Communities of insects around the world consist of unique sets of species that have evolved under different historical processes of assembly and lineage diversification. Whole-community phylogenetics can partition the shared and uniquely derived evolutionary history at sites. We used mitochondrial genome sequences of >1000 species each from two assemblages of Coleoptera (beetles) in distantly situated tropical lowland rainforest of Malaysia and Panama for phylogenetic reconstruction and community ecological analysis. Assemblages were entirely distinct at species level but were surprisingly similar at family level in their overall composition and relative species richness, despite a high degree of phylogenetic clustering that implied independent evolution. Inclusion of species poor lineages reduced the level of community clustering in parallel in both sites, indicating lineage-specific factors to determine species richness and their effect on local community composition. In conclusion, relative species richness in local community composition and global clade sizes are connected, in part due to biotic exchange in deep time, but more likely because of intrinsic rates of diversification unique to each clade (family), thus making assembly composition more predictable, i.e. the ‘evolutionary tape’ would be similar wherever a new assemblage of tropical-forest Coleoptera arises.

Understanding how geographic range limits are shaped is a central and challenging question in ecology that has become particularly critical in the context of global environmental changes. While such limits are often studied for resident or breeding species, range limits are equally important for migratory species in winter when population regulation may occur due to limited resources in the non-breeding season. A central hypothesis in several theories for range limitations is that the density, fitness and performance of individuals decrease towards the edge of the range as organisms become maladapted when approaching the limit of their environmental tolerance (‘Abundant-centre Hypothesis’). Energy is a critical resource, especially in winter when environmental conditions deteriorate, and this hypothesis predicts that high energy expenditure (low performance) at the range limit would lead to rapidly dwindling body mass and reduced fitness. We investigated this hypothesis in an Arctic-breeding seabird wintering in the North-Atlantic, the black-legged kittiwake (Rissa tridactyla). From 2008 to 2019, we tracked 117 adult kittiwakes (n=176 tracks) with geolocation devices and saltwater immersion sensors to estimate the migratory strategies, time-activity budget and energy expenditure of individuals during winter, and estimated their reproductive success after their return to the colony during summer. Population density was indeed higher towards the center of the range. However, contrary to the predictions, the energy expenditure of individuals was higher at the centre of the range and decreased towards the edge. In contrast, there were no spatial differences in the reproductive success of individuals wintering at the centre versus at the edge of their range. We conclude that performance and fitness did not increase towards the centre of the wintering range, implying that although resource acquisition was likely higher at the abundant centre, energy expenditure was also higher, so that individual fitness was constant across the winter range.

The study of species environmental niches underpins numerous questions in ecology and evolutionary and has increasing relevance in a rapidly changing world. Environmental niches, characterized from observations of organisms, inform about a species’ specialization in multivariate environment space and help assess their exposure and sensitivity to a changing climate. Environmental niches are also the central concept behind the species distribution models (SDMs) which assess and predict the geographic variation in environmental suitability. Despite the clear role of past evolutionary processes in driving contemporary biodiversity distribution, the assessment of multivariate or n-dimensional (where n is the number of environmental axes) niches in a phylogenetic framework has remained limited and constrained by restrictive assumptions. This hampers important existing and emerging applications, such as assessments of niche conservatism, estimates of species’ adaptive potential under changing climates, and prediction of niches in less-studied parts of the tree of life. Here we introduce a framework that extends SDMs to estimate n-dimensional environmental niches jointly with underlying evolutionary processes. Specifically, we fit the relationship between niche distance and phylogenetic distance as a latent Gaussian Process across all species in a clade. We demonstrate mathematically how the parameters of the Gaussian Process can be linked to existing traditional evolutionary models. Simulations indicate that the approach successfully recovers evolutionary parameters. Applied to two clades of hummingbirds, the presented joint framework uncovers the relationships among species’ niches in phylogenetic space and supports the quantification and hypothesis testing of niche evolution. A key advantage of the presented framework is its joint estimation of the evolutionary process alongside niches directly from species observations with uncertainty propagated to evolutionary model parameters. The proposed approach has the potential to increase the robustness of inference about niche evolution and improve understanding of how the processes of niche formation and evolution interact.

