Climate surfaces are digital representations of climatic variables from a region in the planet estimated via geographical interpolation techniques. Climate surfaces have multiple applications in research planning, experimental design, and technology transfer. Although high‐resolution climatologies have been developed worldwide, Mexico is one of the few countries that have developed several climatic surfaces. Here, we present an updated high‐resolution (30 arc sec) climatic surfaces for Mexico for the average monthly climate period 1910–2009, corresponding to monthly values of precipitation, daily maximum, and minimum temperature, as well as 19 bioclimatic variables derived from the monthly precipitation and temperature values. To produce these surfaces we applied the thin‐plate smoothing spline interpolation algorithm implemented in the ANUSPLIN software to nearly 5000 climate weather stations countrywide. As an additional product and unlike the previous efforts, we generated monthly standard error surfaces for the three climate parameters, which can be used for error assessment when using these climate surfaces. Our climate surface predicted slightly drier and cooler conditions than the previous ones. ANUSPLIN diagnostic statistics indicated that model fit was adequate. We implemented a more recent error assessment, a set of withheld stations to perform an independent evaluation of the model surfaces. We estimate the mean absolute error and mean error, with the withheld data and all the available data. Average RTGCV for monthly temperatures was of 1.26–1.12 °C and 24.67% for monthly precipitation, and a RTMSE of 0.48–0.56 °C and 11.11%. The main advantage of the surfaces presented here regarding the other three developed for the country is that ours cover practically the entire 20th century and almost the entire first decade of the 21st century. It is the most up to date high‐resolution climatology for the country.

Spatial assessments of historical climate change provide information that can be used by scientists to analyze climate variation over time and evaluate, for example, its effects on biodiversity, in order to focus their research and conservation efforts. Despite the fact that there are global climatic databases available at high spatial resolution, they represent a short temporal window that impedes evaluating historical changes of climate and their impacts on biodiversity. To fill this gap, we developed climate gridded surfaces for Mexico for three periods that cover most of the 20^th and early 21^st centuries: t₁-1940 (1910–1949), t₂-1970 (1950–1979) and t₃-2000 (1980–2009), and used these interpolated surfaces to describe how climate has changed over time, both countrywide and in its 19 biogeographic provinces. Results from our characterization of climate change indicate that the mean annual temperature has increased by nearly 0.2°C on average across the whole country from t₂-1970 to t₃-2000. However, changes have not been spatially uniform: Nearctic provinces in the north have suffered higher temperature increases than southern tropical regions. Central and southern provinces cooled at the beginning of the 20^th century but warmed consistently since the 1970s. Precipitation increased between t₁-1940 and t₂-1970 across the country, more notably in the northern provinces, and it decreased between t₂-1970 and t₃-2000 in most of the country. Results on the historical climate conditions in Mexico may be useful for climate change analyses for both environmental and social sciences. Nonetheless, our climatology was based on information from climate stations for which 9.4–36.2% presented inhomogeneities over time probably owing to non-climatic factors, and climate station density changed over time. Therefore, the estimated changes observed in our analysis need to be interpreted cautiously.

Evaluation of various climate change factors on Mexican bird populations shows temperature has the strongest influence.

Global change drives biodiversity shifts worldwide, but these shifts are poorly understood in highly diverse tropical regions. In tropical mountains, plants are mostly expected to migrate upslope in response to warming. To assess this, we analyze shifts in elevation ranges of species in Mesoamerican cloud forests using three decades of species’ occurrence records. Our findings reveal a mean upslope shift of 1.8 to 2.7 meters per year since 1979 driven by the upslope retreat of the less thermophilic montane species. These shifts are mostly accompanied by retreating lower and upper edges attributed to varying degrees of species’ exposure to deforestation and climate change. Our results highlight the vulnerability of cloud forests under global change and the urgency to increase monitoring of species’ responses.

There is a need to revise the framework used to project species risks under climate change (CC) and land‐use/cover change (LUCC) scenarios. We built a CC risk index using the latest Intergovernmental Panel on Climate Change framework, where risk is a function of vulnerability (sensitivity and adaptive capacity), exposure, and hazard. We incorporated future LUCC scenarios as part of the exposure component. We combined a trait‐based approach based on biological characteristics of species with a correlative approach based on ecological niche modeling, assigning risk scores to species, taxonomic (orders), and functional (trophic, body size, and locomotion) groups of terrestrial mammals occurring in Mexico. We identified 15 species projected to lose their climatic suitability. Of the 11 taxonomic orders, Eulipotyphla, Didelphimorphia, Artiodactyla, and Lagomorpha had the highest risk scores. Of the 19 trophic groups, piscivores, insectivores under canopy, frugivores–granivores, herbivores browser, and myrmecophagous had the highest risk scores. Of the five body‐sized groups, large‐sized species (>15 kg) had highest risk scores. Of the seven locomotion groups, arboreal and semi‐aquatics had highest risk scores. CC and LUCC scenarios reduced suitable areas of species potential distributions by 37.5% (with CC), and 51% (with CC and LUCC) under a limited full‐dispersal assumption. Reductions in suitable areas of species potential distributions increased to 50.2% (with CC), and 52.4% (with CC and LUCC) under a non‐dispersal assumption. Species‐rich areas (>75% species) projected 36% (with CC) and 57% (with CC and LUCC) reductions in suitability for 2070. Shifts in climatic suitability projections of species‐rich areas increased in number of species in northeast and southeast Mexico and decreased in northwest and southern Mexico, suggesting important species turnover. High‐risk projections under future CC and LUCC scenarios for species, taxonomic, and functional group diversities, and species‐rich areas of terrestrial mammals highlight trends in different impacts on biodiversity and ecosystem function.

Crop wild relatives (CWR) intra- and interspecific diversity is essential for crop breeding and food security. However, intraspecific genetic diversity, which is central given the idiosyncratic threats to species in landscapes, is usually not considered in planning frameworks. Here, we introduce an approach to develop proxies of genetic differentiation to identify conservation areas, applying systematic conservation planning tools that produce hierarchical prioritizations of the landscape. It accounts for: (i) evolutionary processes, including historical and environmental drivers of genetic diversity, and (ii) threat processes, considering taxa-specific tolerance to human-modified habitats, and their extinction risk status. Our analyses can be used as inputs for developing national action plans for the conservation and use of CWR. Our results also inform public policy to mitigate threat processes to CWR (like crops living modified organisms or agriculture subsidies), and could advise future research (e.g. for potential germplasm collecting). Although we focus on Mesoamerican CWR within Mexico, our methodology offers opportunities to effectively guide conservation and monitoring strategies to safeguard the evolutionary resilience of any taxa, including in regions of complex evolutionary histories and mosaic landscapes.