Strong discrepancies between local temperature mapping and interpolated climatic grids in tropical mountainous agricultural landscapes

Spatiotemporal analysis of seasonal trends in land surface temperature within the distribution range of Moringa peregrina (Forssk.) in Southern and Southeastern Iran

Temperature fluctuations and related factors are among the main causes of climate change. Understanding the temporal and spatial variations in temperature can shed light on how species respond to climate change. Plants generally persist in suitable microclimates in response to environmental change; however, examining long-term temperature variations within a species' range can be challenging using field observations. Thermal remote sensing, on the other hand, provides multi-scale time-series data with good coverage and regularity to overcome the challenges associated with field observations in environmental monitoring. Although changes in land surface temperature (LST) affect climate, hydrological processes, land-atmosphere interactions, and ecological activities, this metric has not received much research attention. This study aimed to analyze changes in habitat suitability and microclimatic conditions for Moringa peregrina. Seasonal changes in LST within the distribution range of the species were also investigated. To this aim, mean seasonal LST was computed in Google Earth Engine using the daily MODIS/006/MYD13A2 product from 2003 to 2023. Subsequently, a binary habitat suitability map was created based on the true skill statistic (TSS). The Mann-Kendall test was used to analyze seasonal LST trends. Major trends in LST were quantified based on the z-score, and compatibility with habitat suitability was evaluated via GAP analysis and the Kappa index. Seasonal temperature trends were evaluated by comparing each season with the following season using binary comparison. Landforms at presence points were regarded as microclimates and the sensitivity of microclimates to LST was evaluated using two methods: Principal component analysis (PCA) was used to quantify seasonal LST heterogeneity and the random forest (RF) approach was used to evaluate the effect of environmental parameters on habitat suitability within microclimates. The Kappa index revealed a weak overlapping between suitable / unsuitable habitat and the surfaces affected by the trend of changes. Moreover, the suitable habitat of Moringa peregrina in spring, autumn and winter is spatially overlapped by areas that have shown an increasing LST trend, and the presence points have not experienced an increasing temperature trend only in the summer. The findings show that the analysis of seasonal trends in LST provides insights into the effect of LST on habitat suitability and the condition of vegetation. The current study clearly shows that seasonal changes have had a significant impact on the distribution and habitat suitability of M. peregrina, particularly during summer and winter. Improved habitat suitability and range expansion were observed throughout the year. The study also highlights the role of landforms in regulating temperature. Landforms such as local ridges with minimal temperature fluctuations and regions near the Oman Sea were identified as potential future habitats due to favorable humidity conditions.

Patterns of tropical forest understory temperatures

Temperature is a fundamental driver of species distribution and ecosystem functioning. Yet, our knowledge of the microclimatic conditions experienced by organisms inside tropical forests remains limited. This is because ecological studies often rely on coarse-gridded temperature estimates representing the conditions at 2 m height in an open-air environment (i.e., macroclimate). In this study, we present a high-resolution pantropical estimate of near-ground (15 cm above the surface) temperatures inside forests. We quantify diurnal and seasonal variability, thus revealing both spatial and temporal microclimate patterns. We find that on average, understory near-ground temperatures are 1.6 °C cooler than the open-air temperatures. The diurnal temperature range is on average 1.7 °C lower inside the forests, in comparison to open-air conditions. More importantly, we demonstrate a substantial spatial variability in the microclimate characteristics of tropical forests. This variability is regulated by a combination of large-scale climate conditions, vegetation structure and topography, and hence could not be captured by existing macroclimate grids. Our results thus contribute to quantifying the actual thermal ranges experienced by organisms inside tropical forests and provide new insights into how these limits may be affected by climate change and ecosystem disturbances.

Recognizing salinity threats in the climate crisis

Climate change is causing habitat salinity to transform at unprecedented rates across the globe. While much of the research on climate change has focused on rapid shifts in temperature, far less attention has focused on the effects of changes in environmental salinity. Consequently, predictive studies on the physiological, evolutionary, and migratory responses of organisms and populations to the threats of salinity change are relatively lacking. This omission represents a major oversight, given that salinity is among the most important factors that define biogeographic boundaries in aquatic habitats. In this perspective, we briefly touch on responses of organisms and populations to rapid changes in salinity occurring on contemporary time scales. We then discuss factors that might confer resilience to certain taxa, enabling them to survive rapid salinity shifts. Next, we consider approaches for predicting how geographic distributions will shift in response to salinity change. Finally, we identify additional data that are needed to make better predictions in the future. Future studies on climate change should account for the multiple environmental factors that are rapidly changing, especially habitat salinity.

