Download Supplementary Material - Proceedings of the Royal Society B

ESM_Changes in range limits under climate change
Page 1 of 15
Supplementary Material
Study systems
We investigated how climate change and population dynamics together affect the range
limits of two lagomorphs of conservation concern: the Mexican Volcano Rabbit
5
(Romerolagus diazi) and the European Mountain Hare (Lepus timidus). Romerolagus
diazi is protected by national and international legislation: listed as an endangered species
in the Mexican law (DOF 2001) and in the IUCN Red List (LSG 1996). Lepus timidus is
listed under Annex V of the EC Habitats Directive (1992), which implies that a number
of methods of capture are restricted or banned (JNCC 2007).
10
The current distribution of Romerolagus diazi is at its range limit (see Fig. S1
supplementary material), due to historical non-climatic drivers of range contraction.
Although the species has always been endemic to a small region of the Transvolcanic
Belt in central Mexico, between 2,800 and 4,250 meters above sea level (Romero &
15
Velázquez 1999; Velázquez et al. 1999) it was previously more widespread. A total
occupancy area of about 280 km2 has been estimated in a discontinuous distribution
pattern, from which four major core areas have been identified (Velázquez et al. 1996).
Population size at the end of the 1980’s was estimated at between 2,478 and 12,120
(Velázquez 1994). Besides its natural restricted distribution, several factors threaten the
20
long-term persistence of Romerolagus diazi. First, two of its core areas are located about
30 km south of Mexico City -one of the largest urban areas in the world- imposing a
strong pressure to the rabbit’s habitat, which has been quickly reducing in the last
decades due to urbanization and expansion of the grazing and cropland frontier, the
ESM_Changes in range limits under climate change
Page 2 of 15
increase of frequency of wildfires, illegal hunting, and introduction of domestic dogs and
25
cats that prey upon the rabbits are among the most important ones (Hoth et al. 1989;
Romero & Velázquez 1999). Second, more recent climatic changes have been detected in
the distributional area of Romerolagus diazi, in particular an increase in the winter
temperature of more than 1.5 °C in the last 40 years (Domínguez 2007). It is this
combination of pressures that makes this species highly vulnerable to extinction.
30
Fig. S1. Distribution of Romerolagus diazi (blue) superimposed over the 2010 climate
suitability.
Lepus timidus is an arctic/subartic species with a fragmented range across Europe,
35
extending across Russia in the east and to Scotland and Ireland in the west (MitchellJones et al. 1999; Thulin 2003). In Europe the northwest range limit of this species is in
ESM_Changes in range limits under climate change
Page 3 of 15
Scotland. It is highly fragmented and although Lepus timidus is capable of existing in a
wide range of habitats and environmental conditions, in Great Britain (England, Wales
and Scotland) it is generally associated with heather (Calluna and Erica spp., Newey et al.
40
2007). The current distribution of Lepus timidus populations show generally regular but
sometimes dramatic changes in density, depending on habitat suitability related to
vegetation and climate [see below] (Newey et al. 2007). The current distribution of Lepus
timidus within Britain, the geographical area of interest in the current paper, is estimated at
76 721 km2 (JNCC 2007).
45
Habitat suitability
Romerolagus diazi inhabits coniferous forests with a dense sub-alpine grassland cover in
the herbaceous stratum. It is highly sensitive to vegetation structure and composition,
thus perturbations to structural habitat has an important impact in its populations
50
(Cervantes et al. 1990; Cervantes & Martínez 1996). The habitat map for the Volcano
Rabbit was obtained from the last land use / land cover map generated for the whole
country in 2000 (IGUNAM-INEGI 2001). Original land cover classes were reclassified in
highly suitable (1), suitable (0.5), and unsuitable (0) for the Volcano Rabbit based on
Velázquez et al. (1999).
55
Habitat for Lepus timidus was based on the proportion of suitable habitat in the cell using
the 1990 Land Cover Map (Fuller et al. 1994) sub categories that are largely heather,
open shrub moor (10) and shrub heath (25). In the absence of more detailed information
on the relationship between hare density and vegetation cover, we here assumed that grid
ESM_Changes in range limits under climate change
60
Page 4 of 15
cells were potentially suitable habitat if the percentage cover of heather exceeded 70%.