The relative importance of abiotic and biotic factors in determining species distributions has long been of interest to ecologists but is often difficult to assess due to the lack of spatially and temporally robust occurrence records. Furthermore, locating places where potentially highly competitive species co-occur may be challenging but would provide critical knowledge into the effects of competition on species ranges. We built species distribution models for two closely related species of small mammals (Neotoma) that are largely parapatric along mountainsides throughout the Great Basin Desert using extensive modern occurrence records. We hindcasted these models to the mid-Holocene to compare the response of each species to dramatic climatic change and used paleontological records to validate our models. Model results showed species co-occurrence at mid-elevations along select mountain ranges in this region. We confirmed our model results with fine-scale field surveys in a single mountain range containing one of the most extensive survey datasets across an elevational gradient in the Great Basin. We found close alignment of both species’ realized distributions to their respective abiotic species distribution model predictions, despite the presence of the congener, indicating that climate may be more influential than competition in shaping distribution at the scale of a single mountain range. Our models also predict differential species responses to historic climate change, leading to reduced probability of species interactions during warmer and dryer climatic conditions. Our results emphasize the utility of examining species distributions with regards to both abiotic variables and species interactions and at various spatial scales to make inferences about the mechanisms underlying distributional limits.

Glaciers are retreating worldwide at an ever-increasing rate, exposing new ice-free areas to ecological succession. This process leads to changes in biodiversity and potentially to species interactions. However, we still have a limited understanding of how glacier retreat influences species interaction networks, particularly the structure and robustness of mutualistic networks. After reconstructing plant--pollinator networks along a glacier foreland, we address the effects of glacier retreat on pollination network structure and robustness. Our results show that the prevalence of different network motifs changes over space-time. With glacier retreat, pollination networks shift from being highly connected with specialist interactions to loosely connected with generalist interactions. Furthermore, network robustness decreased with glacier retreat. Despite the turnover of plant species, we find that structural roles played by different plant species stay constant over space-time. Our findings suggest that glacier retreat pushes pollination networks towards a loss of specialist interactions and low robustness, leading to increased fragility in the long term. Monitoring network motifs may provide valuable insights into the ability of novel pollination networks to withstand disturbances and preserve functionality in the face of glacier extinction.

Species distribution modeling is increasingly used to describe and anticipate consequences of a warming ocean. These models often identify statistical associations between distribution and environmental conditions such as temperature and oxygen, but rarely consider the mechanisms by which these environmental variables affect metabolism. Oxygen and temperature jointly govern the rate of oxygen supply to oxygen demand, and theory predicts thresholds in these rates below which species population densities are diminished. However, parameterizing models with this joint dependence is challenging because of the paucity of experimental work for most species, and the limited applicability of experimental findings in situ. Here we ask whether the joint effects of temperature and oxygen can be reliably inferred from species distribution observations in the field, using the U.S. Pacific Coast as a model system. Through simulation testing, we found that our statistical model—which adapted the metabolic index to jointly consider oxygen and temperature by applying an Arrhenius equation and used a non-linear threshold function to link the index to fish distribution—could not precisely estimate the parameters due to inherent features of the distribution data. However, the model reliably estimated an overall metabolic index threshold effect, and provided a better fit to sablefish (Anoplopoma fimbria) spatial distribution than previously used models. This mechanistic approach may improve predictions of species distribution, even in novel environmental conditions. Further efforts to combine insights from mechanistic responses and realized species distributions will improve forecasts of species’ responses to future environmental changes.

Anticipating the effects of global change on biodiversity have become a global challenge that requires new methods. Approaches like Species Distribution Models have important limitations which have fuelled the development of Joint Species Distribution Models (JSDM). However, JSDMs rely on community data from structured surveys. Nonetheless, no assessment on the suitability of JSDMs to work with unstructured data from opportunistic databases has been performed. Here we test JSDMs performance when using opportunistic databases. Using artificial data that mimic the limitations of such databases by subsampling complete cooccurrence matrices, we analysed how the completeness of opportunistic databases affects JSDMs in terms of (a) the role of independent variables on species occurrence, (b) residual species cooccurrence (as a proxy of biotic interactions), and (c) species distributions. Moreover, we illustrate how to evaluate completeness at the pixel level of real data with a study case of forest tree species in Europe, and evaluated the role of data completeness in model estimation. Our results with artificial data demonstrate that decreasing the retention percentage increase false negatives and negative cooccurrence probabilities, leading to loss of ecological information. However, JSDMs support different levels of degradation depending on the aspect of the model being considered. Models with 50 % of missing data are valid for estimating species niches and distribution, but interaction matrices would require more complete databases with at least 75% of data retention. Furthermore, in most cases JSDMs predict the original data even better than the data from subsampled matrices, both from testing and training subsets. All those findings were confirmed in the analysis with the real study case. We conclude that opportunistic databases are a valuable data source for JSDMs, but their use require a previous analysis of data completeness for the target taxa in the study area at the spatial resolution of interest.