Potential distribution of invasive crop pests under climate change: incorporating mitigation responses of insects into prediction models

Climate change facilitates biological invasions globally. Predicting potential distribution shifts of invasive crop pests under climate change is essential for global food security in the context of ongoing world population increase. However, existing predictions often omit the capacity of crop pests to mitigate the impacts of climate change by using microclimates, as well as through thermoregulation, life history variation and evolutionary responses. Microclimates provide refugia buffering climate extremes. Thermoregulation and life history variation can reduce the effects of diurnal and seasonal temperature variability. Evolutionary responses allow insects to adapt to long-term climate change. Neglecting these ecological processes may lead to overestimations in the negative impacts of climate change on invasive pests whereas in turn cause underestimations in their range expansions. To improve model predictions, we need to incorporate the fine-scale microclimates experienced by invasive crop pests and the mitigation responses of insects to climate change into species distribution models.

Low temperatures impact species distributions of jumping spiders across a desert elevational cline

Temperature is known to influence many aspects of organisms and is frequently linked to geographical species distributions. Despite the importance of a broad understanding of an animal's thermal biology, few studies incorporate more than one metric of thermal biology. Here we examined an elevational assemblage of Habronattus jumping spiders to measure different aspects of their thermal biology including thermal limits (CT_min, CT_max), thermal preference, V̇CO₂ as proxy for metabolic rate, locomotor behavior and warming tolerance. We used these data to test whether thermal biology helped explain how species were distributed across elevation. Habronattus had high CT_max values, which did not differ among species across the elevational gradient. The highest-elevation species had a lower CT_min than any other species. All species had a strong thermal preference around 37 °C. With respect to performance, one of the middle elevation species was significantly less temperature-sensitive in metabolic rate. Differences between species with respect to locomotion (jump distance) were likely driven by differences in mass, with no differences in thermal performance across elevation. We suggest that Habronattus distributions follow Brett's rule, a rule that predicts more geographical variation in cold tolerance than heat. Additionally, we suggest that physiological tolerances interact with biotic factors, particularly those related to courtship and mate choice to influence species distributions. Habronattus also had very high warming tolerance values (> 20 °C, on average). Taken together, these data suggest that Habronattus are resilient in the face of climate-change related shifts in temperature.

Canopy structure and topography jointly constrain the microclimate of human-modified tropical landscapes

Local-scale microclimatic conditions in forest understoreys play a key role in shaping the composition, diversity and function of these ecosystems. Consequently, understanding what drives variation in forest microclimate is critical to forecasting ecosystem responses to global change, particularly in the tropics where many species already operate close to their thermal limits and rapid land-use transformation is profoundly altering local environments. Yet our ability to characterize forest microclimate at ecologically meaningful scales remains limited, as understorey conditions cannot be directly measured from outside the canopy. To address this challenge, we established a network of microclimate sensors across a land-use intensity gradient spanning from old-growth forests to oil-palm plantations in Borneo. We then combined these observations with high-resolution airborne laser scanning data to characterize how topography and canopy structure shape variation in microclimate both locally and across the landscape. In the processes, we generated high-resolution microclimate surfaces spanning over 350 km² , which we used to explore the potential impacts of habitat degradation on forest regeneration under both current and future climate scenarios. We found that topography and vegetation structure were strong predictors of local microclimate, with elevation and terrain curvature primarily constraining daily mean temperatures and vapour pressure deficit (VPD), whereas canopy height had a clear dampening effect on microclimate extremes. This buffering effect was particularly pronounced on wind-exposed slopes but tended to saturate once canopy height exceeded 20 m-suggesting that despite intensive logging, secondary forests remain largely thermally buffered. Nonetheless, at a landscape-scale microclimate was highly heterogeneous, with maximum daily temperatures ranging between 24.2 and 37.2°C and VPD spanning two orders of magnitude. Based on this, we estimate that by the end of the century forest regeneration could be hampered in degraded secondary forests that characterize much of Borneo's lowlands if temperatures continue to rise following projected trends.

