Coarse climate change projections for species living in a fine‐scaled world

Nadeau, Christopher P.; Urban, Mark C.; Bridle, Jon R.

doi:10.1111/gcb.13475

Cited by 67 publications

(63 citation statements)

References 68 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Lastly, surveys spaced over four decades might miss potentially important temporal variability both in climate and morph frequency changes. The temporal and spatial variability in climate and an increasing frequency of extreme events (Buckley et al 2012, Vasseur et al 2014) might explain some site-specific responses better than simple hypotheses equating morph frequencies to mean climate variables (Gibbs and Karraker 2006, Moore and Ouellet 2015, Nadeau et al 2017. This result has been demonstrated in repeated surveys of polymorphic land snail species, which show correlations between morph frequency changes and climate variation across multiple time periods (Cameron andPokryszko 2008, Johnson 2011).…”

Section: Modelmentioning

confidence: 96%

Salamander morph frequencies do not evolve as predicted in response to 40 years of climate change

et al. 2018

Self Cite

View full text Add to dashboard Cite

The global climate is changing rapidly, yet biotic responses remain uncertain. Most studies focus on changes in species ranges or plastic responses like phenology, but adaptive evolution could be equally important. Studying evolutionary responses is challenging given limited historical data and a poor understanding of genetically variable traits under selection. We take advantage of a historical dataset to test for an adaptive response to climate change in a widespread, polymorphic amphibian, the eastern red‐backed salamander Plethodon cinereus. We resurveyed color morph frequencies across New England to test for an adaptive shift in response to climate change. We modeled historical and present‐day morph proportions as a function of climate and tested the accuracy of predictions both within and across different time periods. Our models showed moderate accuracy when predicting morph frequencies within time periods, but poor accuracy across time periods. Despite substantial changes in climate and significant relationships between morph frequency and climate variables within periods, we found no evidence for the predicted shift in morph frequencies across New England. The relationship between climate and color morph frequencies is likely more complex than originally suggested, potentially involving the interplay of additional factors such as microclimate variation, land use changes, and frequency‐dependent selection. Model extrapolation and changes in the correlation structure of climate variables also likely contributed to poor predictive ability. Evolution could provide a means to moderate the effects of climate change on many species. However, we often do not understand the direct links between climate variation, traits, and fitness. Therefore, forecasting climate‐mediated evolution remains an ongoing and important challenge for understanding climate change threats to species.

show abstract

Section: Modelmentioning

confidence: 96%

Salamander morph frequencies do not evolve as predicted in response to 40 years of climate change

et al. 2018

Self Cite

View full text Add to dashboard Cite

show abstract

“…SDMs the appropriate spatial resolution depends on the species considered, as large and mobile organisms might be well-represented by large-scale climatic conditions, whereas small and less mobile species might not (Nadeau, Urban, & Bridle, 2017). This also strongly depends on the data source considered, as range maps at a high resolution typically result in incorrect spatial patterns of species richness (Hurlbert & Jetz, 2007).…”

Section: Current Patterns Of Species Richnessmentioning

confidence: 99%

A comparison of macroecological and stacked species distribution models to predict future global terrestrial vertebrate richness