In broad outlines, the results of our long-term (1977-2017) study on dynamics of small rodents on the Finnmarksvidda tundra conformed to the prediction the Exploitation Ecosystems Hypothesis (EEH). Productive shrublands supported boreal-type vole cycles, where vole declines were accompanied by intense predator activity. Conversely, the unproductive high tundra was characterized by irregular outbreaks of Norwegian lemmings (Lemmus lemmus), ending in abrupt winter crashes and in profound destruction of perennially available plants. In contrast to the Siberian and North American tundra, densities of avian predators where chronically low. Lemmings thus increased unhinged during peak summers. As proposed by Kalela, young adults responded to the discrepancy between numbers and resource supply by migrating. Tens of young lemmings were trapped on a small island in the middle of Iešjávri, a 10 by 8 km tundra lake, and many lemmings were seen starting to swim across the lake. The risky crossings of a major water barrier indicated that these lemmings were on a long journey. We propose that the unique dynamics and traits of Norwegian lemmings are a legacy of the Last Glacial Maximum (LGM), which Norwegian lemmings survived in a small, extremely isolated refugium archipelago, unlikely to have been exploited by avian predators specialized to Lemmus spp. On the basis of the results summarized above and earlier simulation studies, we argue that pure lemming-vegetation interactions create extremely violent, chaotic density oscillations, where periods with low lemming numbers are long, and high lemming densities are only achieved late in peak summers. When Norwegian lemmings lost their specialized avian predators during LGM, the Fennoscandian tundra shifted to the alternative state of pure lemming-plant oscillations, characterized by autumnal peaks and long periods of low lemming density, which is thus resistant to the invasion of avian predators adapted to exploit Lemmus spp.

not-yet-known not-yet-known not-yet-known unknown Projecting how climate change will reshape global patterns of forest carbon storage is paramount to investigate the future of the global carbon cycle. Advances in machine learning and the proliferation of remote-sensing missions have stimulated the development of statistical models for the estimation of carbon storage on a global scale. However, existing models present two major limitations. First, they are not suitable for forecasting because they are trained on variables that cannot be projected. Second, they are based on large numbers of predictors, which hinders the interpretability and explainability of their results from a biological and ecological perspective. In this manuscript, we present a machine learning model for the global mapping of potential Aboveground Biomass Density that overcomes the above mentioned limitations. On the one hand, our model is based exclusively on bioclimatic variables and is therefore suitable for forecasting and interpretable from a biological perspective. On the other hand, we calibrated our model with a state-of-the-art predictor selection process to identify the optimal subset of predictors for the maximization of model accuracy. We found that a minimal model based solely on four bioclimatic variables performed the best. Furthermore, our model reproduces field measurements from experimental forest plots equally well than a state-of-the-art model trained on $190$ predictors. In conclusion, we provide a simple and computationally cheap model that can be coupled with climate projections to investigate how climate change will reshape carbon storage on a global scale.

Forest bird populations in Europe have remained stable overall, unlike the drastic decline in the populations of farmland species. However, this apparent overall stability may hide large variation among species. We aimed to determine if forest bird species with varying life histories and biome distributions show different population trends. We used functional traits and specialisation indices to study changes in abundance and distribution of European forest bird populations, and to identify “winner”, “loser”, and stable species. We defined change in abundance as the population trend of each species over the last 40 years, and change in distribution as two components: range change (i.e., area shrinkage or expansion) and range shift (i.e., latitudinal adjustments), both over the last 30 years. We also considered specialist groups of different biomes (i.e., boreal, temperate, Mediterranean and biome generalists) separately. We show that while Mediterranean and temperate species have increased in abundance and range, probably as the result of warmer temperatures and forest expansion in these regions, boreal forest species have declined in abundance and range area. This probably results from changes in forest structure and composition due to forestry practices, increasing temperatures, and colonisation of warm-dwelling species. Among boreal species, the ones related to mixed forest (i.e., mix of broadleaf and coniferous trees) declined the most, both in abundance and range, and shifted northwards. In contrast, for vertebrate carnivores (i.e., birds of prey), we observed abundance increase among Mediterranean species and southward expansion among all species. We conclude that forest bird species in Europe are sensitive to the combined effects of land use and climate change, and these effects vary among the different biomes. Our results highlight the necessity of maintaining and restoring key forest habitats (e.g. through increased protected areas and extensive management) and halting or limiting climate change, especially regarding boreal species.

