ForestClim-Bioclimatic variables for microclimate temperatures of European forests

Artificial Intelligence for Climate Change Biology: From Data Collection to Predictions

In the era of big data, ecological research is experiencing a transformative shift, yet big-data advancements in thermal ecology and the study of animal responses to climate conditions remain limited. This review discusses how big data analytics and artificial intelligence (AI) can significantly enhance our understanding of microclimates and animal behaviors under changing climatic conditions. We explore AI's potential to refine microclimate models and analyze data from advanced sensors and camera technologies, which capture detailed, high-resolution information. This integration can allow researchers to dissect complex ecological and physiological processes with unprecedented precision. We describe how AI can enhance microclimate modeling through improved bias correction and downscaling techniques, providing more accurate estimates of the conditions that animals face under various climate scenarios. Additionally, we explore AI's capabilities in tracking animal responses to these conditions, particularly through innovative classification models that utilize sensors such as accelerometers and acoustic loggers. For example, the widespread usage of camera traps can benefit from AI-driven image classification models to accurately identify thermoregulatory responses, such as shade usage and panting. AI is therefore instrumental in monitoring how animals interact with their environments, offering vital insights into their adaptive behaviors. Finally, we discuss how these advanced data-driven approaches can inform and enhance conservation strategies. In particular, detailed mapping of microhabitats essential for species survival under adverse conditions can guide the design of climate-resilient conservation and restoration programs that prioritize habitat features crucial for biodiversity resilience. In conclusion, the convergence of AI, big data, and ecological science heralds a new era of precision conservation, essential for addressing the global environmental challenges of the 21st century.

Tracking effects of extreme drought on coniferous forests from space using dynamic habitat indices

Terrestrial ecosystems such as coniferous forests in Central Europe are experiencing changes in health status following extreme droughts compounding with severe heat waves. The increasing temporal resolution and spatial coverage of earth observation data offer new opportunities to assess these dynamics. Dense time-series of optical satellite data allow for computing Dynamic Habitat Indices (DHIs), which have been predominantly used in biodiversity studies. However, DHIs cover three aspects of vegetation changes that could be affected by drought: annual productivity, minimum cover, and seasonality. Here, we evaluate the health status of coniferous forests in the federal state of Hesse in Germany over the period 2017-2020 including the severe drought year of 2018 using DHIs based on the Normalized Difference Vegetation Index (NDVI) for drought assessment. To identify the most important variables affecting coniferous forest die-off, a series of environmental variables together with the three DHIs components were used in a logistic regression (LR) model. Each DHI component changed significantly across non-damaged and damaged sites in all years (p-value 0.05). When comparing 2017 to 2019, DHI-based annual productivity decreased and seasonality increased. Most importantly, none of the DHI components had reached pre-drought conditions, which likely indicates a change in ecosystem functioning. We also identified spatially explicit areas highly affected by drought. The LR model revealed that in addition to common environmental parameters related to temperature, precipitation, and elevation, DHI components were the most important factors explaining the health status. Our analysis demonstrates the potential of DHIs to capture the effect of drought events on Central European coniferous forest ecosystems. Since the spaceborne data are available at the global level, this approach can be applied to track the dynamics of ecosystem conditions in other regions, at larger spatial scales, and for other Land Use/Land Cover types.

The interior climate and its microclimatic variation of temperate forests in Northern Patagonia, Argentina

Knowledge on mesoclimatic zonation and microclimatic variations within mountain forest ecosystems is crucial for understanding regional species turnover and effects of climate change on these systems. The temperate mountain forests in the Andean region of South America are among the largest and contiguous natural deciduous forest areas in the world. Due to their pronounced disturbance regime and different successional stages, a climatic zonation combined with the characterisation of its microclimatic variation is important to identify thresholds of species occurrences.We used micro-loggers to measure air temperature and relative humidity for one year at 40 measurement locations along longitudinal and elevation gradients in mountain forests in Northern Patagonia, Argentina. Our results unveil mesoclimatic patterns within these forests characterised by variations in temperature and vapour pressure deficit along the elevational gradient in general, but also at different times of the year. For example, Austrocedrus chilensis and Nothofagus dombeyi forests differed mainly by temperature and its diurnal range in the warmest months of the year. Also, differences between forest stands and gaps were more pronounced in the warmest months of the year and at lower elevations, with up to 2.5 K higher temperatures in the second half of the day in gaps. We found clear indications that shrubland of Nothofagus antarctica representing a successional stage after disturbances alters the mesoclimatic pattern, favouring forest fire ignition. Such mesoclimatic variations have a major influence on tree species turnover and ecological processes within these forest ecosystems.The findings contribute to our understanding of the complex interplay between topography, climate, and vegetation in shaping the spatial patterns of species occurrences.

