Cross-realm assessment of climate change impacts on species' abundance trends

Climate change, land-use change, pollution and exploitation are among the main drivers of species' population trends; however, their relative importance is much debated. We used a unique collection of over 1,000 local population time series in 22 communities across terrestrial, freshwater and marine realms within central Europe to compare the impacts of long-term temperature change and other environmental drivers from 1980 onwards. To disentangle different drivers, we related species' population trends to species- and driver-specific attributes, such as temperature and habitat preference or pollution tolerance. We found a consistent impact of temperature change on the local abundances of terrestrial species. Populations of warm-dwelling species increased more than those of cold-dwelling species. In contrast, impacts of temperature change on aquatic species' abundances were variable. Effects of temperature preference were more consistent in terrestrial communities than effects of habitat preference, suggesting that the impacts of temperature change have become widespread for recent changes in abundance within many terrestrial communities of central Europe.Additionally, we appreciate the open access marine data provided by the International Council for the Exploration of the Sea. We thank the following scientists for taxonomic or technical advice: C. Brendel, T. Caprano, R. Claus, K. Desender, A. Flakus, P. R. Flakus, S. Fritz, E.-M. Gerstner, J.-P. Maelfait, E.-L. Neuschulz, S. Pauls, C. Printzen, I. Schmitt and H. Turin, and I. Bartomeus for comments on a previous version of the manuscript. R.A. was supported by the EUproject LIMNOTIP funded under the seventh European Commission Framework Programme (FP7) ERA-Net Scheme (Biodiversa, 01LC1207A) and the long-term ecological research program at the Leibniz-Institute of Freshwater Ecology and Inland Fisheries (IGB). R.W.B. was supported by the Scottish Government Rural and Environment Science and Analytical Services Division (RESAS) through Theme 3 of their Strategic Research Programme. S.D. acknowledges support of the German Research Foundation DFG (grant DO 1880/1-1). S.S. acknowledges the support from the FP7 project EU BON (grant no. 308454). S.K., I.Kü. and O.S. acknowledge funding thorough the Helmholtz Association’s Programme Oriented Funding, Topic ‘Land use, biodiversity, and ecosystem services: Sustaining human livelihoods’. O.S. also acknowledges the support from FP7 via the Integrated Project STEP (grant no. 244090). D.E.B. was funded by a Landes–Offensive zur Entwicklung Wissenschaftlich–ökonomischer Exzellenz (LOEWE) excellence initiative of the Hessian Ministry for Science and the Arts and the German Research Foundation (DFG: Grant no. BO 1221/23-1).Peer Reviewe

Ideal free distribution of fixed dispersal phenotypes in a wing dimorphic beetle in heterogeneous landscapes

According to the ideal free distribution (IFD) theory, individuals that are able to perceive the quality of different patches in a landscape and disperse freely are expected to redistribute themselves proportionally to the carrying capacities of heterogeneous patches. Here, we argue that, when dispersal is unconditional and genetically fixed, a coalition of sedentary and dispersing phenotypes can attain an IFD under spatiotemporally uncorrelated variation in fitness. This not only leads to a stable polymorphism of both dispersal phenotypes, but also implies that the number of dispersing individuals should on average be equal among patches and determined by the carrying capacity of the smallest local populations in the landscape. Differences in carrying capacity among patches are thus only reflected by changes in the number of sedentary individuals. Individual-based simulations show that this mechanism can be generalized over a wide range of spatiotemporal conditions and dispersal strategies. Moreover, these expectations are in strong agreement with empirical data on the density of both dispersal phenotypes of the wing dimorphic ground beetle Pterostichus vernalis within and among 10 different landscapes. Hence, for the first time, these results demonstrate that this mechanism serves as a plausible alternative to the competition-colonization model to explain the spatial distribution of fixed dispersal phenotypes in heterogeneous landscapes. Understanding of the frequency distributions of individuals expressing discrete dispersal morphs moreover improves our predictive and management capabilities for a broad range of species, for which we currently typically rely on using mean dispersal rates

Appendix A. Expected distribution of fixed dispersal phenotypes under the competition–colonization model described in Roff (1994).