Successful plant invasions are often explained by adaptation to novel environments. However, invasive species usually occupy broad niches within their native and introduced ranges. A true understanding of microevolution during invasion therefore requires a wide sampling of ranges, ideally with a knowledge of introduction history. We tested for genetic differentiation in herbivore resistance among 128 introduced (European, North American) and native (Chinese, Japanese) populations of the invasive Japanese knotweed (Reynoutria japonica) in two common gardens in the native range. In both common gardens, we found that the resistance traits of the introduced populations differed from most Chinese native populations but not from native populations in Japan, which are the two putative sources of introduction. Compared to Chinese populations, introduced European populations had thicker leaves in both common gardens with a lower C: N ratio but higher flavonoids content in the Shanghai garden. In the native range, variation in herbivore resistance was much more strongly associated with climate of origin than in introduced populations. Our results support that introducing particular resistance phenotypes from Japan played a key role in the invasion of knotweed into Europe and North America. Our study demonstrates how knowledge of introduction history can avoid misinterpretations of observed biogeographic divergence.

Remote sensing is an invaluable tool for tracking decadal-scale changes in vegetation greenness in response to climate and land use changes. While the Landsat archive has been widely used to explore these trends and their spatial and temporal complexity, its inconsistent sampling frequency over time and space raises concerns about its ability to provide reliable estimates of annual vegetation indices such as the annual maximum NDVI, commonly used as a proxy of plant productivity. Here we demonstrate for seasonally snow-covered ecosystems, that greening trends derived from annual maximum NDVI can be significantly overestimated because the number of available Landsat observations increases over time, and mostly that the magnitude of the overestimation varies along environmental gradients. Typically, areas with a short growing season and few available observations experience the largest bias in greening trend estimation. We show these conditions are met in late snowmelting habitats in the European Alps, which are known to be particularly sensitive to temperature increases and present conservation challenges. In this critical context, almost 50% of the magnitude of estimated greening can be explained by this bias. Our study calls for greater caution when comparing greening trends magnitudes between habitats with different snow conditions and observations. At a minimum we recommend reporting information on the temporal sampling of the observations, including the number of observations per year, when long term studies with Landsat observations are undertaken.

Fire plays a pivotal role in driving ecological shifts between Mediterranean-type vegetation and subtropical ecosystems in South Africa. This study investigates long-term environmental dynamics and ecological regime changes at the Mediterranean-type vegetation /subtropical boundary using a 6000-year palaeoecological sequence from the Baviaanskloof – a region of South Africa characterized by high levels of biodiversity and climate dynamism. Combining fossil pollen and microcharcoal data from a rock hyrax (Procavia capensis) midden, we analyse vegetation responses to environmental changes. Our findings reveal that Mediterranean-type vegetation resilience prevailed until ca. 2800 cal yr BP when a major fire event triggered a transition to a subtropical thicket-dominated environment. This abrupt ecological turnover underscores the significance of fire as a major driver of vegetation change at the Mediterranean-type vegetation /subtropical boundary. Our study emphasizes the vulnerability of Mediterranean-type vegetation ecosystems to global environmental change, suggesting potential implications for similar biome boundaries worldwide. By integrating multi-proxy palaeoecological evidence, we gain insights into the resilience and vulnerability of these ecosystems, aiding in understanding future responses to climate change scenarios.

Human activities drive ecological transformation, impacting island ecosystems from species diversity to ecological traits, mainly through habitat degradation and invasive species. Using two unique long-term datasets we aim to evaluate whether species traits (body size, trophic level, dispersal capacity and habitat occupancy) can predict temporal variations in the abundance of endemic, native non-endemic and exotic arthropods in the Azores Islands. We found that body size is crucial to predict arthropods abundance trends. Small-bodied herbivorous arthropods showed a decrease in abundance, while large-bodied indigenous arthropods increased in abundance, mainly in well-preserved areas. Also, large-bodied exotic arthropods increased in abundance across the entire archipelago. Moreover, endemic canopy dwellers increased in abundance, while endemic ground-dwellers decreased in abundance. Simultaneously, exotic arthropods showed the opposite result, increasing abundance in the ground while decreasing abundance in the canopy. Finally, habitat influenced both endemic and exotic spider abundance trends. Endemic spiders that occupy solely natural habitats experienced a decline in abundance, while exotic spiders in the same habitats increased in abundance. Our study underscores the significance of arthropod species traits in predicting abundance changes in island ecosystems over time, as well as the importance of monitoring species communities. Conservation efforts must extend beyond endangered species to protect non-threatened ones, given the increased extinction risk faced by even common species on islands. Monitoring and restoration programs are essential for preserving island ecosystems and safeguarding endemic arthropod populations.