After applying this vegetation mask (categorical threshold), the bioclimatic was thereafter
used to determine relative habitat suitability.
Occurrence data
Occurrence data for the Volcano Rabbit was obtained from four scientific collections
65
[Colección Nacional de Mamíferos, Instituto de Biología, UNAM (CNMA); Museum of
Natural History, University of Kansas (KU); Instituto Politécnico Nacional (IPN) and
Colección de Mamíferos of Universidad Autónoma Metropolitana (Unidad Iztapalapa)
(UAMI)], scientific literature (Velázquez et al. 1996), and from fieldwork carried out
from 2004-2007 {Domínguez, 2007 #1262}.
70
Presences for the Mountain Hare (Lepus timidus) were based on records held at the
Biological Records Centre (BRC) for Great Britain (www.nbn.org.uk/). Squares (10km
x 10km) within Great Britain with no record at or below 10km resolution were
considered an absence. For simplicity, all 1km squares within a 10km square were
75
considered a potential occupancy, provided the total habitat suitability threshold
(vegetation + climate – see below) was >0.2.
Historic distribution of Romerolagus diazi
Occurrence data for the Romerolagus diazi were obtained from four scientific collections
80
(see above). Historical distribution map was generated using species distribution
modelling techniques and GIS analysis. A potential distribution map of the species was
created using a maximum entropy approach implemented in the MaxEnt software
ESM_Changes in range limits under climate change
Page 5 of 15
(Phillips et al. 2006). For the purpose of this study, we used all available occurrences of
the species and a suite of 19 bioclimatic variables produced specifically for Mexico with
85
the ANUSPLIN software (Hutchinson 1997) and kindly provided by O. Tellez-Valdes.
Automatic settings were used in Maxent for all tuning parameters following Phillips and
Dudik (2008) and we selected the new logistic output format to obtain a map that is
interpreted as an estimate of the probability of presence. The probabilistic map was
converted into a binary map (presence/absent) selecting as threshold the minimum
90
probability value in which all occurrences were predicted. Finally, those climatically
suitable areas which have never been inhabited by the species due to dispersal limitation
or historical reasons were trimmed based on distributional range limits described in
Cervantes et al. (1990) and Velázquez et al. (1996).
Climate suitability methods
95
Generalized Additive Models (GAMs) with binomial errors, a logit link and a smoothed
function (3 nodes) were used to build the bioclimatic models (mgcv (1.4-1) library in R,
Wood 2008). GAMs are semi-parametric models with data-driven response curves
(Hastie 1992). We took an ensemble modelling approach using a multi-model inference
framework (Burnham & Anderson 2002; Araujo & New 2007; Thuiller et al. 2007) based
100
on all-subsets selection of the GAMs using the AIC measure. The ten ‘best’ models
(lowest AIC) were conserved and the final projections were a weighted average of these.
Romerolagus diazi
The Mexican volcano rabbit model was built and projected on a 0.01° x 0.01° (~1km2)
grid. This is a very range-restricted species and the number of presences was small
105
compared to the number of absences. Rather than using all the absences in the
ESM_Changes in range limits under climate change
Page 6 of 15
surrounding area (>180 000 points) we chose a random set of absences. Bioclimate
modelling was the same as for the mountain hare except that due to the smaller number of
presences only three bioclimatic variables were used to build the models; Annual Mean
Temperature, Temperature Seasonality (standard deviation *100), Annual Precipitation.
110
These three variables were highly correlated (r >0.6) with a larger set of variables
including those used in the mountain hare modelling. All 7 possible models (i.e., one
model for each unique combination of the three bioclimate variables) were used and were
weighted as in the mountain hare modelling (see below).
