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.

Walker’s Manihot, Manihot walkerae, is an endangered plant that is endemic to the Tamaulipan thornscrub ecoregion of extreme southern Texas and northeastern Mexico. M. walkerae populations are highly fragmented and are found on both protected public lands and private property. Habitat loss and competition by invasive species are the most detrimental threats for M. walkerae; however, the effect of climate change on M. walkerae’s geographic distribution remains unexplored and could result in further range restrictions. Our objectives are to evaluate the potential effects of climate change on the distribution of M. walkerae and assess the usefulness of natural protected areas in future conservation. We predict current and future geographic distribution for M. walkerae (years 2050 and 2070) using three different general circulation models (CM3, CMIP5, and HADGEM) and two climate change scenarios (RCP 4.5 and 8.5). A total of nineteen spatially rarefied occurrences for M. walkerae and ten non-highly correlated bioclimatic variables were inputted to the maximum entropy algorithm (MaxEnt) to produce twenty replicates per scenario. The area under the curve (AUC) value for the consensus model was higher than 0.90 and the partial ROC value was higher than 1.80, indicating a high predictive ability. The potential reduction in geographic distribution for M. walkerae by the effect of climate change was variable throughout the models, but collectively they predict a restriction in distribution. The most severe reductions were 9% for the year 2050 with the CM3 model at an 8.5 RCP, and 14% for the year 2070 with the CMIP5 model at the 4.5 RCP. The future geographic distribution of M. walkerae was overlapped with protected lands in the U.S. and Mexico in order to identify areas that could be suitable for future conservation efforts. In the U.S. there are several protected areas that are potentially suitable for M. walkerae, whereas in Mexico no protected areas exist within M. walkerae suitable habitat.

Protected areas are of paramount relevance to conserving wildlife and ecosystem contributions to people. Yet, their conservation success is increasingly threatened by human activities including habitat loss, climate change, pollution, and species overexploitation. Thus, understanding the underlying and proximate drivers of anthropogenic threats is urgently needed to improve protected areas’ effectiveness, especially in the biodiversity-rich tropics. We addressed this issue by analyzing expert-provided data on long-term biodiversity change (last three decades) over 14 biosphere reserves from the Mesoamerican Biodiversity Hotspot. Using multivariate analyses and structural equation modeling, we tested the influence of major socioeconomic drivers (demographic, economic, and political factors), spatial indicators of human activities (agriculture expansion and road extension), and forest landscape modifications (forest loss and isolation) as drivers of biodiversity change. We uncovered a significant proliferation of disturbance-tolerant guilds and the loss or decline of disturbance-sensitive guilds within reserves causing a “winner and loser” species replacement over time. Guild change was directly related to forest spatial changes promoted by the expansion of agriculture and roads within reserves. High human population density and low nonfarming occupation were identified as the main underlying drivers of biodiversity change. Our findings suggest that to mitigate anthropogenic threats to biodiversity within biosphere reserves, fostering human population well-being via sustainable, nonfarming livelihood opportunities around reserves is imperative.

Climate change may influence the incidence of infectious diseases including those transmitted by ticks. Rhipicephalus sanguineus complex has a worldwide distribution and transmits Rickettsial infections that could cause high mortality rates if untreated. We assessed the potential effects of climate change on the distribution of R. sanguineus in the Americas in 2050 and 2070 using the general circulation model CanESM5 and two shared socioeconomic pathways (SSPs), SSP2-4.5 (moderate emissions) and SSP2-8.5 (high emissions). A total of 355 occurrence points of R. sanguineus and eight uncorrelated bioclimatic variables were entered into a maximum entropy algorithm (MaxEnt) to produce 50 replicates per scenario. The area under the curve (AUC) value for the consensus model (>0.90) and the partial ROC value (>1.28) indicated a high predictive capacity. The models showed that the geographic regions currently suitable for R. sanguineus will remain stable in the future, but also predicted increases in habitat suitability in the Western U.S., Venezuela, Brazil and Bolivia. Scenario 4.5 showed an increase in habitat suitability for R. sanguineus in tropical and subtropical regions in both 2050 and 2070. Habitat suitability is predicted to remain constant in moist broadleaf forests and deserts but is predicted to decrease in flooded grasslands and savannas. Using the high emissions SSP5-8.5 scenario, habitat suitability in tropical and subtropical coniferous forests and temperate grasslands, savannas, and shrublands was predicted to be constant in 2050. In 2070, however, habitat suitability was predicted to decrease in tropical and subtropical moist broadleaf forests and increase in tropical and subtropical dry broadleaf forests. Our findings suggest that the current and potential future geographic distributions can be used in evidence-based strategies in the design of control plans aimed at reducing the risk of exposure to zoonotic diseases transmitted by R. sanguineus.