Biology subjects

Jetz, W.

Publications and source records attributed to Jetz, W..

At least 19 recordsLinked to original sources

bioRxiv2026

Movement mechanisms explain current animal density patterns and predict their reorganization under global change

Aim: To test whether individual movement mechanisms inferred from animal tracking data can be scaled up to explain landscape-scale patterns of population density and improve predictions of population redistribution under future environmental change. Location: Texas Gulf Coast, USA Time Period: 2009-2018 Major Taxa Studied: Whooping Crane (Grus americana) Methods: We parameterized individual-level step-selection functions using 14,898 GPS locations from 22 Whooping Cranes and propagated the resulting movement and habitat-selection mechanisms across the landscape to derive steady-state distributions of space use. We compared these movement-informed predictions with correlative species distribution models fitted to the same data. Predictions were evaluated using withheld tracking observations and fully independent population-level aerial-survey data. We then projected both approaches under sea-level-rise scenarios to assess how future habitat loss and fragmentation alter crane space use. Results: Movement mechanisms derived from individual-level tracking data captured the mechanistic dependence of population density on habitat quality and spatial configuration. When projected across the landscape, these mechanisms reproduced fully independently observed density patterns and outperformed conventional species distribution models. Because predictions arose from movement mechanisms rather than occurrence-environment correlations, movement-informed models also captured the effects of habitat reconfiguration under sea-level rise. They projected pronounced population redistribution and an expansion of core space-use areas of up to 80% which conventional models missed. Main Conclusions: Individual movement mechanisms derived from biologging data can scale up to explain current population structure and predict future redistribution under environmental change. By mechanistically accounting for how habitat configuration constrains accessibility, movement-informed models reveal severe impacts of fragmentation that are missed by conventional distribution models. Rapidly expanding biologging datasets therefore offer a scalable basis for connecting individual behavior to macroecological patterns and improving biodiversity forecasts in changing landscapes.

ecology↗

bioRxiv2026

Global slowdown in the rate of invasive alien species establishment

The number of species introduced outside of their historical ranges by human activity continues to rise. A subset of these species establishes, form self-sustaining populations, and some (invasive alien species) go on to cause substantial harm to biodiversity and ecosystems. Preventing new invasive alien species from establishing is the key focus of interventions, because post-establishment management is costly and often fails. However, it remains unclear how effective multilateral efforts have been in curbing the rise. Here we show that the emergence of new invasive alien species across countries is slowing, and trends are similarly negative across geographically diverse countries. Using data and modelling advances, we find a 35% reduction in the establishment of new invasive alien species over a policy-relevant 50-year time frame. The findings directly inform the assessment of progress for the invasive alien species target of the Kunming-Montreal Global Biodiversity Framework, and provide a global baseline for monitoring rates of invasive alien species establishment. Furthermore, the slowdown suggests that policy and investment over recent decades to prevent invasive alien species from entering and establishing in countries have had a positive effect.

ecology↗

bioRxiv2025

Extreme weather risk shrinks range size estimates and alters biodiversity predictions

Extreme weather events, including heat waves, cold snaps, and droughts, are increasing in frequency and intensity with expected but little understood consequences for biodiversity. Extreme weather events can push organisms beyond their physiological thermal or hydric tolerances and thus limit where they can persist, affecting their geographic distributions. Species might be especially sensitive to extreme weather at the edges of their geographic ranges, where they are often already living near their physiological limits. However, the influence of climatic variability and extreme weather is often ignored in favor of climatic means when estimating distributional and richness patterns. Here we link hundreds of millions of citizen science bird observations from 2004-2024 to high-resolution extreme weather risk maps to explore how climatic variability and extreme weather risk alters summer and winter distributions and biodiversity patterns for 535 North American species. We find that species distribution models accounting for historical extreme weather risk performed better at predicting richness and the presence of individual species across 220 well-surveyed sites. Models incorporating extreme weather predicted narrower geographic distributions than models relying on only climatic means, with species ranges shrinking an average of 6% in summer and 10% in winter and range truncation observed at the range edges. These effects were observed in both seasons but were particularly strong in winter, a time with greater short-term weather variability than summer. Richness estimates were substantially lower when extreme weather was accounted for, especially in the US southwest and central plains (up to 30-40 fewer species), regions highly prone to extreme heat, cold and drought. Our results suggest that more mechanistically informed biodiversity predictions that account for extreme weather are critical for reliably predicting shifting distributional and biodiversity patterns.

