Ecography最新文献

Developing species distribution models (SDMs) requires high-quality species occurrence records. These records, stemming from various sources with different sampling procedures, are often archived in open-access databases, making automated data quality checks inevitable. Temporal, geographic, and taxonomic quality checks are usually conducted in SDM workflows, but checking for records distant in environmental space, i.e. outliers, is often ignored.

Here, we present ‘specleanr', an R package that contains 20 outlier detection methods (ODMs) that can be ensembled to identify potential outliers in environmental predictors. These methods are categorized into 1) species-specific ecological range, 2) univariate, and 3) multivariate ODMs. All potential outliers flagged by the different methods are pooled to identify absolute outliers (records appearing in multiple methods). The local regression (LOESS) method is then used to automatically set a threshold that optimally identifies the absolute outliers. Additionally, clustering records into poor, fair, moderate, very strong, and perfect outliers, as well as non-outliers, is possible based on each record's likelihood as a potential outlier, which allows expert assessment.

We demonstrated the approach to 15 fish species from the Danube River Basin, including native, alien, threatened, and common species. We fitted SDMs using bioclimatic and hydromorphological parameters. We compared the model area under the curve (AUC) before and after outlier removal using three scenarios: 1) the LOESS method, 2) removing very strong outliers, and 3) removing perfect outliers. The results showed a significant improvement in the model AUC, with generally small to moderate effect sizes after outlier removal.

‘specleanr' is generalizable across taxonomic groups, data types, ecological realms, and geographic regions. Beyond SDMs, it can also be broadly used in general data analysis where outlier detection is essential. We provide detailed vignettes to support package use. ‘specleanr' offers a user-friendly and reproducible approach for handling outliers in biogeographical modeling and general data analysis workflows.

Cultivation by humans is the primary mode of introduction for naturalized plants and an important driver of naturalization, a critical step in the invasion process. Historical records of cultivated plants can represent introduced species pools and propagule pressure, allowing for tests of how species' traits and environmental context affect naturalization while accounting for human influence. Ruderal traits, which generally promote naturalization, may not be universally advantageous across closed versus open landscapes (forest versus grassland/shrubland) or different agricultural land use conversion types, though such context dependence has not yet been demonstrated at a broad scale. We analyzed the naturalization of 3949 cultivated ornamental non-native plant taxa that were for sale in nursery and seed catalogs in the conterminous United States during a period over 200 years to test for context dependence between traits associated with ruderality (short lifespan, shade intolerance, and self-compatibility) and estimates of historical forest/grassland cover and agricultural land use change. We found that present-day naturalization was closely tied to longer cultivation duration and greater cultivation extent. While ruderal traits tended to promote naturalization, perennial lifespan and shade tolerance favored naturalization in US states with higher forest cover, which is consistent with an alternative invasion strategy in closed-canopy systems. Land use conversion to pasture and succession of abandoned agricultural land promoted naturalization of disturbance-adapted plants in both forest and grassland landscapes. Our results emphasize the central role of cultivation in plant invasion and provide spatially and temporally extensive evidence that, while ruderal traits are important predictors of naturalization, they are dependent on the landscape context into which plants are introduced. Our work demonstrates the importance of integrating historical cultivation and land use/cover data for a nuanced understanding of the ecological factors that drive plant naturalization.

Species distribution models (SDMs), broadly referring to both species distribution and ecological niche modelling frameworks, are widely used to predict habitat suitability. However, their performance can be biased by uneven sampling effort in occurrence data. Building on two existing approaches, we propose a novel method for sampling bias correction, consisting of the estimation of observer kernel densities for individual species and their subsequent weighting according to the relative contribution of individual observers to the total number of focus species presences. This approach, the ‘presence-weighted observer-oriented approach' (PW-OOA), aimed to provide a better estimation of sampling effort, thus further improving SDM prediction performance. Using bird occurrence data from the Czech Republic, we modelled the distributions of 109 species using four approaches to bias correction: spatial thinning of species presences (STSP), target group occurrences background (TGOB), TGOB+ (tuned up by adjusting kernel smoothing bandwidths) and the new PW-OOA method. We compared the results with simple random background sampling. Models were evaluated using independent reference (presence–absence) data. The PW-OOA method outperformed the other approaches, with the greatest improvement detected for species with higher prevalence. However, as internal validation can be misleading with biased occurrences, we recommend TGOB+ as the most robust approach without independent data; with such data, PW-OOA is superior. While no single optimal combination of bandwidth and observers' weights was identified across species, the PW-OOA method provides a flexible framework to account for observer-specific sampling biases. This study demonstrates the crucial importance of considering the behavior of individual observers and sampling intensity smoothing when correcting for sampling bias in SDMs based on unstructured opportunistic occurrence data.