Lepus timidus
115
The mountain hare (Lepus timidus) bioclimatic model was built on the ~50 x 50km Atlas
Flora Europea (AFE) grid, using presence absence distribution data from the European
Mammals Atlas (Mitchell-Jones et al. 1999) as the response variable. We used four
bioclimatic variables that have been previously been shown to correspond well to species
range limits: mean temperature of the warmest month and coldest month, annual
120
precipitation, and the ratio of actual to potential evapotranspiration (Thuiller et al. 2005;
Levinsky I. et al. 2007). Climate data used to build the model was based on the 10’
European grid for the last recognized climate normal period (1961-1990) generated by
the FP5 ATEAM project (New et al. 2002; Schroter et al. 2005). These data were
aggregated to 50 x 50 km Universal Transverse Mercator (UTM) in ArcGIS/ArcInfo 9.2
125
(ESRI, Redlands, California, USA) to match the species data grid. The model was then
projected onto the 10 x 10km British National Grid (BNG) using climate data for the
same variables for both the recent past and future (1961-2100).
ESM_Changes in range limits under climate change
Page 7 of 15
Future projections
Future projections for the climate variables were derived using climate model outputs
130
from the HadCM3 global climate model made available through the Intergovernmental
Panel on Climate Change (IPCC) Data Distribution Centre (ipcc-ddc.cru.uea.ac.uk).
Modelled climate anomalies were scaled based on the A2 storyline (Special Report on
Emissions Scenarios: http://www.grida.no/climate/ipcc/emission/); this scenario describes
a heterogeneous future world focused on self-reliance, preservation of local identities and
135
slower and more regional economic development (Nakicenovic & Swart 2000). This
scenario is more conservative than the A1FI scenario, which we are currently tracking
well above (Rahmstorf et al. 2007), but A2 better reflects emissions scenarios now
gaining favour among mitigation policy researchers, encompassing a later shortage of
fossil fuels and more active mitigation policies which come into force by mid century
140
(www.ipcc.ch). Given the likelihood of currently unmodelled slow feedbacks in the
climate system (Hansen et al. 2007), it is plausible that future climate change will be
more extreme than that used here, so we consider our simulations to be a mid-range
projection.
145
Future projections for Romerolagus diazi were calculated as an averaged projection
surface for each of three future 30year means provided by the IPCC (2010-2039, 20402069, and 2070-2099). For interpolation purposes these were labelled for the first year
and the interpolation extended 30 years to 2100. For the dynamic climate maps these
values were then interpolated to annual time slices using (“gi_beta_r44.exe” Ersts & R.
ESM_Changes in range limits under climate change
150
Page 8 of 15
2008). Grid interpolator applies a linear interpolation between two grids on a cell by cell
basis.
InterpolationIncrementi,j = EndYeari,j - StartYeari,j / ( EndYeari,j - StartYeari,j )
For each year between the StartYear and EndYear
CurrentYeari,j = StartYeari,j + ( InterpolationIncrementi,j * ( CurrentYear - StartYear ).
155
Future climate envelope projections for Lepus timidus were produced in the same way
(using 30-year means 1991-2020, 2021-50, 2051-80). These were then converted to a
1 x 1 km grid to match the habitat and occurrence layer for Great Britain, but with all
squares within the HadCM3-modelled 10 km having the same climate value. The annual
160
interpolation was extended by 49 years to 2100.
Stochastic Population Models
Romerolagus diazi and Lepus timidus population models comprised 3 stage classes leveret; one year old; and those two years or greater. Demographic rates (survival, age of
165
maturity and fecundity rates) were based directly on published estimates or taken from
similar species (Flux & Angerman 1990; Hewson & Hinge 1990; Marboutin et al. 2003;
Newey et al. 2004; Dahl 2005; Jennings et al. 2006; Mahony & Montgomery 2006).
Leveret survival was estimated at 30-50% and adult survival at 45-70%. Age of maturity
was modelled at 1 year (Iason 1989) and fecundity was related to age, with an average
170
litter size of 5 for 2-year olds and 6 for 3-year olds. We estimated variability in vital rates
by trialling values until the fluctuations in the simulated populations matched those of the
time series.