ecology↗

bioRxiv2024

Scaling ecological niches from individuals to populations and beyond

The niche is a key concept that unifies ecology and evolutionary biology. However, empirical and theoretical treatments of the niche are mostly performed at the species level, neglecting individuals as important units of ecological and evolutionary processes. So far, a formal mathematical link between individual-level niches and higher organismal-level niches has been lacking, hampering the unification of ecological theories and more accurate forecasts of biodiversity change. To fill in this gap, we propose a bottom-up approach to derive population and higher organismal-level niches from individual niches. We demonstrate the power of our framework by showing that 1) the statistical properties of higher organismal-level niches (e.g. niche breadth, skewness etc.) can be partitioned into individual contributions; 2) the species-level niche shifts can be estimated by tracing the responses of individuals. Our method paves the way for a unifying niche theory and enables mechanistic assessments of organism-environment relationships across organismal scales.

ecology↗

bioRxiv2024

The Performance and Potential of Deep Learning for Predicting Species Distributions

Species distribution models (SDMs) address the whereabouts of species and are central to ecology. Deep learning (DL) is poised to further elevate the already significant role of SDMs in ecology and conservation, but the potential and limitations of this transformation are still largely unassessed. We evaluate DL SDMs for 2,299 terrestrial vertebrate and invertebrate species at continental scale and 1km resolution in a like-for-like comparison with latest implementation of classic SDMs. We compare two DL methods (a multi-layer perceptron (MLP) on point covariates and a convolutional neural network (CNN) on geospatial patches) against existing SDMs (Maxent and Random Forest). On average, DL models match, but do not surpass, the performance of existing methods. DL performance is substantially weaker for species with narrow geographic ranges, fewer data points, and those assessed as threatened and hence often of greatest conservation concern. Furthermore, information leakage across dataset splits substantially inflates performance metrics, especially of CNNs. We find current DL SDMs to not provide significant gains, instead requiring careful experimental design to avoid biases. However, future advances in DL-supported use of ancillary ecological information have the potential to make DL a viable instrument in the larger SDM toolbox. Realising this opportunity will require a close collaboration between ecology and machine learning disciplines.

ecology↗

bioRxiv2024

Geographic redistributions are insufficient to mitigate the erosion of species environmental niches

As climate change accelerates, species may survive in place thanks to niche plasticity or adaptation or must redistribute to conserve their environmental niches1. Examples of such geographical range shifts abound2-4, but to date an assessment of species success in retaining niches and limiting their climate change exposure is missing. Here, we develop a novel method to account for biases inherent in tens of millions of citizen science observations, allowing us to evaluate how species have mitigated their climatic niche loss using geographical redistributions. We find that over 20 years, 384 North American bird species shifted their summertime distributions 0.73{degrees} north, mitigating their expected exposure to warming by [~]1.16 {degrees}C and thus averting 44% of expected niche loss had they stayed in place. Despite these movements, species were still exposed to an average [~]1.47 {degrees}C increase in temperature and few species achieved complete niche retention. Meanwhile, species only mitigated [~]0.47 {degrees}C (11%) in winter, shifting their niches by [~]3.74 {degrees}C, with almost no species fully retaining their niches. Species moving the furthest north succeeded most in conserving niches across both seasons. As expected, but previously untested at this scale, species that have physiological characteristics associated with dispersal achieved the greatest redistributions and niche retention. Most geographical redistributions have only been partially effective towards mitigating climate change and the gap between climate change exposure and species historical niches is growing rapidly even in a highly mobile group such as birds, raising concerns about the ability of less mobile taxa to persist in a warmer world.

