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In response to the pressing challenges of the ongoing biodiversity crisis, the protection of endangered species and their habitats, as well as the monitoring of invasive species are crucial. Habitat suitability modeling (HSM) is often treated as the silver bullet to address these challenges, commonly relying on generic variables sourced from widely available datasets. However, for species with high habitat requirements, or for modeling the suitability of habitats within the geographic range of a species, variables at a coarse level of detail may fall short. Consequently, there is potential value in considering the incorporation of more targeted data, which may extend beyond readily available land cover and climate datasets. In this study, we investigate the impact of incorporating targeted land cover variables (specifically tree species composition) and vertical structure information (derived from LiDAR data) on HSM outcomes for three forest specialist bat species (Barbastella barbastellus, Myotis bechsteinii, and Plecotus auritus) in Rhineland‐Palatinate, Germany, compared to commonly utilized environmental variables, such as generic land‐cover classifications (e.g., Corine Land Cover) and climate variables (e.g., Bioclim). The integration of targeted variables enhanced the performance of habitat suitability models for all three bat species. Furthermore, our results showed a high difference in the distribution maps that resulted from using different levels of detail in environmental variables. This underscores the importance of making the effort to generate the appropriate variables, rather than simply relying on commonly used ones, and the necessity of exercising caution when using habitat models as a tool to inform conservation strategies and spatial planning efforts. [ABSTRACT FROM AUTHOR]

Our understanding of how biotic interactions influence animal community assembly is largely restricted to local systems due to the difficulty of obtaining ecologically meaningful assemblage data across large spatial extents. Here, we used thousands of spatio‐phenologically high‐resolution assemblages across three distinct European regions together with a functional diversity approach to understand community assembly of dragonflies and damselflies (Odonata), an insect group characterized by a pronounced competitive reproductive biology. We found that adult dragonfly, but not damselfly, assemblages were consistently composed of species morphologically more different than expected by chance based on the traits that enhance their interspecific reproductive encounters. These results provide consistent evidence for the role of competition in the assembly of animal communities, which we interpret is most likely caused by the territorial reproductive biology of dragonflies. Support for competition varied both spatially and seasonally following theoretical expectations, as it was strongest in locations and seasonal moments with low thermal stress (i.e. warm conditions) and high niche packing. Our study illustrates how spatio‐temporal diversity patterns arise from variation in assembly processes. [ABSTRACT FROM AUTHOR]

Ecosystem functions and services are severely threatened by unprecedented global loss in biodiversity. To counteract these trends, it is essential to develop systems to monitor changes in biodiversity for planning, evaluating, and implementing conservation and mitigation actions. However, the implementation of monitoring systems suffers from a trade‐off between grain (i.e., the level of detail), extent (i.e., the number of study sites), and temporal repetition. Here, we present an applied and realized networked sensor system for integrated biodiversity monitoring in the Nature 4.0 project as a solution to these challenges, which considers plants and animals not only as targets of investigation, but also as parts of the modular sensor network by carrying sensors. Our networked sensor system consists of three main closely interlinked components with a modular structure: sensors, data transmission, and data storage, which are integrated into pipelines for automated biodiversity monitoring. We present our own real‐world examples of applications, share our experiences in operating them, and provide our collected open data. Our flexible, low‐cost, and open‐source solutions can be applied for monitoring individual and multiple terrestrial plants and animals as well as their interactions. Ultimately, our system can also be applied to area‐wide ecosystem mapping tasks, thereby providing an exemplary cost‐efficient and powerful solution for biodiversity monitoring. Building upon our experiences in the Nature 4.0 project, we identified ten key challenges that need to be addressed to better understand and counteract the ongoing loss of biodiversity using networked sensor systems. To tackle these challenges, interdisciplinary collaboration, additional research, and practical solutions are necessary to enhance the capability and applicability of networked sensor systems for researchers and practitioners, ultimately further helping to ensure the sustainable management of ecosystems and the provision of ecosystem services. [ABSTRACT FROM AUTHOR]

