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Fig 2 (heatmap) data files and R codeData and R code needed to create Fig 2 in Hargreaves et al (2015) J Evol Biol. One data file for each of the 6 figure panels. Each file contains evolved D across the range in each of 500 generations of stable climate followed by 1000 generations of climate change.Fig 2 (heatmap).zipFig 3 (D lines) data and R codeData and R code needed to create Fig 3 in Hargreaves et al (2015) J Evol Biol. One data file for each of the 6 models shown. Each file contains evolved D across the range after 500 generations of stable climate and after 1000 generations of climate change, averaged across 10 runs per cost per model.Fig 3 (D lines).zipFig 4 (delta.D) data and R codeData and R code needed to create Fig 4 in Hargreaves et al (2015) J Evol Biol. One data file for each of the 4 models (ie figure rows) shown. Each file contains evolved D across the range after 500 generations of stable climate and after 1000 generations of climate change for 30 runs per model.Fig 4 (delta.D).zipFig 6 (D vs density) data and R codeData and R code needed to create Fig 6 in Hargreaves et al (2015) J Evol Biol. Two data files (one for evolved D and one for density) for each of 2 model runs, one with dispersal (dispersal distance =1 as normal) and one run without dispersal (dispersal distance =0).Fig 6 (D vs density).zipAppendix S1 data and R code for each figureData and R code needed to create figures in Appendix S1 in Hargreaves et al (2015) J Evol Biol. All figures remake Fig 3 while varying one parameter. Fig S1.1 shows murate = .005; Fig S1.2 shows avshift = .01, .05, .2; Fig. S1.3 shows K=10; Fig. S1.4 shows effect of eliminating kin selection by randomizing individuals within columns before each dispersal event. For each figure there is 1 data file per model. Each data file contains evolved D across the range after 500 generations of stable climate and after 1000 generations of climate change, for 10 runs per cost.Appendix S1.zipModel code Matlab fileCode to run the model simulations.rangeshift (for dryad).mFig 5 (extinction threshold) Matlab codeMatlab code to run the simulations necessary to determine the relationship between the speed of climate change (avshift) and probability of extinction.rangeshift_thresh (for dryad).m Dispersal ability will largely determine whether species track their climatic niches during climate change, a process especially important for populations at contracting (low-latitude/low-elevation) range limits that otherwise risk extinction. We investigate whether dispersal evolution at contracting range limits is facilitated by two processes that potentially enable edge populations to experience and adjust to the effects of climate deterioration before they cause extinction: (i) climate-induced fitness declines towards range limits and (ii) local adaptation to a shifting climate gradient. We simulate a species distributed continuously along a temperature gradient using a spatially explicit, individual-based model. We compare range-wide dispersal evolution during climate stability vs. directional climate change, with uniform fitness vs. fitness that declines towards range limits (RLs), and for a single climate genotype vs. multiple genotypes locally adapted to temperature. During climate stability, dispersal decreased towards RLs when fitness was uniform, but increased when fitness declined towards RLs, due to highly dispersive genotypes maintaining sink populations at RLs, increased kin selection in smaller populations, and an emergent fitness asymmetry that favoured dispersal in low-quality habitat. However, this initial dispersal advantage at low-fitness RLs did not facilitate climate tracking, as it was outweighed by an increased probability of extinction. Locally adapted genotypes benefited from staying close to their climate optima; this selected against dispersal under stable climates but for increased dispersal throughout shifting ranges, compared to cases without local adaptation. Dispersal increased at expanding RLs in most scenarios, but only increased at the range centre and contracting RLs given local adaptation to climate.

File format: NetCDFSimulated/analyzed periods: 1989-2010 (current) and 2079-2100 (future)The repository for the analysis code is attached.Entry scripts for the figures are:- figure1, 4: src/lake_effect_snow/hles_cc/plot_monthly_histograms_cc_and_domain.py- figure2(partially lake ice fraction), figure3: src/lake_effect_snow/hles_cc_validation/validate_hles_and_related_params_biases_and_obs.py- figure5: src/lake_effect_snow/hles_cc/plot_cc_2d_all_variables_for_all_periods_001.py- figure6: src/lake_effect_snow/hles_cc/hles_tt_and_pr_correlations_mean_ice_fraction.py- cold_air.m for part of Fig. 2 and hles_intensity.m for Fig. 7 The dataset contains Heavy Lake Effect Snowfall (HLES) and related parameters from GEM outputs (RCP8.5, 10 km horizontal resolution, Laurentian Great Lakes region, driven by CanESM2 at the boundaries) and observation datasets. Observation data included are: interpolated to the model grid Daymet 2m air temperature and total precipitation, CIS-NIC ice concentration observations, and REA-Interim near-surface winds.

