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Transcript
Letter
Extending Rapid
Ecosystem Function
Assessments to
Marine Ecosystems:
A Reply to Meyer
Jonathan S. Lefcheck,1,*
Simon J. Brandl,2
Pamela L. Reynolds,1,3
Ashley R. Smyth,1 and
Sebastian T. Meyer4
Meyer et al. [1] propose a series of assays
constituting their rapid ecosystem function assessment (REFA) to quickly and
inexpensively survey terrestrial ecosystem
processes. In this reply we extend their
framework to estuarine and coastal
marine ecosystems, which provide invaluable services to humanity. We propose an
analogous suite of assays that are equally
simple and easily deployed by a variety of
end users, including scientists, managers,
and citizens. We aim to facilitate crosssystem comparisons, test ecological theory, engage society, and provide rigorous
quantitative data on the consequences of
global change and biodiversity loss for the
world's oceans.
Meyer et al. [1] cite the current biodiversity
crisis as the motivation for their framework. While terrestrial extinctions have
been historically severe, the world's
oceans face similarly dire threats to biodiversity through overexploitation, climate
change, habitat loss and fragmentation,
nutrient pollution, and species invasions.
Based on current trajectories, marine
communities appear to be at the tipping
point first experienced by terrestrial communities right before the Industrial Revolution [2]. All available evidence indicates
that loss of marine biodiversity would
decrease ecosystem functioning [3],
although this inference has come from
experiments that are generally cumbersome to execute, occur in a single place
or time, and often fail to adequately reproduce natural conditions. Clearly, there is a
need for standardized and rigorous
assessments of functioning that can be
conducted at the same pace and scale
as the rapid changes currently facing
marine ecosystems.
Here we extend the REFA framework to
marine systems (Figure 1 and Table S1 in
the supplemental information online). This
standardized toolbox allows the quantification of key ecosystem functions across
a variety of natural ecosystems, including
biogenic reefs (corals, oysters), seagrasses, marshes, rocky reefs (including
kelps), mangroves, soft bottoms, and artificial habitats. As in Meyer et al. [1], we
focus on primary producers and inorganic
resources, consumers, and decomposers
(Figure 1). Within these compartments, we
provide assays to assess variables linked
to marine ecosystem functioning [3]. We
also suggest additional methods to examine two processes that are critical for
marine systems: nutrient cycling and
recruitment.
Unlike Meyer et al. [1], whose measure of
soil fertility is meant to serve as a proxy for
resource availability to fuel primary production, the ability of coastal systems to
regulate, remove, and otherwise buffer
coastal waters against nutrient pollution
is a key service, particularly in light of
coastal eutrophication and low-oxygen
‘dead zones’. Elemental cycling and biogeochemical activity can be quantified
using specialized sensor probes (e.g.,
O2), spectrophotometry for dissolved
nutrient concentrations, combustion of
sediment plugs to obtain organic matter
content [4], or even incubations of sediment cores to quantify nutrient fluxes and
sediment oxygen demand [5].
While seed dispersal is an essential driver
of terrestrial plant community structure
and function, marine propagules can disperse over distances 10–100 those of
terrestrial organisms [6]. As such, recruitment is one of the primary determinants of
local dynamics in marine systems. The use
of settling plates or tiles is the predominant
tool for investigating and manipulating
local marine communities [7]. While blank
tiles provide a standardized substrate,
heterogeneity can be manipulated by
combining plates in prearranged designs
or by gluing additional structural elements
to the plates [7]. Recruitment, however, is
not limited to sessile organisms, and other
methods, such as light traps [8] and frayed
ropes [9], have been used to successfully
attract and manipulate mobile animal
communities.
We also draw attention to the possibility to
convert abundances obtained from many
of these survey methods into rigorous
estimates of biomass or even productivity
using classic length–weight regressions
or, for smaller (<2 cm) invertebrates,
empirically derived equations based on
size class [10]. Such estimates will bring
the data collected using these simple
assays even closer to a process-based
view of marine ecosystems without the
need for complicated and time-intensive
post-processing.
While the environmental conditions and
target organisms often differ greatly among
systems, some of the proposed assays
have already shown tremendous flexibility
in assessing ecosystem functioning across
taxa and habitats [11]. We do not claim to
provide an exhaustive list and expect that
continued development will yield greater
applicability and extend these assays into
freshwater systems as well. Such flexible
applications allow the testing of basic ecological theories (e.g., the role of predation
along stress gradients [11]), the success of
management and restoration, and the prioritization of areas or times for these efforts.