Expected distribution of fixed dispersal phenotypes under the competition–colonization model described in Roff (1994)

Supplement 2. R code to model the spatial distribution of fixed dispersal phenotypes under competition-colonization dynamics as described in Roff (1994), but allowing for spatial variation in K.

<h2>File List</h2><div> <a href="SupplementS2/Comp_colon.r">Comp_colon.r</a> (MD5: 4206e4a34a10e025546bedb379a2ed7b)</div><h2>Description</h2><div> <p>R code to model the spatial distribution of fixed dispersal phenotypes under competition-colonization dynamics as described in Roff (1994). In contrast to the original model where <i>K</i> is constant across all patches in the landscape, spatial variation in <i>K</i> can be implemented. The model was used to generate the results described in <a href="appendix-A.php">Appendix A</a>.</p> </div

Supplement 1. C++ source code to model the spatial distribution of fixed dispersal phenotypes as described in this paper and a short description of the program and its options.

<h2>File List</h2><div> <p><a href="SupplementS1/Animal.h">Animal.h</a> (MD5: 8153e300d878df797b47e57d23dd5a6c)</p> <p><a href="SupplementS1/Animal.cpp">Animal.cpp</a> (MD5: 683e8c2c50db41f24112a96e7685d0b6)</p> <p><a href="SupplementS1/Landscape.h">Landscape.h</a> (MD5: 0b0ad03fece5a776e37312d9ca3b6985)</p> <p><a href="SupplementS1/Landscape.cpp">Landscape.cpp</a> (MD5: 995aef09ab98afc52476516734372275)</p> <p><a href="SupplementS1/Main.cpp">Main.cpp</a> (MD5: 8eaff25cd44dda1f770d9a22435db513)</p> <p><a href="SupplementS1/mersenne.cpp">mersenne.cpp</a> (MD5: 3aca9a8a7886793781b3e157a32825cd)</p> <p><a href="SupplementS1/Parameters.h">Parameters.h</a> (MD5: f3b58e95205f9a80a768f2a15a53594a)</p> <p><a href="SupplementS1/Parameters.cpp">Parameters.cpp</a> (MD5: 98844c290091a34b2cdc40b15db5f04b)</p> <p><a href="SupplementS1/Predators.h">Predators.h</a> (MD5: 381b096a56401a89af3b9ae6d69efc5b)</p> <p><a href="SupplementS1/Predators.cpp">Predators.cpp</a> (MD5: fd8ceed5b4085231c5c11b63ee80f631)</p> <p><a href="SupplementS1/randomc.h">randomc.h</a> (MD5: c9a7dd78ee8ffc00743f8346835638a8)</p> <p><a href="SupplementS1/stoc1.cpp">stoc1.cpp</a> (MD5: cc18034beb9b8b47ccbf3a67c04c87a8)</p> <p><a href="SupplementS1/stocc.h">stocc.h</a> (MD5: 3748e5471bf7b8b1d8f16ac201e54f01)</p> <p><a href="SupplementS1/userintf.cpp">userintf.cpp</a> (MD5: 4b20c9c2a5b06636fbcbd66891834c7e)</p> <p><a href="SupplementS1/readme.txt">readme.txt</a> (MD5: b2fef2ece86f9574c562f8235f5fa648)</p> </div><h2>Description</h2><div> <p>C++ individual-based model used in this study to model the spatial distribution of fixed dispersal phenotypes in a landscape consisting of n × n patches with spatiotemporal uncorrelated variation in <i>K</i>. The implementation of the model is fairly crude, in that model parameters are set within the file Parameters.cpp prior to compilation, and the model as it stands can therefore be run for only one set of parameters at a time. However, it would be possible to introduce <i>for</i> loops into the code within Main.cpp to vary parameters of interest. Technical information to run the model is described in the readme.txt file. Code was written by Stephen C. F. Palmer, to whom correspondence regarding these files should be addressed. </p> </div