Biogeography has a critical influence on how ecological communities respond to threats and how effective conservation interventions are designed. For example, the resilience of ecological communities is linked to environmental and climatic features, and the nature of threats impacting ecosystems also varies geographically. Understanding community-level threat responses may be most accurate at fine spatial scales, however collecting detailed ecological data at such a high resolution would be prohibitively resource intensive. In this study, we aim to find the spatial scale that could best capture variation in community-level threat responses whilst keeping data collection requirements feasible. Using a database of biodiversity records with extensive global coverage, we modelled species richness and total abundance (the responses) across land-use types (reflecting threats), considering three different spatial scales: biomes, biogeographical realms, and regional biomes (the interaction between realm and biome). We then modelled data from three highly sampled biomes separately to ask how responses to threat differ between regional biomes and taxonomic group. We found strong support for regional biomes in explaining variation in species richness and total abundance compared to biomes or realms alone. Our biome case studies demonstrate that there is a high variation in magnitude and direction of threat responses across both regional biomes and taxonomic group, but all groups in tropical forest showed a consistently negative response, whilst many taxon-regional biome groups showed no clear response to threat in temperate forest and tropical grassland. Our results suggest that the taxon-regional biome unit has potential as a reasonable spatial and ecological scale for understanding how ecological communities respond to threats and designing effective conservation interventions to bend the curve on biodiversity loss.

Climatic changes can affect species distributions, population abundance, and evolution. Such organismal responses could be determined by the amount and quality of available habitats, which can vary independently. In this study, we assessed changes in habitat quantity and quality independently to generate explicit predictions of the species’ responses since the Last Glacial Maximum (LGM) climatic changes. We built ecological niche models and distribution models for 21 reptile, mammal, and plant taxa from the Baja California peninsula inhabiting lowland or highland environments. Geological data suggests the CCSM global circulation model is a better representation of LGM climate for the Baja California peninsula. Significant niche divergence was detected for all clades within species, along with significant differences in niche breadth and area of distribution between northern and southern clades. Most clades showed a reduction in distribution area towards LGM. Further, niche marginality (used as a measure of habitat quality) was higher during LGM for most clades, except for northern highland species who experienced improvements in both. Our results suggest that changes in habitat quantity and quality can affect organismal response independently. This allows the prediction of genomic signatures associated with changes in effective population size and selection pressure that could be explicitly tested to support our models.

The analysis of macroecological patterns has necessitated the use of large, composite datasets recording local-scale species occurrences distributed across the globe. These datasets, however, have various spatial and temporal biases. They have rarely been compared to data collected in the field across large spatial gradients. In this paper we use two datasets built from online repositories plus a standardised field collection to reconstruct macroecological patterns for marine bivalves along the eastern coastline of Australia – spanning over 20° of latitude. We test the strength of the latitudinal diversity gradient using four diversity measures and identify a biogeographical boundary. The field collection demonstrates a strong latitudinal gradient, but mixed support was found in the composite datasets. Worse, adding observation-based records to the composite dataset obscured the latitudinal gradient. The biogeographic boundary was consistently found, and the location mirrored two previously published bioregionalisations. Although broad patterns seen in the field can be uncovered from composite macroecological datasets, care both in dataset construction and choice of methods is needed to ensure robust results.

Forest litter decomposition is considered as an essential ecosystem process affecting carbon and nutrient cycling in mountains. However, there exists high uncertainty in accurately estimating the contribution of litter decomposition to terrestrial ecosystems, largely due to the incomparability of different studies and the data limitation in microclimate and non-climatic factors at spatially matched scales. Here we used the tea bag index (TBI) as a standardized protocol to evaluate spatial variations in forest litter decomposition rate (k) and stabilization factor (S) across 10 mountains spanning a wide range of subtropical and tropical forests. Based on the coordinated experiment of 6,864 teabags in 568 sampling sites along elevations, we evaluated the importance of 10 environmental factors covering soil microclimate, edaphic properties, plant diversity, and topography on k and S by using model averaging and linear-mixed effects models. Of the 10 mountains, we found a consistently decreasing pattern of k and an increasing pattern for S along elevations. And the significant effect of k with elevation was mainly found in the western and northmost mountains, while the effect of S occurred in the western and southernmost mountains. For microclimate, there was a general importance of soil temperature (coef. = 0.48) and temperature variation in the growing season (coef. = 0.36) in k, and soil temperature (coef. = -0.46) and moisture variation on S (coef. = -0.36). The dominant role of soil microclimate was mainly found in western mountains with relatively cold environments. For non-climatic drivers, a significant effect of tree diversity on k and a negative correlation of edaphic and topography with S in the western and southern mountains were detected. These findings provide a general understanding of spatial variations of driving factors in forest litter decomposition and highlight a dominant control of soil microclimate in cold forests in high elevations and latitudes.