Quickly locating new populations of non‐native species can reduce the ecological and economic costs of species invasions. However, the difficulty of predicting which new non‐native species will establish, and where, has limited active post‐border biosurveillance efforts. Because pathways of introduction underlie spatial patterns of establishment risk, an intuitive approach is to search for new non‐native species in areas where many non‐native species have first been detected in the past. We formalize this intuition via first records distribution models (FRDMs), which apply species distribution modeling methods to the collection of first occurrence records across species (i.e. one record per species). We define FRDMs as statistical models that quantify environmental conditions associated with species' first naturalized records to predict spatial patterns of establishment risk. We model the first records of non‐native plants in the conterminous USA as a proof‐of‐concept. The novelty of FRDMs is that their inferences apply not just to the species that contributed data; they provide a rigorous framework for predicting hotspots of invasion for new non‐native taxa that share a pathway of introduction with the modeled species. FRDMs can guide survey efforts for new non‐native taxa at multiple scales and across ecosystems.

Avian population sizes fluctuate and change over vast spatial scales, but the mechanistic underpinnings remain poorly understood. A key question is whether spatial and annual variation in avian population dynamics is driven primarily by variation in breeding season recruitment or by variation in overwinter survival. We present a method using large‐scale volunteer‐collected data from project eBird to develop species‐specific indices of net population change as proxies for survival and recruitment, based on twice‐annual, rangewide snapshots of relative abundance in spring and fall. We demonstrate the use of these indices by examining spatially explicit annual variation in survival and recruitment in two well‐surveyed nonmigratory North American species, Carolina wren Thryothorus ludovicianus and northern cardinal Cardinalis cardinalis. We show that, while interannual variation in both survival and recruitment is slight for northern cardinal, eBird abundance data reveal strong and geographically coherent signals of interannual variation in the overwinter survival of Carolina wren. As predicted, variation in wintertime survival dominates overall interannual population fluctuations of wrens and is correlated with winter temperature and snowfall in the northeastern United States, but not the southern United States. This study demonstrates the potential of participatory science (also known as citizen science) datasets like eBird for inferring variation in demographic rates and introduces a new complementary approach towards illuminating the macrodemography of North American birds at comprehensive continental extents.

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 novel 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 140‐years chronosequence on a glacier foreland, we address the effects of glacier retreat on network structure and robustness. Our results show that the prevalence of different network motifs changes over spacetime, leading to a decrease of network robustness. With glacier retreat, mutualistic networks shift from highly connected with diverse specialist interactions to loosely connected with few generalist interactions. Furthermore, despite the turnover of plant species, we find that species structural roles remain constant over spacetime while depending on species identity. Our findings suggest that glacier retreat reshuffles mutualistic networks with motifs posing low robustness, leading to increased fragility. Understanding the assembly and breaking down of species interaction networks provides novel insights into the development and stability of novel, post‐glacial ecological systems facing glacier extinction.

Genetic variation among populations is reflected in biogeographic patterns for many species, but general rules of spatial genetic variation have not been established. In this paper, we establish a theoretical framework based on projecting environmental Grinellian niches back through time to relate the present geographic distribution of population genetic structure to a given species' historical evolutionary context. Thanks to advances in next-generation sequencing technologies, as well as more accurate climate models and the amassing of information stored in biological collections, it is possible to implement this theoretical framework directly. We develop a case study of the Tassel-eared Squirrel (Sciurus aberti) to jointly analyze spatial, environmental, and genetic data to predict the historical endemic area of this species. Our results reveal that in cases of genetic isolation by geographic distance, the prevalence of environmental suitability over time corresponds to the genetic fixation index ( ) of populations with respect to a source population. Populations closer to the historical endemic area show higher genetic diversity and a lower value. This empirical example relates back to the theoretical framework, allowing two further advances: (i) a layer of biogeographic explanation for the results obtained from population genomic methods; and (ii) predictive maps of this genetic structure to support biodiversity conservation efforts. Overall, this work advances a perspective that integrates population genetics with historical patterns of species distribution. The limitations posed in the theoretical framework should be considered before implementing the SPA in a general way over different taxa. Otherwise, the predictability of the genetic diversity of populations as a product of environmental stability over time may not be adequate.

Liverworts are an ancient plant lineage that occurs worldwide with the highest species richness in cool and humid habitats such as tropical montane and temperate rain forests. It has been proposed that liverworts originated under such temperate climatic conditions and have later expanded into more tropical conditions, but how this is reflected in their phylogenetic diversity along the strong climatic gradients associated with elevation remains unexplored. We studied the phylogenetic diversity of regional liverwort floras along the elevational gradient in the tropical Andes, comparing indices that emphasize deeper and shallower phylogenetic relationships, and relating these to temperature‐ and precipitation‐related variables, as well as to climatic extremes and seasonality. We found that whereas liverwort species richness peaks at around 2000 m a.s.l., richness‐corrected phylogenetic diversity increases with elevation, and the standardized effect of size of phylogenetic diversity is highest at 2500–4000 m a.s.l. This is in accordance with an origin of liverworts under cool conditions, followed by more recent diversification in warmer climates at lower elevations. We further found temperature‐related climatic parameters to be stronger predictors of phylogenetic diversity of liverworts than precipitation‐related variables, and climatic extremes to have a stronger influence than climatic seasonality. We interpret these patterns as reflecting the physiological challenges of adapting to low temperatures as well as rare occurrences of extreme climatic events. All this reveals a strong signal of the evolutionary dynamics of this ancient plant lineage linked with its physiological adaptations to climatic conditions. The age of this group and its poikilohydric nature, i.e. its inability to regulate water loss, lead to patterns that contrast with those of vascular plants, allowing for discerning evolutionary generalities that are independent of physiology and lineage age.