Temperate deciduous forests of North America, west Eurasia, and east Eurasia share a common origin but were later separated by major geographic barriers. Here, we examine their diverging biodiversity and evolutionary patterns by analyzing floristic richness, phylogenetic turnover, and community evolutionary distinctiveness (CED). We analyzed ~ 9600 vegetation plots across the Northern Hemisphere to calculate species rarefaction curves, within- and between-region phylogenetic turnover, and CED to assess the presence of evolutionarily isolated lineages within communities. We then modeled CED as a function of present-day and last glacial maximum (LGM) macro-environmental factors using boosted regression trees (BRTs). East Eurasian forests had the highest floristic richness, especially among woody species, while west Eurasia featured the richest herbaceous component. Within-region phylogenetic turnover was lowest in east Eurasia, followed by North America and west Eurasia. Between-region phylogenetic turnover was highest between west Eurasia and east Eurasia, and lowest for North America–east Eurasia. North America ranked highest in CED, followed by east Eurasia and west Eurasia. The BRTs revealed contrasting effects of the current and LGM climate on CED across regions. Present precipitation seasonality had a striking negative impact on CED in east Eurasia, whereas temperature seasonality had a strong negative effect in west Eurasia. East Eurasia's exceptional woody, gymnosperm, and fern diversity may reflect the region's long-term climatic and geological stability, which has allowed the persistence and diversification of ancient lineages. Meanwhile, the pronounced evolutionary distinctiveness of North American forests may be linked to more intense climatic and tectonic shifts over both Quaternary and deeper timescales. These findings highlight the unique evolutionary legacies of the temperate deciduous biome and call for future research that expands geographic and climatic coverage to capture the full diversity of temperate deciduous forests worldwide.

Human impacts are forcing species towards marginal and suboptimal portions of their historical ranges. Cetaceans are now under protection, but are still threatened by fishing activities, which reduce fish stocks, alter their feeding behavior, and can cause mortality due to bycatch. Here, we investigated how different fishing activities affect cetacean population density patterns in the Mediterranean, one of the most impacted and fished seas.

We collected 366 population density estimates for eight cetacean species. We then classified species into four trophic groups (planktivorous, piscivorous, teutophagous, generalist) and modelled their density as a function of both environmental and fishing variables (artisanal, demersal destructive, demersal non-destructive with low bycatch, demersal non-destructive with high bycatch, and pelagic fishing with low bycatch). Finally, to quantify human contribution to the observed geographic pattern of population density, we predicted and compared population density patterns under a baseline fishing and a minimum fishing scenario.

The four groups of cetacean species exhibited diverse responses to environmental and fishing variables. Demersal destructive fishing consistently had a negative influence on species population density. In contrast, others, such as demersal non-destructive fishing, showed mixed effects, including a potential attraction effect on piscivorous species. Overall, we predicted a probable change in the geographic pattern of population density of cetaceans in response to fishing activities, especially along the coasts in planktivorous species and in offshore areas in generalist species.

Our study provides evidence of the negative impact of fishing activities on cetacean population density, while highlighting functional group-specific responses to different fishing practices. These findings enhance our understanding of human-induced changes in marine ecosystems, suggesting probable alterations to the natural population density patterns of cetaceans in the Mediterranean Sea.