ESM_Changes in range limits under climate change
Page 9 of 15
Density Dependence
Density dependence (DD) was implemented using a Scramble model (Logistic or Ricker
175
type of DD), which determined the population growth rate at each time step (by
modifying fecundity and leveret survival) as a function of the population size at that time
step. Maximum rate of population growth (Rmax) was calculated by fitting exponential
and logistic models to time series of abundances from the Global Population Dynamics
Database (http://www3.imperial.ac.uk/cpb/research/patternsandprocesses/gpdd). AIC
180
model averaging was used to provide a weighted estimate of maximum/intrinsic
population growth rate for 17 population time series. This procedure resulted in an Rmax
estimate of 1.34 which was used for both R. diaza and L. timidus.
Dispersal
The rate of dispersal between patches of suitable habitat during each time step was
185
modelled with an exponential function, P = exp(Db), where D is the distance between
patch centroids and b is a constant. When D exceeds a specified maximum distance
(Dmax; set arbitrarily at a high value of 20 km), P is set to zero. The best estimate of b
was set at 2 based on observed mean and maximum dispersal distances (Hewson & Hinge
1990; Dahl & Willebrand 2005) and a sensitivity analysis examined alternative values of
190
1 (less dispersal) and 3 (greater).
Stochasticity
Demographic stochasticity was implemented by sampling the number of survivors from
binomial distributions, and the number of young produced from a Poisson distribution
(Akçakaya & Root 2005). Environmental stochasticity was sampled from lognormal
195
distributions. Environmental variability was correlated between populations depending on
ESM_Changes in range limits under climate change
Page 10 of 15
their spatial separation. Pairwise correlations were calculated using an exponential
function, P = exp(Db), where D is the distance between centroids of habitat patches and b
is a constant. This function was parameterised b=300, which was based on correlationdistance relationship in annual mean temperature variation among 20 weather stations in
200
the UK. Annual environmental variability for vital rates was estimated based on
variability of population sizes from time series data.
ESM_Changes in range limits under climate change
Romerolagus diazi patches
Historic
2010
2050
2080
Page 11 of 15
ESM_Changes in range limits under climate change
205
Page 12 of 15
Fig. S2. Volcano rabbit habitat changes, showing size and location of habitat patches
predicted by climatic and land-use variables, with climate changing in time according to
the A2 SRES scenario. For years 2010 through 2080, the colour of grid cells indicates
habitat suitability (brighter colour more suitable), and the white outlines delineate patches
or discrete populations of the metapopulation. From 2010 to 2050, two smaller
210
(northern) patches disappear, one large (western) patch splits into three smaller patches,
and two medium-sized (eastern) patches become slightly smaller. From 2050 to 2080,
two of the three western patches disappear, and the two eastern patches become
substantially smaller.
ESM_Changes in range limits under climate change
215
Page 13 of 15
References
Araujo, M. B. & New, M. 2007 Ensemble forecasting of species distributions. Trends
in Ecology & Evolution 22, 42-47.
220
Burnham, H. P. & Anderson, D. R. 2002 Model selection and multimodel inference –
A practical information-theoretic approach. Fort Collins: Springer.
Cervantes, F. A., Lorenzo, C. & Hoffmann, R. S. 1990 Romerolagus diazi.
Mammalian Species 360, 1-7.
225
Cervantes, F. A. & Martínez, J. 1996 Historia natural del conejo zacatuche o
teporingo (Romerolagus diazi). In Ecología y conservación del conejo
zacatuche y su hábitat (ed. A. Velázquez, F. J. Romero & J. López), pp. 29 –
40: UNAM y Fondo de Cultura Económica. 204 pp.
Dahl, F. 2005 Life and Death of The Mountain Hare in the Boreal Forest of Sweeden:
Sweedish University of Agricultural Sciences.
230
Dahl, F. & Willebrand, T. 2005 Natal dispersal, adult home ranges and site fidelity
of mountain hares Lepus timidus in the boreal forest of Sweden. Wildlife
Biology 11, 309-317.
