.e.
seasonal variation and variation in response to precipitation events) can be more
important in influencing plant species composition than the absolute water table position
(Laitinen, et al., 2008; Talbot, et al., 2009). In general, drainage is expected to alter peat
physical properties (i.e. bulk density and hydraulic conductivity with subsidence), which
can lead to more extreme water table fluctuations in response to precipitation events
(Whittington & Price, 2006).
86
In this thesis, I focused on environmental variables that I expected to be directly
influenced by drainage. I measured water table position to characterize changes in plot
level hydrology due to drainage.
Surface soil temperature was measured because
changing tree canopy characteristics in response to drainage are predicted to influence the
amount of energy that reaches the soil surface. Deeper soil temperatures might have been
altered because of changing peat properties, such as bulk density, with drainage. I also
predicted that tree biomass would increase with drainage and thus measured percent
canopy closure for each understory species composition quadrat. However, other factors
important in structuring plant communities, such as biological mechanisms like
competition or abiotic variables like pH, were not quantified. Ultimately, my goal was
not to perform a comprehensive examination of controls on peatland vegetation
communities (c.f. Vitt, 1990, Vitt & Chee, 1990), but rather to assess how changing
environmental conditions as a result of drainage impacted vegetation composition. In
this thesis, canopy closure and water table position were strong predictors of community
composition, although temperature was not. Unlike uplands, boreal peatland vascular
communities assemble along nutrient availability gradients, while bryophytes are
constrained by pH (Vitt & Chee, 1990). Drainage has been shown to increase the pH of a
system (Minkkinen, et al., 1999) and alter plant available nutrients (Laiho, et al., 1999).
Considering that the response of understory composition and productivity in peatlands to
drainage may depend on nutrient pools tied to woody biomass, it is possible that
information on pH and nutrient concentrations would have been more strongly related to
changes in community composition than water table and soil temperature.
I selected species composition quadrate location within each site randomly and
did not stratify my sampling by microform. This allowed me to attain a representative
illustration of community composition, biomass, and productivity at the plot scale, but in
Chapter 2, I showed that microform was important in determining community responses
to drainage in some sites. For example, hollow communities responded more strongly to
drainage than hummocks, consequently, increases in vascular cover occurred in hollows
but not hummocks.
However, I did not examine whether changes in biomass and
87
productivity with drainage varied between microforms. Murphy et al. (2009b) found that
hummocks experienced larger increases in aboveground biomass than lawns in a drained
bog in Ontario. This was due mostly to changes in ericoid shrub biomass. Across my
sites, I would predict that biomass would vary among hummocks and hollows in both
bogs and fens, as there were more increases in vascular cover on hollows than hummocks.
Understanding the response of plant productivity at the microform scale might be
important for parameterizing ecosystem models that incorporate information on
microform plant composition.
Total aboveground biomass did not change with drainage at most sites. Although,
I found some differences in ANPP with drainage in fens, I did not quantify ANPP in bogs.
Despite no change in aboveground biomass with drainage in a bog, Murphy et al. (2009a)
observed a change in resource allocation in shrubs, where plants allocated more biomass
to the stem than leaves with drainage. Increases in lignin-rich woody biomass could alter
soil litter quality and perhaps peat accumulation rates. Exploration into aboveground
resource allocation may also yield important information for predicting fire behavior.
For example, if shrub stem biomass increases but leaf biomass does not change with
drainage, this could lead to an increase in ladder fuels for fires. Additionally, I only
investigated changes in aboveground biomass and productivity in response to drainage.
However, Murphy et al. (2009a) found that drainage caused increases in belowground
productivity.
If bogs are assumed to be more nutrient limited than fens, then bog
vegetation may be investing more energy into roots to meet their nutritional requirements
(Chapin, et al., 1987). Thus, it is possible that a better understanding of root biomass and
belowground NPP rates across sites may have led to different conclusions about the
relative effect of drainage on plant biomass and productivity in bogs versus fens.
Although this study provides information on peatland drainage that is useful for
understanding human land-use impacts on peatlands (such as the effects of road
construction or drainage for forestry), I also was interested in using these results to better
understand how future drying associated with climate change might influence peatlands.
Initial modelling suggests that future drying of western Canadian peatlands likely will
88
result in water table drawdown exceeding a meter (Waddington, pers. comm.), within the
magnitude of water table changes observed in this study.
However, there are
dissimilarities between climate related drying and drainage. Drainage is an event that
occurs at a discrete event in time, or a pulse disturbance. It physically drains water away
from the site and dry conditions are maintained if the impetus for drainage (i.e. ditches or
roads) remains in place. The projected drying related to climate change will occur
though warming as well as elevated evapotranspiration and will likely be a press
disturbance, or a gradual pressure on the ecosystem. Drought also can lead to peatland
drying through decreased precipitation. Both drought and warming will cause more
gradual drying of peat, while drainage may push the ecosystem into another equilibrium
state by imposing a sudden stress on the ecosystem. However, compared to short-term
drainage experiments, my results reflect ecosystem responses to drainage over several
decades, presumably after biological communities have had ample time to acclimate to
new environmental conditions. This work is one of the first studies to examine peatland
vegetation succession in response to drying in boreal North America.
89
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