Because these proposed tools are analogs
of those in Meyer et al. [1], they may also
promote the formal comparison of functioning and drivers within and across terrestrial and aquatic ecosystems in the
future. These assays also complement
and extend methods for monitoring Essential Biodiversity Variables proposed by the
Trends in Ecology & Evolution, April 2016, Vol. 31, No. 4
251
Tethering assays
Exclusion cages
Herbivory
Granivory
Net or trap samples
Sucon samples
Anaesthesia staons
Observaon/video
Seed boards
Selement plates
Recruitment
ProducƟon
rs
Co
nsu
Arficial habitat units
Light traps
Selement plates
Recruitment
Seagrasses
Mangroves
Ring counts
Hole punch
Chlorophyll
Harvest
Aboveground
producƟon
Biogenic
reefs
me
PredaƟon
s
cer
du
pro
ry
ma
Pri
Tethering assays
Exclusion
SoŌ-boƩom
Salt marshes
Corers
Belowground
producƟon
Hard-boƩom
Decomposers
Recruitment
Elemental
cycling
DecomposiƟon
Selement
plates
Sensor probes
Dissolved elemental
concentraon
Sediment organic maer
Incubaons
Tea-bags
Figure 1. Rapid Ecosystem Function Assessment (REFA) Framework for Marine Systems. Moving outward from the three organismal axes are the ecosystem
functions of interest, followed by the specific methods used to quantify them. For further information and references for the proposed methods, refer to the supplemental
material online.
Group on Earth Observations Biodiversity Supplemental Information
Observation Network (GEO BON) [12]. We Supplemental information associated with this article
hope that the simplicity of these tools will can be found online at http://dx.doi.org/10.1016/j.
engender their adoption by scientists, citi- tree.2016.02.002.
zens, and students, who have an equal 1Virginia Institute of Marine Science, The College of
William & Mary, Gloucester Point, VA 23062, USA
stake in a changing world.
252
Trends in Ecology & Evolution, April 2016, Vol. 31, No. 4
2
Tennenbaum Marine Observatories Network, Smithsonian
Environmental Research Center, Edgewater, MD 21037, USA
3
University of California, Davis, Davis, CA 95616, USA
4
Terrestrial Ecology Research Group, Department of
Ecology and Ecosystem Management, Center for Food
and Life Sciences Weihenstephan, Technische Universität
München, Hans-Carl-von-Carlowitz-Platz 2, 85354
Freising, Germany
*Correspondence: [email protected] (J.S. Lefcheck).
http://dx.doi.org/10.1016/j.tree.2016.02.002
References
1. Meyer, S.T. et al. (2015) Towards a standardized Rapid
Ecosystem Function Assessment (REFA). Trends Ecol.
Evol. 30, 390–397
2. McCauley, D.J. et al. (2015) Marine defaunation: animal loss
in the global ocean. Science 347, 1255641
3. Gamfeldt, L. et al. (2015) Marine biodiversity and ecosystem
functioning: what's known and what's next. Oikos 124,
252–265
4. Byers, S.C. et al. (1978) A comparison of methods of
determining organic carbon in marine sediments, with
suggestions for a standard method. Hydrobiologia 58,
43–47
5. Miller-Way, T. et al. (1994) Sediment oxygen-consumption
and benthic nutrient fluxes on the Louisiana continental
shelf: a methodological comparison. Estuaries 17, 809–815
6. Kinlan, B.P. and Gaines, S.D. (2003) Propagule dispersal in
marine and terrestrial environments: a community perspective. Ecology 84, 2007–2020
7. Freestone, A.L. and Osman, R.W. (2011) Latitudinal variation in local interactions and regional enrichment shape
patterns of marine community diversity. Ecology 92,
208–217
8. Doherty, J.M. and Zedler, J.B. (2014) Dominant graminoids
support restoration of productivity but not diversity in urban
wetlands. Ecol. Eng. 65, 101–111
9. Edgar, G.J. (1991) Artificial algae as habitats for mobile
epifauna: factors affecting colonization in a Japanese Sargassum bed. Hydrobiologia 226, 111–118
10. Edgar, G.J. (1990) The use of the size structure of benthic
macrofaunal communities to estimate faunal biomass
and secondary production. J. Exp. Mar. Biol. Ecol. 137,
195–214
11. Duffy, J.E. et al. (2015) Squidpops: a simple tool to crowdsource a global map of marine predation intensity. PLoS
ONE 10, e0142994
12. Pereira, H.M. et al. (2013) Essential biodiversity variables.
Science 339, 277–278
Forum
Seminal Fluid
and Mate Choice:
New Predictions
preferences that maximise both
sperm-borne and seminal fluidborne benefits – could therefore
apply much more broadly.