Growth responses to elevated temperatures and the importance of ontogenetic niche shifts in Bromeliaceae

Epiphytic bromeliads represent a major component of Neotropical forests, but the potential effect of climate change on these plants is unclear. We investigated whether and how bromeliads are affected by the predicted 3°C temperature rise by the end of the century. We conducted growth experiments with 17 epiphytic bromeliad species at different temperatures to determine their fundamental thermal niches. By comparing those with niches for germination, we tested whether ontogenetic niche shift or niche contraction occurs in Bromeliaceae. Applying a classical growth analysis, we assessed the relative importance of the underlying growth components on interspecific variations in growth. Members of two bromeliad subfamilies differed in their response to elevated temperatures: Tillandsioideae may be negatively affected, whereas Bromelioideae moved closer to their thermal optimum. Across different ontogenetic stages, thermal niche characteristics revealed both niche shift and niche contraction. Interspecific variation in growth was driven almost exclusively by net assimilation rate at all temperatures. We conclude that the vulnerability of tropical plants to a future increase in temperature may be more variable than suggested by previous studies. We emphasize the importance of assessing niche breadth over multiple life stages and the need for better microclimatic data to link laboratory data with field conditions.

Microclimate Data Improve Predictions of Insect Abundance Models Based on Calibrated Spatiotemporal Temperatures

A large body of literature has recently recognized the role of microclimates in controlling the physiology and ecology of species, yet the relevance of fine-scale climatic data for modeling species performance and distribution remains a matter of debate. Using a 6-year monitoring of three potato moth species, major crop pests in the tropical Andes, we asked whether the spatiotemporal resolution of temperature data affect the predictions of models of moth performance and distribution. For this, we used three different climatic data sets: (i) the WorldClim dataset (global dataset), (ii) air temperature recorded using data loggers (weather station dataset), and (iii) air crop canopy temperature (microclimate dataset). We developed a statistical procedure to calibrate all datasets to monthly and yearly variation in temperatures, while keeping both spatial and temporal variances (air monthly temperature at 1 km² for the WorldClim dataset, air hourly temperature for the weather station, and air minute temperature over 250 m radius disks for the microclimate dataset). Then, we computed pest performances based on these three datasets. Results for temperature ranging from 9 to 11°C revealed discrepancies in the simulation outputs in both survival and development rates depending on the spatiotemporal resolution of the temperature dataset. Temperature and simulated pest performances were then combined into multiple linear regression models to compare predicted vs. field data. We used an additional set of study sites to test the ability of the results of our model to be extrapolated over larger scales. Results showed that the model implemented with microclimatic data best predicted observed pest abundances for our study sites, but was less accurate than the global dataset model when performed at larger scales. Our simulations therefore stress the importance to consider different temperature datasets depending on the issue to be solved in order to accurately predict species abundances. In conclusion, keeping in mind that the mismatch between the size of organisms and the scale at which climate data are collected and modeled remains a key issue, temperature dataset selection should be balanced by the desired output spatiotemporal scale for better predicting pest dynamics and developing efficient pest management strategies.

Beyond the Mean: Biological Impacts of Cryptic Temperature Change

Studies have typically used shifts in mean temperatures to make predictions about the biotic impacts of climate change. Though shifts in mean temperatures correlate with changes in phenology and distributions, other hidden, or cryptic, changes in temperature, such as temperature variation and extreme temperatures, could pose greater risks to species and ecological communities. Yet, these cryptic temperature changes have received relatively little attention because mean temperatures are readily available and the organism-appropriate temperature response is often elusive. An alternative to using mean temperatures is to view organisms as physiological filters of hourly temperature data. We explored three classes of physiological filters: (1) nonlinear thermal responses using performance curves of insect fitness, (2) cumulative thermal effects using degree-day models for corn emergence, and (3) threshold temperature effects using critical thermal maxima and minima for diverse ectotherms. For all three physiological filters, we determined the change in biological impacts of hourly temperature data from a standard reference period (1961-90) to a current period (2005-10). We then examined how well mean temperature changes during the same time period predicted the biotic impacts we determined from hourly temperature data. In all cases, mean temperature alone provided poor predictions of the impacts of climate change. These results suggest that incorporating high frequency temperature data can provide better predictions for how species will respond to temperature change.