List of DIGE-spots with homology with sequences in databases that are up-regulated in response to cold acclimation (ANOVA, Pâ

1.Increasing demand for benefits provided by riverine ecosystems threatens their sustainable provision. The ecosystem service concept is a promising avenue to inform riverine ecosystem management, but several challenges have prevented the application of this concept. 2.We quantitatively assess the field of riverine ecosystem services’ progress in meeting these challenges. We highlight conceptual and methodological gaps, which have impeded integration of the ecosystem service concept into management. 3.Across 89 relevant studies, 33 unique riverine ecosystem services were evaluated, for a total of 404 ecosystem service quantifications. Studies quantified between one and 23 ecosystem services, although the majority (55%) evaluated three or less. Among studies that quantified more than one service, 58% assessed interactions between services. Most studies (71%) did not include stakeholders in their quantification protocols, and 34% developed future scenarios of ecosystem service provision. Almost half (45%) conducted monetary valuation, using 16 methods. Only 9% did not quantify or discuss uncertainties associated with service quantification. The indicators and methods used to quantify the same type of ecosystem service varied. Only 3% of services used indicators of capacity, flow, and demand in concert. 4.Our results suggest indicators, data sources, and methods for quantifying riverine ecosystem services should be more clearly defined and accurately represent the service they intend to quantify. Furthermore, more assessments of multiple services across diverse spatial extents and of riverine service interactions are needed, with better inclusion of stakeholders. Addressing these challenges will help riverine ecosystem service science inform river management. 5.Synthesis and applications. The ecosystem service concept has great potential to inform riverine ecosystem management and decision making processes. However, this review of riverine ecosystem service quantification uncovers several remaining research gaps, impeding effective use of this tool to manage riverine ecosystems. We highlight these gaps and point to studies showcasing methods that can be used to address them. Review of riverine ecosystem service quantification studiesThis file contains a database of studies that quantified riverine ecosystem services prior to April 2016, as well as quantitative data on the location of each study, the types and numbers of ecosystem services evaluated, and the methods used to quantify services.Hanna_Riverine ES Review Database.xlsx

Background: Sea ice across the Arctic is declining and altering physical characteristics of marine ecosystems. Polar bears (Ursus maritimus) have been identified as vulnerable to changes in sea ice conditions. We use sea ice projections for the Canadian Arctic Archipelago from 2006 – 2100 to gain insight into the conservation challenges for polar bears with respect to habitat loss using metrics developed from polar bear energetics modeling. Principal Findings: Shifts away from multiyear ice to annual ice cover throughout the region, as well as lengthening ice-free periods, may become critical for polar bears before the end of the 21st century with projected warming. Each polar bear population in the Archipelago may undergo 2–5 months of ice-free conditions, where no such conditions exist presently. We identify spatially and temporally explicit ice-free periods that extend beyond what polar bears require for nutritional and reproductive demands. Conclusions/Significance: Under business-as-usual climate projections, polar bears may face starvation and reproductive failure across the entire Archipelago by the year 2100. Depth-bathymetry fileUse as land mask file when depth=0depth.ncMITgcm_SeaIce_GFDL_CM3_RCP85_2006-2100Monthly average sea ice and snow conditions in the Canadian Arctic Archipelago 2006-2100 under climate warming scenario RCP85. Model output in netcdf files, time steps of 1 month starting on January 2006.MITgcm_SeaIce_GFDL_CM3_RCP85_2006_2100.zip

Spatial heterogeneity in the strength of trophic interactions is a fundamental property of food web spatial dynamics. The feeding effort of herbivores should reflect adaptive decisions that only become rewarding when foraging gains exceed 1) the metabolic costs, 2) the missed opportunity costs of not foraging elsewhere, and 3) the foraging costs of anti-predator behaviour. Two aspects of these costs remain largely unexplored: the link between the strength of plant-herbivore interactions and the spatial scale of food-quality assessment, and the predator-prey spatial game. We modeled the foraging effort of free-ranging plains bison (Bison bison bison) in winter, within a mosaic of discrete meadows. Spatial patterns of bison herbivory were largely driven by a search for high net energy gains and, to a lesser degree, by the spatial game with grey wolves (Canis lupus). Bison decreased local feeding effort with increasing metabolic and missed opportunity costs. Bison herbivory was most consistent with a broad-scale assessment of food patch quality, i.e., bison grazed more intensively in patches with a low missed opportunity cost relative to other patches available in the landscape. Bison and wolves had a higher probability of using the same meadows than expected randomly. This co-occurrence indicates wolves are ahead in the spatial game they play with bison. Wolves influenced bison foraging at fine scale, as bison tended to consume less biomass at each feeding station when in meadows where the risk of a wolf's arrival was relatively high. Also, bison left more high-quality vegetation in large than small meadows. This behavior does not maximize their energy intake rate, but is consistent with bison playing a shell game with wolves. Our assessment of bison foraging in a natural setting clarifies the complex nature of plant-herbivore interactions under predation risk, and reveals how spatial patterns in herbivory emerge from multi-scale landscape heterogeneity. HarveyFortinDataset S1Field data

Additional file 1. Geographical, genetic, and kinetic parameter information for hybrids.