New Insights into the Multiple
Functions of Seminal Fluid
In resource-based mating systems,
female mate choice and polyandry have
been assumed to evolve so as to allow
females to take advantage of direct benefits or paternal investment provided by
males. In some insects and other animals,
limiting resources are transferred as
‘nuptial gifts’ of nutrients, defensive compounds, or water via the seminal fluid, with
ejaculates sometimes comprising a substantial proportion of male body mass [1].
However, males of most species provide
no obvious resources to females or offspring, with males’ contribution to reproduction consisting of relatively tiny
ejaculates that are usually assumed to
be too small to contain substantial quantities of limiting resources (e.g., [2,3]). In
such ‘nonresource-based’ mating systems, polyandry and female mate choice
have typically been assumed to evolve via
fertilisation benefits or genetic benefits to
offspring, such as good or compatible
genes, although the evidence remains
equivocal.
Yet, even in species with small ejaculates,
recent evidence shows that seminal fluid
contains chemicals that can affect not
only females themselves but also mediate nongenetic effects on offspring, and
such effects can occur independently of
Angela J. Crean,1
fertilisation.
In light of this evidence, we
Margo I. Adler,1 and
argue that theory on the evolution of
Russell Bonduriansky1,*
female mate choice in resource-based
mating systems could apply much more
Recent evidence shows that semi- broadly, yielding new predictions for sysnal fluid can affect females and off- tems typically regarded as nonresourcespring independently of fertilisation based.
in species lacking conventional
‘nuptial gifts’. We argue that a
hypothesis from paternal investment systems – that selection can
favour
changing
female
enzymes, and hormones, and can contain
pheromones, viruses, and bacteria [4].
The composition of seminal fluid is influenced by natural selection for sperm survival, as seminal fluid nourishes and
protects sperm from oxidative damage
and immune attacks in the female reproductive tract. In polyandrous systems,
seminal fluid is also subject to sexual
selection via its role in sperm competition,
and may therefore be a sexually antagonistic trait [4]. Yet, despite the potential
harmfulness of seminal fluid, females
may benefit from some seminal fluid components. Seminal fluid can enhance
female reproductive success through
positive direct effects on fertilisation rate
and female fecundity [5]. Moreover, rodent
studies involving embryo transfer without
exposure to seminal fluid, or mating to
seminal–vesicle-deficient males, show
that seminal fluid contains substances that
are important for normal offspring survival,
growth, and development [5]. Even in
humans, acute exposure to semen at
the beginning of a pregnancy, as well as
cumulative exposure over time, has been
shown to protect against recurrent miscarriage and pre-eclampsia, and significantly improve success rates of artificial
reproductive technologies such as in vitro
fertilisation (IVF) [5,6]. Given that seminal
fluid appears to be costly to produce and
variable among males (Box 1), this evidence suggests that seminal fluid composition can affect female fitness directly and
via seminal fluid-mediated paternal effects
on offspring.
In addition, recent evidence from insect
studies shows that seminal fluid can influence traits of offspring sired by other
males that mate subsequently with the
same female (‘non-sire effects’). In Drosophila melanogaster, exposure to nonsire ejaculates from different genetic
backgrounds enhanced the fecundity of
daughters [7]. In neriid flies, Telostylinus
Effects of Seminal Fluid in
angusticollis, the environmentally induced
Nonresource-Based Systems
condition of a female's first mating partner
Seminal fluid contains numerous proteins influenced the body size of offspring sired
and peptides, RNA, salts, sugars, 2 weeks later by another male [8]. These
Trends in Ecology & Evolution, April 2016, Vol. 31, No. 4
253
1
2
Figure S1
3
4
Table S1: Methods for rapid ecosystem function assessment in marine systems (see also
Figure S1).