Human activities have significantly modified habitats, resulting in a global biodiversity crisis. In this study, we leveraged the first national-scale biodiversity survey based on airborne environmental DNA, comparing the effects of three human pressure indices increasing in complexity and scope – a binary urban–rural index, an index integrating land cover and pollutant concentrations as a proxy of human activity, and the composite human footprint index – across mammals, birds, insects, plants and fungi. While most taxa exhibited higher diversity in urban areas compared to rural ones, we uncovered more complex patterns using the landscape-pollution and human footprint indices, including dual diversity maxima at both high and moderate levels of human pressure. We also show an effect of human pressure on community composition even when local species richness remained stable: regardless of the human pressure index, anthropogenic sites were mostly characterized by synanthropic and invasive species. Overall, our results underscore the complex interactions among anthropogenic pressures, taxon diversity and community composition, demonstrating the value of multi-taxon analyses and multiple indices to better understand biodiversity patterns at large scales.

Amphibians balance their thermal and water budgets depending on their physiological state and the physical environment, with both factors capable of constraining activity. Most mechanistic assessments emphasize thermal over water constraints, potentially missing important aspects of amphibian ecophysiological patterns. Here, we evaluate the potential role of thermal and hydric constraints on the activity time of three Neotropical frogs (Leptodactylus fuscus, L. mystacinus, and L. macrosternum) across their geographic distribution. We inferred environmental suitability based on heat and mass transfer principles through a mechanistic modeling procedure anchored to empirically obtained laboratory and field data. We integrated species-specific thermal, hydric, and performance attributes with their immediate physical environment (ground-level microclimate) under nocturnal conditions, while allowing for the interactive response of retreating into shelter when facing physiological heat or water stress. Our results demonstrate the desiccation-prone role of smaller body sizes in increasing hydric restrictions and inhibiting activity, even under thermally adequate conditions, as well as the role of shelters as thermal and hydric refugia. More strikingly, thermal-induced restrictions in activity were linked to low temperatures rather than warmer conditions, indicating that their engagement in activity is mostly driven by the lower thermal bounds of their functional organismal performance. These findings provide a broader picture of climatic constraints on anuran activity and distribution, as well as insights into how species may respond to changing climatic conditions.

Understanding species distributions across Antarctica is crucial for biodiversity conservation under climate change, but continental-scale analyses of key terrestrial species remain scarce. Here, we modelled distributions of 28 moss species across Antarctica using log-Gaussian Cox process models and environmental covariates including topographic wetness index, distance to seabird colonies, and temperature. Broad-scale distributions were primarily driven by proximity to seabird colonies, while species exhibited distinct responses to water availability and temperature. Species exclusive to maritime Antarctica showed negative relationships with a topographic wetness index, whereas continent-wide species responded positively to water accumulation potential, reflecting regional differences in water availability and habitat preferences. Bias-corrected predictions revealed highest moss diversity in coastal regions, with inland areas supporting ecologically distinct assemblages. Our Bayesian modelling approach provides a foundation for forecasting biodiversity responses to environmental change in data-poor systems, offering critical insights for evidence-based conservation planning under increasing anthropogenic pressures.

Arctic marine ecosystems are rapidly transforming due to climate change. Warming temperatures and shrinking sea ice are enabling boreal fish to expand northward, possibly disturbing cold-adapted Arctic species assemblages. Species range shifts have been documented in the Bering and Barents Seas, raising concerns about ecosystem restructuring. Range shifts are especially difficult to detect in the Arctic due to sparse and inconsistent data. Here, we studied fish composition from eDNA water samples taken in East Greenland, Svalbard, the Barents Sea, and the Kara Sea during the TOPtoTOP and Arctic Century expeditions. We examined the environmental drivers of fish community structure using global dissimilarity models. We calculated the decadal rate of temperature change to identify the fastest-changing areas. We compared fish detections from eDNA with published historical records for the Kara Sea to assess possible range expansions. We found that temperature was the main factor influencing the taxa turnover of fish communities, with Gadidae and Liparis sp. driving the greatest compositional differences. Over the past 30 years, temperatures increased by 0.2 to 0.6°C per decade at our study sites, with the highest increases in western Svalbard and the lowest in the eastern Kara Sea. Despite the apparent dependence on temperature, we identified only one species detected outside its known latitudinal range, and five species in the Kara Sea with recent occurrences or representing an extended distribution. Our study suggests that temperature, the main driver of fish community assembly, is increasing rapidly in the Arctic, and a few species have likely already shifted recently, or at least their detections are new in some areas. While these detections cannot be definitively linked to range shifts, our results highlight the need to improve monitoring of high-latitude fish communities to detect and predict future ecosystem changes.