The Bass Becking and Beijerinck theory of the microbial world that ‘everything is everywhere but the environment selects' has provided a basis to test microbial ecological theory for almost a century (Baas Becking 1934). Applying theory to the apparent chaos of the microbial world is arduous, and applying rules that guide our understanding is difficult. The Bass Becking and Beijerinck theory attempts to explain microbial community structure, i.e. why are certain microbes in a given environment? And why is a particular environment populated by certain microbes? Since the theory was advanced, limitations have been found. In particular, the advent of next‐generation sequencing in the 2000s has amplified our ability to categorize and quantify the microbial world (Tringe and Rubin 2005). Despite evident limitations demonstrating that the Bass Becking and Beijerinck theory is an oversimplification, it is perhaps the most unifying theory within microbial ecology (De Wit and Bouvier 2006).

Species distribution models (SDMs) have proven valuable in filling gaps in our knowledge of species occurrences. However, despite their broad applicability, SDMs exhibit critical shortcomings due to limitations in species occurrence data. These limitations include, in particular, issues related to sample size, positional uncertainty, and sampling bias. In addition, it is widely recognised that the quality of SDMs as well as the approaches used to mitigate the impact of the aforementioned data limitations depend on species ecology. While numerous studies have evaluated the effects of these data limitations on SDM performance, a synthesis of their results is lacking. However, without a comprehensive understanding of their individual and combined effects, our ability to predict the influence of these issues on the quality of modelled species–environment associations remains largely uncertain, limiting the value of model outputs. In this paper, we review studies that have evaluated the effects of sample size, positional uncertainty, sampling bias, and species ecology on SDMs outputs. We build upon their findings to provide recommendations for the critical assessment of species data intended for use in SDMs.

Feedbacks are the basic linkages of living systems. In organisms, they regulate the processes of growth and homeostasis, as well as their interactions with their world. Feedback, which Judson (1980) called ‘one of the chief themes of scientific understanding,' is equally important in ecological systems. The ecological literature is rich in papers dealing with the role of feedback in various phenomena. However, we know of no comprehensive synthesis of feedbacks in ecology. Pichon et al. (2024) accomplish this, and for the first time show that ecological feedbacks can be categorized in terms of a small number of fundamental attributes. The paper brings the array of different types of feedbacks into a manageable order, providing not only the relevant theoretical framework but also guidance on methods for applying understanding to practical issues.

Evidence of large‐scale biodiversity degradation in marine ecosystems has been reported worldwide, yet most research has focused on few species of interest or on limited spatiotemporal scales. Here we assessed the spatial and temporal changes in the taxonomic and functional composition of fish communities in European seas over the last 25 years (1994–2019). We then explored how these community changes were linked to environmental gradients and fishing pressure. We show that the spatial variation in fish species composition is more than two times higher than the temporal variation, with a marked spatial continuum in taxonomic composition and a more homogenous pattern in functional composition. The regions warming the fastest are experiencing an increasing dominance and total abundance of r‐strategy fish species (lower age of maturity). Conversely, regions warming more slowly show an increasing dominance and total abundance of K‐strategy species (high trophic level and late reproduction). Among the considered environmental variables, sea surface temperature, surface salinity and chlorophyll‐a most consistently influenced communities' spatial patterns, while bottom temperature and oxygen had the most consistent influence on temporal patterns. Changes in communities' functional composition were more closely related to environmental conditions than taxonomic changes. Our study demonstrates the importance of integrating community‐level species traits across multi‐decadal scales and across a large region to better capture and understand ecosystem‐wide responses and provides a different lens on community dynamics that could be used to support sustainable fisheries management.

Rare plant and vertebrate species have been documented to contribute disproportionately to the total morphological structure of species assemblages. These species often possess morphologically extreme traits and occupy the boundaries of morphological space. As rare species are at greater risk of extinction than more widely distributed species, human‐induced disturbances can strongly affect ecosystem functions related to assemblage morphology. Here, we assess to what extent the distributions of ant morphological traits are supported by morphologically extreme species and how they are distributed among habitats in a global biodiversity hotspot, the Brazilian Amazon. We used a morphological database comprising 15 continuous morphological traits and 977 expert‐validated ant species distributed across the Brazilian Amazon. We produced species range estimates using species distribution models or alpha hulls (when few records were available). Next, we conducted a principal components analysis to combine traits into a space with reduced dimensionality (morphospace). Then, we identified morphologically extreme species in this space and quantified their contributions to morphological diversity across different habitat types in the Brazilian Amazon Basin. We identified 114 morphologically extreme ant species across the Amazon ant morphospace. These species also accounted for a large percentage of morphospace filling, exceeding 99% representation in the most disturbed habitats in the Amazon. Our results suggest that a few morphologically extreme species capture most of the variation in ant morphology and, therefore, the spectrum of ecosystem functions performed by ants in the Brazilian Amazon Basin. Further, unlike in many other groups, these extreme morphologies were represented by the set of most common species. These results suggest greater functional redundancy and resilience in Brazilian Amazon ants, but more broadly, they contribute to our understanding of ecological processes that sustain ecosystem functions.