Ecosystem
function
Target variable
Primary producers
Sessile organismal
recruitment (rate)
Field method
Settlement
plates
Recruitment
Macroalgal density
Ring counts
Microalgal
abundance
Chlorophyll
concentration
Macroalgal growth
Hole-punch
Macroalgal/macrop
hyte biomass
Direct harvest
Root biomass
Corers
Organic material
break-down
Tea bag assay
Elemental
concentrations
Sensor probes
Abovegroun
d biomass
production
Belowgroun
d biomass
production
Description
Timeeffort
Lab
Ref
Individuals
adhering to
plate
counted/biomas
s weighed after
standardized
duration
Shoot density
counted within
standardized
area
Algae collected
and pigments
extracted,
absorbences
converted to
biomass
estimates
Growth
calculated from
elongation of
fixed points
Material
directed
harvested, dried
and weighed
Core inserted
and
belowground
material sorted
and weighed
Y
L-H,
dependi
ng on
organis
ms
[13,1
4]
N
L
[15,1
6]
Y
M
[16,1
7]
N
M
[16]
Y
L/H
[18]
Y
L-H,
dependi
ng on
habitat
[18]
Mass loss in
standardized
mesh bag
Sondes
deployed to
measure
elemental
concentrations
(e.g., O2, pH)
N
M
[19]
N
L
[20]
Decomposers
Decompositi
on
Elemental
cycling
Concentrations of
chemical
compounds
Spectrophotome
try
Sediment organic
matter
Sediment plugs
Chemical fluxes
Incubations
Fouling organismal
recruitment (rates)
Settlement
plates
Sessile/fouling/mob
ile organismal
recruitment
Artificial habitat
units
Photophilic mobile
organism activity
Light traps
Sessile/fouling
organismal
recruitment (rates)
Settlement
plates
Prey removal
Tethers
Prey reduction
Exclusion
Recruitment
Water samples
subjected to
spectrophotome
try to convert
absorbances to
dissolved
chemical
concentrations
Identify
sediment
carbon through
combustion
Fluxes
measured from
sediment cores
kept in
controlled
chambers
Organisms
adhering to
plate
counted/biomas
s weighed
Y
M/H
[21]
Y
L
[22]
Y
H
[23]
Y
L-H,
dependi
ng on
organis
ms
[13,1
4]
Individuals
colonizing bare
substrate
counted/biomas
s weighed after
standardized
duration
Individuals
migrate to
lighted traps
and captured
Individuals
adhering to
plate
counted/biomas
s weighed after
standardized
duration
Prey tethered
and loss
recorded after
standardized
duration
Predators
excluded via
direct removal
Y
L-H,
dependi
ng on
organis
ms
[24]
N
M
[25]
Y
L-H,
dependi
ng on
organis
ms
[13,1
4]
N
M
[11,2
6]
N
H
[27,2
8]
Consumers
Recruitment
Predation
Biomass
production
Herbivory
Granivory
Mobile organism
abundance
Net / trap
samples
(Small) mobile
organismal
abundance
Suction samples
Mobile organismal
abundance
Anesthetism
Sessile/mobile
organismal
abundance
Observation /
video
Herbivory rates
Tethers
Plant biomass
reduction
Exclusion
Seed removal
Seed boards
or through
physical cages
Individuals
trapped using
nets or baited
traps
N/Y
*
M/H,
dependi
ng on
gear
deploye
d
M
[29]
N/Y
*
M
[31,3
2]
Y
[33]
Individuals
collected using
vacuum
machine
Individuals
stunned using
anesthetic (e.g.,
clove oil,
rotenone)
Individuals
abundance/leng
th recorded via
visual census or
video recording
Y
[30]
Plant material
tethered and
loss recorded
after
standardized
duration
Herbivores
excluded
through
physical cages
or chemical
deterrent (e.g.,
copper paint,
carbaryl)
Seeds pinned to
board and loss
recorded after
standardized
duration
N
M/H,
dependi
ng on
duration
and
water
clarity
M
N
H
[3437]
N
M
[38]
[34]
5
Notes: Lab refers to whether this is an additional post-processing or analysis that must occur in the
6
laboratory. This does not include preparation, construction, calibration, or any other work to take place
7
before sampling. Time-effort refers to the amount of time and effort needed to conduct and extract data from
8
the sample, from deployment to laboratory post-processing (not including time left alone for the process
9
under investigation to occur). L = low (≤ 15 min), M = medium (≤ 1 h), H = high (>1 hour).
10
*Depending on whether specimens are retained
11
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