The natural resources of Ethiopian high-altitude ecosystems are commonly perceived as increasingly threatened by devastating land-use practices owing to decreasing lowland resources. Quantified time-series data of the course of land-use cover changes are still needed. Very-high-resolution digital data on the historical landscape over recent decades are needed to determine the impacts of changes in afro-alpine ecosystems. However, digital elevation models (DEMs) and orthomosaics do not exist for most afro-alpine ecosystems of Africa. We processed the only available and oldest historical aerial photographs for Ethiopia and any afro-alpine ecosystem. Here, we provide a DEM and an orthomosaic image for the years 1967 and 1984 for the Bale Mountains in Ethiopia, which comprise the largest afro-alpine ecosystem in Africa. We used 298 historical aerial photographs captured in 1967 and 1984 for generating DEMs and orthomosaics with a structure-from-motion multi-view stereo photogrammetry workflow along an elevation gradient from 977 to 4377 m above sea level (a.s.l.) at very high spatial resolutions of 0.84 m and 0.98 m for the years 1967 and 1984, respectively. The structure-from-motion multi-view stereo photogrammetry workflow, employed with Agisoft Metashape, represents a modern approach that combines computer vision and photogrammetry. This method proves useful for reconstructing DEMs and orthomosaics from historical aerial photographs, with a focus on high spatial resolution. To validate the accuracy of the reconstructed DEMs, ground control points gathered through GPS measurements were used, resulting in root mean square error (RMSE) values of 3.55 m for the year 1967 and 3.44 m for the year 1984. Our datasets can be used by researchers and policymakers for watershed management, as the area provides water for more than 30 million people, landscape management, detailed mapping, and analysis of geological and archaeological features as well as natural resources, analyses of geomorphological processes, and biodiversity research. All the datasets are available online at 10.5281/zenodo.7271617 (Muhammed et al., 2022a) for all the inputs used and at 10.5281/zenodo.7269999 (Muhammed et al., 2022b) for the results obtained (very-high-resolution DEMs and orthomosaics) for both the years 1967 and 1984. [ABSTRACT FROM AUTHOR]

Subterranean animals act as ecosystem engineers, for example, through soil perturbation and herbivory, shaping their environments worldwide. As the occurrence of animals is often linked to above‐ground features such as plant species composition or landscape textures, satellite‐based remote sensing approaches can be used to predict the distribution of subterranean species. Here, we combine in‐situ collected vegetation composition data with remotely sensed data to improve the prediction of a subterranean species across a large spatial scale. We compared three machine learning‐based modeling strategies, including field and satellite‐based remote sensing data to different extents, in order to predict the distribution of the subterranean giant root‐rat GRR, Tachyoryctes macrocephalus, an endangered rodent species endemic to the Bale Mountains in southeast Ethiopia. We included no, some and extensive fieldwork data in the modeling to test how these data improved prediction quality. We found prediction quality to be particularly dependent on the spatial coverage of the training data. Species distributions were best predicted by using texture metrics and eyeball‐selected data points of landscape marks created by the GRR. Vegetation composition as a predictor showed the lowest contribution to model performance and lacked spatial accuracy. Our results suggest that the time‐consuming collection of vegetation data in the field is not necessarily required for the prediction of subterranean species that leave traceable above‐ground landscape marks like the GRR. Instead, remotely sensed and spatially eyeball‐selected presence data of subterranean species could profoundly enhance predictions. The usage of remote sensing‐derived texture metrics has great potential for improving the distribution modeling of subterranean species, especially in arid ecosystems. [ABSTRACT FROM AUTHOR]

The Himalayas and the Hengduan Mountains of southwest China are hotspots of both climatic and species diversity. Yet, the distribution patterns of semi‐arid plant communities that have arisen throughout the region's complex uplift history remain insufficiently understood. In particular, the striking disjunctions of plants associated with dry river valleys that solely occur on the eastern and western ends of the Himalayan arc, but are absent in between, lack a sound explanation. Here we aim to disentangle the more recent environmental drivers behind the disjunction of the semi‐woody shrub Rumex hastatus found in dry river valleys of the western Himalayas and the Hengduan Mountains. We used ecological niche modeling and enhanced random forest parameterizations (down‐sampling) to infer suitable and unsuitable habitats within the study area during the last glacial maximum, under present climate conditions, and under four future climate scenarios. Annual and seasonal precipitation contributed the strongest to the discrimination between occurrences and the distribution gap, with the latter showing much higher rainfall amounts. The gap was also characterized by low overall habitat suitability, whereas occurrence probabilities in dry river valleys inhabited by R. hastatus were very high. However, some suitable but isolated habitats within the gap were detected in Bhutan and the southeastern Tibetan Plateau. The identified distribution gap was consistent in all simulated scenarios from the last glacial maximum to the near future. Our results suggest that the South Asian summer monsoon system acts as a persistent ecological barrier maintaining the disjunct distribution of dry river valley‐dwelling plants in the western Himalayas and the Hengduan Mountains. [ABSTRACT FROM AUTHOR]