Domínguez, A. 2007 Efecto del cambio climático en la distribución geográfica del
teporingo (Romerolagus diazi). In Facultad de Ciencias, vol. Bachelor
Science. México: Universidad Nacional Autónoma de México.
235
240
Ersts, P. J. & R., P. 2008 Grid Interpolator (version beta_r44): American Museum
of Natural History, Center for Biodiversity and Conservation. Available from
http://biodiversityinformatics.amnh.org/.).
Flux, J. E. C. & Angerman, R. 1990 The hares and jackrabbits. In Rabbits, Hares
and Pikas: Status Survey and Conservation Action (ed. J. A. Chapman & E. C.
Flux): International Union for the Conservation of Nature.
Fuller, R. M., Groom, G. B. & Jones, A. R. 1994 The Land Cover Map of Great
Britain: an automated classification of Landsat Thermatic Mapper data. .
Photogrammetric Engineering & Remote Sensing 60, 553-562
245
Hansen, J., Sato, M., Kharecha, P., Russell, G., Lea, D. W. & Siddall, M. 2007
Climate change and trace gases. Philosophical Transactions of the Royal
Society A 365, 1925-1954.
Hastie, T. J. 1992 Generalized Additive Models. In Statistical Models in S (ed. J. M.
Chambers & T. J. Hastie). Boca Raton: Chapman & Hall.
ESM_Changes in range limits under climate change
250
Page 14 of 15
Hewson, R. & Hinge, M. D. C. 1990 Characteristics of the home range of mountain
hares Lepus timidus. Journal of Applied Ecology 27, 651-666.
Hoth, J., Velazquez, A., Romero, F. J., Leon, L., Aranda, M. & Bell, D. J. 1989 The
volcano rabbit, a shrinking distribution and a threatened habitat. Oryx 21,
85-91.
255
Hutchinson, M. F. 1997 ANUSPLIN Version 4.1. User guide. Canberra.: Centre for
Resource and Environmental Studies, Australian National University,
Australian Capital Territory,.
Iason, G. R. 1989 Growth and mortality in mountain hares - the effect of sex and
date of birth. Oecologia 81, 540-546.
260
265
Jennings, N., Smith, R. K., Hacklander, K., Harris, S. & White, P. C. L. 2006
Variation in demography, condition and dietary quality of hares Lepus
europaeus from high-density and low-density populations. Wildlife Biology
12, 179-189.
JNCC. 2007 Joint Nature Conservation Committee. Second Report by the UK under
Article 17 on the implementation of the Habitats. Directive from January
2001 to December 2006. Peterborough: JNCC. Available from:
www.jncc.gov.uk/article17.
Levinsky I., Skov F., Svenning J.C. & C., R. 2007 Potential impacts of climate
change on the distribution and diversity patterns of European mammals.
Biodiversity and Conservation 16, 3803-3816.
270
275
Mahony, D. O. & Montgomery, W. I. 2006 The distribution, abundance and habitat
use of the Irish Hare (Lepus timidus hibernicus) in upland and lowland areas
of Co. Antrim and Co. Down. Belfast: Environment and Heritage Service
Research and Development Series.
Marboutin, E., Bray, Y., Peroux, R., Mauvy, B. & Lartiges, A. 2003 Population
dynamics in European hare: breeding parameters and sustainable harvest
rates. Journal of Applied Ecology 40, 580-591.
Mitchell-Jones, A. J., G.,, Amori, G., Bogdanowicz, W., Krystufek, B., Reijnders, P.
J. H., Spitzenberger, F., Stubbe, M., Thissen, J. M. B., Vohralik, V. & Zima,
J. 1999 Atlas of European Mammals. London: Academic Press.
280
Nakicenovic, N. & Swart, R. 2000 Emissions scenarios. A special report of Working
Group III of the Intergovernmental Panel on Climate Change. Cambridge.:
Cambridge University Press.
New, M., Lister, D., Hulme, M. & Makin, I. 2002 A high-resolution data set of
surface climate over global land areas. Climate Research 21, 1-25.