Plant canopies promote climatic disequilibrium in Mediterranean recruit communities

Current rates of climate change are exceeding the capacity of many plant species to track climate, thus leading communities to be in disequilibrium with climatic conditions. Plant canopies can contribute to this disequilibrium by buffering macro-climatic conditions and sheltering poorly adapted species to the oncoming climate, particularly in their recruitment stages. Here we analyse differences in climatic disequilibrium between understorey and open ground woody plant recruits in 28 localities, covering more than 100,000 m2 , across an elevation range embedding temperature and aridity gradients in the southern Iberian Peninsula. This study demonstrates higher climatic disequilibrium under canopies compared with open ground, supporting that plant canopies would affect future community climatic lags by allowing the recruitment of less arid-adapted species in warm and dry conditions, but also it endorse that canopies could favour warm-adapted species in extremely cold environments as mountain tops, thus pre-adapting communities living in these habitats to climate change.

Cliff-edge forests: Xerothermic hotspots of local biodiversity and models for future climate change

Cliffs are remarkable environments that enable the existence of microclimates. These small, isolated sites, decoupled from the regional macroclimate, play a significant role in maintaining species biodiversity, particularly in topographically homogeneous landscapes. Our study investigated the microclimate of south-exposed forests situated at the edge of sandstone cliffs in the western part of the North Alpine Foreland Basin in Switzerland and its role in local forest community composition. Using direct measurements from data loggers, as well as vegetation analyses, it was possible to quantify the microclimate of the cliff-edge forests and compare it with that of the surrounding forests. Our results highlighted the significant xerothermic and more variable nature of the cliff-edge forest microclimate, with a mean soil temperature up to 3.72°C warmer in the summer, higher annual (+28%) and daily (+250%) amplitudes of soil temperature, which frequently expose vegetation to extreme temperatures, and an 83% higher soil drying rate. These differences have a distinct influence on forest communities: cliff-edge forests are significantly different from surrounding forests. The site particularities of cliff edges support the presence of locally rare species and forest types, particularly of Scots pine. Cliff edges must therefore be considered microrefugia with a high conservation value for both xerothermic species and flora adapted to more continental climates. Moreover, the microclimate of cliff-edge forests could resemble the future climate in many ways. We argue that these small areas, which are already experiencing the future climate, can be seen as natural laboratories to better answer the following question: what will our forests look like in a few decades with accelerated climate change?

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.

Forest herb species with similar European geographic ranges may respond differently to climate change

Many phenological studies have shown that spring geophytes are very sensitive to climate change, responding by shifting flowering and fruiting dates. However, there is a gap in knowledge about climatic drivers of their distributions and range shifts under climate change. Here we aimed to estimate climate niche shifts for four widely distributed and common geophytes of the nemoral zone of Europe (Anemone nemorosa, Anemone ranunculoides, Convallaria majalis and Maianthemum bifolium) and to assess the threat level under various climate change scenarios. Using MaxEnt species distribution models and future climate change scenarios we found that the precipitation of the warmest quarter was the most important factor shaping their ranges. All species studied will experience more loss in the 2061-2080 period than in 2041-2060, and under more pessimistic scenarios. M. bifolium will experience the highest loss, followed by A. nemorosa, A. ranunculoides, and the smallest for C. majalis. A. ranunculoides will gain the most, while M. bifolium will have the smallest potential range expansion. Studied species may respond differently to climate change despite similar current distributions and climatic variables affecting their potential distribution. Even slight differences in climatic niches could reduce the overlap of future ranges compared to present. We expect that due to high dependence on the warmest quarter precipitation, summer droughts in the future may be particularly severe for species that prefer moist soils. The lack of adaptation to long-distance migration and limited availability of appropriate soils may limit their migration and lead to a decline in biodiversity and changes in European forests.

Microclimate reveals the true thermal niche of forest plant species

Species distributions are conventionally modelled using coarse-grained macroclimate data measured in open areas, potentially leading to biased predictions since most terrestrial species reside in the shade of trees. For forest plant species across Europe, we compared conventional macroclimate-based species distribution models (SDMs) with models corrected for forest microclimate buffering. We show that microclimate-based SDMs at high spatial resolution outperformed models using macroclimate and microclimate data at coarser resolution. Additionally, macroclimate-based models introduced a systematic bias in modelled species response curves, which could result in erroneous range shift predictions. Critically important for conservation science, these models were unable to identify warm and cold refugia at the range edges of species distributions. Our study emphasizes the crucial role of microclimate data when SDMs are used to gain insights into biodiversity conservation in the face of climate change, particularly given the growing policy and management focus on the conservation of refugia worldwide.