Sexual dimorphism is typically thought to result from sexual selection for elaborated male traits, as proposed by Darwin. However, natural selection could reduce expression of elaborated traits in females, as proposed by Wallace. Darwin and Wallace debated the origins of dichromatism in birds and butterflies, and although evidence in birds is roughly equal, if not in favor of Wallace's model, butterflies lack a similar scale of study. Here, we present a large‐scale comparative phylogenetic analysis of the evolution of butterfly coloration, using all European non‐hesperiid butterfly species (n = 369). We modeled evolutionary changes in coloration for each species and sex along their phylogeny, thereby estimating the rate and direction of evolution in three‐dimensional color space using a novel implementation of phylogenetic ridge regression. We show that male coloration evolved faster than female coloration, especially in strongly dichromatic clades, with male contribution to changes in dichromatism roughly twice that of females. These patterns are consistent with a classic Darwinian model of dichromatism via sexual selection on male coloration, suggesting this model was the dominant driver of dichromatism in European butterflies. [ABSTRACT FROM AUTHOR]

The body size of an animal is probably its most important functional trait. For arthropods, environmental drivers of body size variation are still poorly documented and understood, especially in tropical regions. We use a unique dataset for two species‐rich, phylogenetically independent moth taxa (Lepidoptera: Geometridae; Arctiinae), collected along an extensive tropical elevational gradient in Costa Rica, to investigate the correlates and possible causes of body‐size variation. We studied 15 047 specimens (794 species) of Geometridae and 4167 specimens (308 species) of Arctiinae to test the following hypotheses: 1) body size increases with decreasing ambient temperature, as predicted by the temperature–size rule; 2) body size increases with increasing rainfall and primary productivity, as predicted from considerations of starvation resistance; and 3) body size scales allometrically with wing area, as elevation increases, such that wing loading (the ratio of body size to wing area) decreases with increasing elevation to compensate for lower air density. To test these hypotheses, we examined forewing length as a proxy for body size in relation to ambient temperature, rainfall, vegetation index and elevation as explanatory variables in linear and polynomial spatial regression models. We analysed our data separately for males and females using two principal approaches: mean forewing length of species at each site, and mean forewing length of complete local assemblages, weighted by abundance. Body size consistently increased with elevation in both taxa, both approaches, both sexes, and also within species. Temperature was the best predictor for this pattern (–0.98 < r < –0.74), whereas body size was uncorrelated or weakly correlated with rainfall and enhanced vegetation index. Wing loading increased with elevation. Our results support the temperature–size rule as an important mechanism for body size variation in arthropods along tropical elevational gradients, whereas starvation resistance and optimization of flight mechanics seem to be of minor importance. [ABSTRACT FROM AUTHOR]

We investigated the effects of contemporary and historical factors on the spatial variation of European dragonfly diversity. Specifically, we tested to what extent patterns of endemism and phylogenetic diversity of European dragonfly assemblages are structured by 1) phylogenetic conservatism of thermal adaptations and 2) differences in the ability of post‐glacial recolonization by species adapted to running waters (lotic) and still waters (lentic). We investigated patterns of dragonfly diversity using digital distribution maps and a phylogeny of 122 European dragonfly species, which we constructed by combining taxonomic and molecular data. We calculated total taxonomic distinctiveness and mean pairwise distances across 4192 50 × 50 km equal‐area grid cells as measures of phylogenetic diversity. We compared species richness with corrected weighted endemism and standardized effect sizes of mean pairwise distances or residuals of total taxonomic distinctiveness to identify areas with higher or lower phylogenetic diversity than expected by chance. Broken‐line regression was used to detect breakpoints in diversity–latitude relationships. Dragonfly species richness peaked in central Europe, whereas endemism and phylogenetic diversity decreased from warm areas in the south‐west to cold areas in the north‐east and with an increasing proportion of lentic species. Except for species richness, all measures of diversity were consistently higher in formerly unglaciated areas south of the 0°C isotherm during the Last Glacial Maximum than in formerly glaciated areas. These results indicate that the distributions of dragonfly species in Europe were shaped by both phylogenetic conservatism of thermal adaptations and differences between lentic and lotic species in the ability of post‐glacial recolonization/dispersal in concert with the climatic history of the continent. The complex diversity patterns of European dragonflies provide an example of how integrating climatic and evolutionary history with contemporary ecological data can improve our understanding of the processes driving the geographical variation of biological diversity. [ABSTRACT FROM AUTHOR]