285
Newey, S., Dahl, F., Willebrand, T. & Thirgood, S. 2007 Unstable dynamics and
population limitation in mountain hares. Biological Reviews 82, 527-549.
Newey, S., Thirgood, S. J. & Hudson, P. J. 2004 Do parasite burdens in spring
influence condition and fecundity of female mountain hares Lepus timidus?
Wildlife Biology 10, 171-176.
ESM_Changes in range limits under climate change
290
Page 15 of 15
Phillips, S. J., Anderson, R. P. & Schapire, R. E. 2006 Maximum entropy modeling
of species geographic distributions. Ecological Modelling 190, 231-259.
Phillips, S. J. & Dudik, M. 2008 Modeling of species distributions with Maxent: new
extensions and a comprehensive evaluation. Ecography 31, 161-175.
295
300
305
310
Rahmstorf, S., Cazenave, A., Church, J. A., Hansen, J. E., Keeling, R. F., Parker, D.
E. & Somerville, R. C. J. 2007 Recent climate observations compared to
projections. Science 316, 709.
Romero, F. J. & Velázquez, a. 1999 La región de montaña al sur de la Cuenca de
México: una revisión de su importancia biológica. In Biodiversidad de la
región de montaña del sur de la Cuenca de México (ed. A. Velázquez & F. J.
Romero), pp. 40 – 51: UAM Xochimilco. México D. F., México. 351 pp.
Schroter, D., Cramer, W., Leemans, R., Prentice, I. C., Araujo, M. B., Arnell, N. W.,
Bondeau, A., Bugmann, H., Carter, T. R., Gracia, C. A., de la Vega-Leinert,
A. C., Erhard, M., Ewert, F., Glendining, M., House, J. I., Kankaanpaa, S.,
Klein, R. J. T., Lavorel, S., Lindner, M., Metzger, M. J., Meyer, J., Mitchell,
T. D., Reginster, I., Rounsevell, M., Sabate, S., Sitch, S., Smith, B., Smith, J.,
Smith, P., Sykes, M. T., Thonicke, K., Thuiller, W., Tuck, G., Zaehle, S. &
Zierl, B. 2005 Ecosystem service supply and vulnerability to global change in
Europe. Science 310, 1333-1337.
Thuiller, W., Richardson, D. M., Pysek, P., Midgley, G. F., Hughes, G. O. & Rouget,
M. 2005 Niche-based modelling as a tool for predicting the risk of alien plant
invasions at a global scale. Global Change Biology 11, 2234-2250.
Thuiller, W., Slingsby, J. A., Privett, S. D. J. & Cowling, R. M. 2007 Stochastic
species turnover and stable coexistence in a species-rich, fire-prone plant
community. PLoS ONE 2, e938.
315
Thulin, C. G. 2003 The distribution of mountain hares Lepus timidus in Europe: a
challenge from brown hares L. europaeus? Mammal Review 33, 29-42.
Velázquez, A. 1994 Distribution and population size of Romerolagus diazi on El
Pelado Volcano, Mexico. Journal of Mammalogy 75, 743-749.
320
325
330
Velázquez, A., Romero, F. J. & Bocco, G. 1999 Análisis y simulación de la
distribución de especies diagnósticas de la región de montaña del sur de la
Cuenca de México. In Biodiversidad de la región de montaña del sur de la
Cuenca de México (ed. A. Velázquez & F. J. Romero), pp. 162 – 187: UAM
Xochimilco. México D. F., México. 351 pp.
Velázquez, A., Romero, F. J. & López-Paniagua, J. 1996 Amplitud y utilización del
hábitat del conejo zacatuche. In Ecología y conservación del conejo zacatuche
y su hábitat (ed. A. Velázquez, F. J. Romero & J. López-Paniagua), pp. 89 –
104: UNAM y Fondo de Cultura Económica. 204 pp.
Wood, S. N. 2008 Fast stable direct fitting and smoothness selection for generalized
additive models. Journal of the Royal Statistical Society Series B-Statistical
Methodology 70, 495-518.