Biber

Voskamp

Niamir

et al. 2019

Journal of Biogeography

View full text Add to dashboard Cite

Aim Predicting future changes in species richness in response to climate change is one of the key challenges in biogeography and conservation ecology. Stacked species distribution models (S‐SDMs) are a commonly used tool to predict current and future species richness. Macroecological models (MEMs), regression models with species richness as response variable, are a less computationally intensive alternative to S‐SDMs. Here, we aim to compare the results of two model types (S‐SDMS and MEMs), for the first time for more than 14,000 species across multiple taxa globally, and to trace the uncertainty in future predictions back to the input data and modelling approach used. Location Global land, excluding Antarctica. Taxon Amphibians, birds and mammals. Methods We fitted S‐SDMs and MEMs using a consistent set of bioclimatic variables and model algorithms and conducted species richness predictions under current and future conditions. For the latter, we used four general circulation models (GCMs) under two representative concentration pathways (RCP2.6 and RCP6.0). Predicted species richness was compared between S‐SDMs and MEMs and for current conditions also to extent‐of‐occurrence (EOO) species richness patterns. For future predictions, we quantified the variance in predicted species richness patterns explained by the choice of model type, model algorithm and GCM using hierarchical cluster analysis and variance partitioning. Results Under current conditions, species richness predictions from MEMs and S‐SDMs were strongly correlated with EOO‐based species richness. However, both model types over‐predicted areas with low and under‐predicted areas with high species richness. Outputs from MEMs and S‐SDMs were also highly correlated among each other under current and future conditions. The variance between future predictions was mostly explained by model type. Main conclusions Both model types were able to reproduce EOO‐based patterns in global terrestrial vertebrate richness, but produce less collinear predictions of future species richness. Model type by far contributes to most of the variation in the different future species richness predictions, indicating that the two model types should not be used interchangeably. Nevertheless, both model types have their justification, as MEMs can also include species with a restricted range, whereas S‐SDMs are useful for looking at potential species‐specific responses.

show abstract

“…In primary forests and secondary forests re‐growing on abandoned farmland, previous studies found that organisms—particularly ectotherms—avoid suboptimal temperatures in the wider “macroclimate” (climate at a spatial scale of m to ha) by moving locally into “microclimates”: climate at a fine‐scale, mm to m, that is distinct from the macroclimate (González del Pliego et al., ; Scheffers, Brett, Diesmos, Williams, & Evans, ; Scheffers, Evans, Williams, & Edwards, ). Climate at this fine‐scale is more relevant for the majority of terrestrial biodiversity, which primarily consists of small‐bodied ectotherms (Nadeau, Urban, & Bridle, ; Potter, Arthur Woods, & Pincebourde, ; Suggitt et al., ). Indeed, the vast proportion of terrestrial species are small in size, flat in shape, or thermoregulate via contact with a substrate, and so it is important to consider microclimates close to, and including, the surfaces on which these species live (Kaspari, Clay, Lucas, Yanoviak, & Kay, ; Scheffers et al., ).…”

Section: Introductionmentioning

confidence: 99%

Tropical forests are thermally buffered despite intensive selective logging

Senior

Hill

Benedick

et al. 2017

Global Change Biology

View full text Add to dashboard Cite

Tropical rainforests are subject to extensive degradation by commercial selective logging. Despite pervasive changes to forest structure, selectively logged forests represent vital refugia for global biodiversity. The ability of these forests to buffer temperature-sensitive species from climate warming will be an important determinant of their future conservation value, although this topic remains largely unexplored.Thermal buffering potential is broadly determined by: (i) the difference between the "macroclimate" (climate at a local scale, m to ha) and the "microclimate" (climate at a fine-scale, mm to m, that is distinct from the macroclimate); (ii) thermal stability of microclimates (e.g. variation in daily temperatures); and (iii) the availability of microclimates to organisms. We compared these metrics in undisturbed primary forest and intensively logged forest on Borneo, using thermal images to capture cool microclimates on the surface of the forest floor, and information from dataloggers placed inside deadwood, tree holes and leaf litter. Although major differences in forest structure remained 9-12 years after repeated selective logging, we found that logging activity had very little effect on thermal buffering, in terms of macroclimate and microclimate temperatures, and the overall availability of microclimates. For 1°C warming in the macroclimate, temperature inside deadwood, tree holes and leaf litter warmed slightly more in primary forest than in logged forest, but the effect amounted to <0.1°C difference between forest types. We therefore conclude that selectively logged forests are similar to primary forests in their potential for thermal buffering, and subsequent ability to retain temperature-sensitive species under climate change. Selectively logged forests can play a crucial role in the long-term maintenance of global biodiversity.

show abstract

Coarse climate change projections for species living in a fine‐scaled world

Cited by 67 publications

References 68 publications

Salamander morph frequencies do not evolve as predicted in response to 40 years of climate change

Salamander morph frequencies do not evolve as predicted in response to 40 years of climate change

A comparison of macroecological and stacked species distribution models to predict future global terrestrial vertebrate richness

Tropical forests are thermally buffered despite intensive selective logging

Contact Info

Product

Resources

About