Changes in ocean ventilation driven by climate change result in loss of oxygen in the open ocean that, in turn, affects coastal areas in upwelling zones such as the northeast Pacific. Saanich Inlet, on the west coast of Canada, is a natural seasonally hypoxic fjord where certain continental shelf species occur in extreme hypoxia. One study site on the VENUS cabled subsea network is located in the hypoxic zone at 104 m depth. Photographs of the same 5 m2 area were taken with a remotely-controlled still camera every 2/3 days between October 6th 2009 and October 18th 2010 and examined for community composition, species behaviour and microbial mat features. Instruments located on a near-by platform provided high-resolution measurements of environmental variables. We applied multivariate ordination methods and a principal coordinate analysis of neighbour matrices to determine temporal structures in our dataset. Responses to seasonal hypoxia (0.1���1.27 ml/l) and its high variability on short time-scale (hours) varied among species, and their life stages. During extreme hypoxia, microbial mats developed then disappeared as a hippolytid shrimp, Spirontocaris sica, appeared in high densities (200 m22) despite oxygen below 0.2 ml/l. The slender sole Lyopsetta exilis was abundant in severe hypoxia and diminished as oxygen increased in the summer. This planktivore may be responding to changes in the depth of the diurnal migration of zooplankton. While the squat lobster Munida quadrispina was common at all times, juveniles disappeared in fluctuating conditions. Despite low oxygen conditions, animal densities were high indicating that the risk from hypoxia is balanced by factors such as food availability and escape from less tolerant predators. As hypoxia increases on the continental shelf, we expect benthic communities to become dominated by low diversity, hypoxia-tolerant species of low commercial significance. CHONe_MB08_Matabos_data_year

Ontogenetic niche shifts are widely prevalent in nature and are important in shaping the structure and dynamics of ecosystems. Stable isotope analysis is a powerful tool to assess these shifts, with δ15N providing a measure of trophic level and δ13C a measure of energy source. Previous applications of stable isotopes to study ontogenetic niche shifts have not considered the appreciable time-lag between diet and consumer tissue associated with isotopic turnover. These time-lags introduce significant complexity into field studies of ontogenetic niche shifts. Juvenile Chinook Salmon (Oncorhynchus tshawytscha) migrate from freshwater to marine ecosystems, and shift their diet from feeding primarily on invertebrates to feeding primarily on fish. This dual ontogenetic habitat and diet shift, in addition to the long time-lag associated with isotopic turnover, suggests that there is potential for a disconnect between the prey sources that juvenile salmon are consuming, and the inferred prey sources from stable isotope analysis. We developed a model that considered ontogenetic niche shifts and time-lags associated with isotopic turnover, and compared this ‘ontogeny’ model to one that considered only isotopic turnover. We used a Bayesian framework to explicitly account for parameter uncertainty. Data showed overwhelming support for the ontogeny model relative to the isotopic turnover model. Estimated variables from best model fits indicate that the ontogeny model predicts a much greater reliance on fish prey than does the stomach content data. Overall, we found that this method of quantifying ontogenetic niche shifts effectively accounted for both isotopic turnover and ontogenetic diet shifts; a finding that could be widely applicable to a variety of systems. Hertzetal16ChinookIsotopesd13C, d15N of dorsal muscle tissue and weights (g) of juvenile Chinook Salmon caught off the west coast of Vancouver Island from 2000-2009. d13C values were corrected for differences in sample preparation following Fig S3, and were lipid-corrected following Post et al. 2007.Hertzetal16Iso.csv

Tropical dry forests (TDFs) are ecosystems with long drought periods, a mean temperature of 25 ��C, a mean annual precipitation that ranges from 900 to 2000 mm, and that possess a high abundance of deciduous species (trees and lianas). What remains of the original extent of TDFs in the Americas remains highly fragmented and at different levels of ecological succession. It is estimated that one of the main fingerprints left by global environmental and climate change in tropical environments is an increase in liana coverage. Lianas are non-structural elements of the forest canopy that eventually kill their host trees. In this paper we evaluate the use of a terrestrial laser scanner (TLS) in combination with hemispherical photographs (HPs) to characterize changes in forest structure as a function of ecological succession and liana abundance. We deployed a TLS and HP system in 28 plots throughout secondary forests of different ages and with different levels of liana abundance. Using a canonical correlation analysis (CCA), we addressed how the VEGNET, a terrestrial laser scanner, and HPs could predict TDF structure. Likewise, using univariate analyses of correlations, we show how the liana abundance could affect the prediction of the forest structure. Our results suggest that TLSs and HPs can predict the differences in the forest structure at different successional stages but that these differences disappear as liana abundance increases. Therefore, in well known ecosystems such as the tropical dry forest of Costa Rica, these biases of prediction could be considered as structural effects of liana presence. This research contributes to the understanding of the potential effects of lianas in secondary dry forests and highlights the role of TLSs combined with HPs in monitoring structural changes in secondary TDFs. SR-EMSS BiogeosciencesLocation of selected sampling sites at the Santa Rosa National Park Environmental Monitoring Super Site. Data represents three levels of information: Terrestrial Scanner derived Information, Hemispherical Photos Derived information, and structural forest parameters. Data provides also latitude and longitude of each plot.Biogeosciences Santa Rosa TLS plots.xlsx