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Genic distribution modelling predicts adaptation of the bank vole to climate change.

ABSTRACT: The most likely pathway for many species to survive future climate change is by pre-existing trait variation providing a fitness advantage under the new climate. Here we evaluate the potential role of haemoglobin (Hb) variation in bank voles under future climate change. We model gene-climate relationships for two functionally distinct Hb types, HbS and HbF, which have a north-south distribution in Britain presenting an unusually tractable system linking genetic variation in physiology to geographical and temporal variation in climate. Projections to future climatic conditions suggest a change in relative climatic suitability that would result in HbS being displaced by HbF in northern Britain. This would facilitate local adaptation to future climate-without Hb displacement, populations in northern Britain would likely be suboptimally adapted because their Hb would not match local climatic conditions. Our study shows how pre-existing physiological differences can influence the adaptive capacity of species to climate change.

SUBMITTER: Escalante MA

PROVIDER: S-EPMC9481625 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Genic distribution modelling predicts adaptation of the bank vole to climate change.

Escalante Marco A MA Marková Silvia S Searle Jeremy B JB Kotlík Petr P

Communications biology 20220916 1

The most likely pathway for many species to survive future climate change is by pre-existing trait variation providing a fitness advantage under the new climate. Here we evaluate the potential role of haemoglobin (Hb) variation in bank voles under future climate change. We model gene-climate relationships for two functionally distinct Hb types, HbS and HbF, which have a north-south distribution in Britain presenting an unusually tractable system linking genetic variation in physiology to geograp ...[more]

PMID: 36114276

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Project description:Species distribution modelling (SDM) is an important tool to examine the possible change in the population range and/or niche-shift under current environment and predicted climate change. Monotheca buxifolia is an economically and ecologically important tree species inhabiting Pakistan and Afghanistan in dense patches, and species range is contracting rapidly. This study hypothesize that predicted climate change might remarkably influence the existing distribution pattern of M. buxifolia in the study area. A total of 75 occurrence locations were identified comprising M. buxifolia as a dominant tree species. The Maximum Entropy (MaxEnt) algorithm was utilized to perform the SDM under current (the 1970s-2000s) and two future climate change scenarios (shared socioeconomic pathways: SSPs 245 and 585) of two time periods (the 2050s and 2070s). The optimal model settings were assessed, and simulation precision was assessed by examining the partial area under the receiver operating characteristic curve (pAUC-ROC). The results showed that out of 39 considered bio-climatic, topographic, edaphic, and remote sensing variables which were utilized in the preliminary model, 6 variables including precipitation of warmest quarter, topographic diversity, global human modification of terrestrial land, normalized difference vegetation index, isothermality, and elevation (in order) were the most influential drivers, and utilized in all reduced SDMs. A high predictive performance (pAUC-ROC; >0.9) of all the considered SDMs was recorded. A total of about 67,684 km2 of geographical area was predicted as suitable habitat (p > 0.8) for M. buxifolia, and Pakistan is the leading country (with about 54,975 km2 of suitable land area) under the current climate scenario. Overall, the existing distribution of the tree species in the study area might face considerable loss (i.e. rate of change %; -27 to -107) in future, and simultaneously a northward (high elevation) niche shift is predicted for all the considered future climate change scenarios. Hence, development and implementation of a coordinated conservation program is required on priority basis to save the tree species in its native geographic range.

Project description:BackgroundClimate change is predicted to impact the transmission dynamics of vector-borne diseases. Tsetse flies (Glossina) transmit species of Trypanosoma that cause human and animal African trypanosomiasis. A previous modelling study showed that temperature increases between 1990 and 2017 can explain the observed decline in abundance of tsetse at a single site in the Mana Pools National Park of Zimbabwe. Here, we apply a mechanistic model of tsetse population dynamics to predict how increases in temperature may have changed the distribution and relative abundance of Glossina pallidipes across northern Zimbabwe.MethodsLocal weather station temperature measurements were previously used to fit the mechanistic model to longitudinal G. pallidipes catch data. To extend the use of the model, we converted MODIS land surface temperature to air temperature, compared the converted temperatures with available weather station data to confirm they aligned, and then re-fitted the mechanistic model using G. pallidipes catch data and air temperature estimates. We projected this fitted model across northern Zimbabwe, using simulations at a 1 km × 1 km spatial resolution, between 2000 to 2016.ResultsWe produced estimates of relative changes in G. pallidipes mortality, larviposition, emergence rates and abundance, for northern Zimbabwe. Our model predicts decreasing tsetse populations within low elevation areas in response to increasing temperature trends during 2000-2016. Conversely, we show that high elevation areas (> 1000 m above sea level), previously considered too cold to sustain tsetse, may now be climatically suitable.ConclusionsTo our knowledge, the results of this research represent the first regional-scale assessment of temperature related tsetse population dynamics, and the first high spatial-resolution estimates of this metric for northern Zimbabwe. Our results suggest that tsetse abundance may have declined across much of the Zambezi Valley in response to changing climatic conditions during the study period. Future research including empirical studies is planned to improve model accuracy and validate predictions for other field sites in Zimbabwe.

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Genic distribution modelling predicts adaptation of the bank vole to climate change.

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Genic distribution modelling predicts adaptation of the bank vole to climate change.

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