ecology↗

bioRxiv2024

Choices to landscapes: Mechanisms of animal movement scale to landscape patterns

Understanding the geographic distributions of animals is central to ecological inquiry and conservation planning. Movement-based habitat selection models offer a powerful tool for identifying preferred environmental attributes, yet applying these models to predict animal geographic distributions faces methodological and computational challenges. Here, we present a framework that integrates habitat selection and movement behaviors to generate landscape-scale space use predictions. Through simulations and empirical data, we demonstrate that combining local selection and movement dynamics yields highly accurate emergent spatial distribution predictions. Our framework outperforms occurrence-based frameworks across individual, population, and regional scales. By explicitly addressing the role of movement constraints and selection patterns in heterogeneous environments, our framework bridges animal movement and spatial distribution modeling in a scalable manner. This approach offers a new paradigm to link organism-environment interactions from individual space use to habitat connectivity and population distributions relevant to policy and conservation.

ecology↗

bioRxiv2023

Continental species distribution and biodiversity predictions depend on modeling grain

As global change accelerates, accurate predictions of species distributions and biodiversity patterns are critical to prevent population declines and biodiversity loss. However, at continental and global scales, these predictions are often derived from species distribution models (SDMs) fit at coarse spatial grains uninformed by ecological processes. Coarse-grain models may systematically bias predictions of distributions and biodiversity if they are consistently over- or under-estimating area with suitable habitat, and this bias may intensify in regions with heterogenous landscapes or with poor data coverage. To test this, we fit presence-absence SDMs characterizing both the summer and winter distributions of 572 North American bird species - nearly the entire avian diversity of the US and Canada - across five spatial grains from 1 to 50 km, using observations from the eBird citizen science initiative. We find that across both seasons, models fit at 1 km performed better under cross-validation than those at coarser scales and more accurately predicted species presences and absences at local sites. Coarser-grain models, including models fit at 3 km, consistently under-predicted range area relative to 1 km models, suggesting that coarse-grain estimates of distributions could be missing important habitat. This bias intensified during summer (83% of species) when many birds have smaller operational scales via localized home ranges and greater habitat specificity while breeding. Biases were greatest in heterogenous desert and scrubland regions and lowest in more homogenous boreal forest and taiga-dominated regions. When aggregating distributions to produce continental biodiversity predictions, coarse-grain models overpredicted diversity in the west and underpredicted it in the great plains, prairie pothole region and boreal/taiga zones. The modern availability of high-performance computing and high-resolution observational and environmental data provides opportunities to improve continental predictions of species distributions and biodiversity.

ecology↗

bioRxiv2023

Assessing the impact of binary land cover variables on species distribution models: A North Americanstudy on water birds

AimSpecies distribution models (SDMs) are an important tool for predicting species occurrences in geographic space and for understanding the drivers of these occurrences. An effect of environmental variable selection on SDM outcomes has been noted, but how the treatment of variables influences models, including model performance and predicted range area, remains largely unclear. For example, although landcover variables included in SDMs in the form of proportions, or relative cover, recent findings suggest that for species associated with uncommon habitats the simple presence or absence of a landcover feature is most informative. Here we investigate the generality of this hypothesis and determine which representation of environmental features produces the best-performing models and how this affects range area estimates. Finally, we document how outcomes are modulated by spatial grain size, which is known to influence model performance and estimated range area. LocationNorth America MethodsWe fit species distribution models (via Random Forest) for 57 water bird species using proportional and binary estimates of water cover in a grid cell using occurrence data from the eBird citizen science initiative. We evaluated four different thresholds of feature prevalence (land cover representations) within the cell (1%, 10%, 20% or 50%) and fit models across both breeding and non-breeding seasons and multiple grain sizes (1, 5, 10, and 50 km cell lengths). ResultsModel performance was not significantly affected by the type of land cover representation. However, when the models were fitted using binary variables, the model-assessed importance of water bodies significantly decreased, especially at coarse grain sizes. In this binary variable-case, models relied more on other land cover variables, and over-or under-predicted the species range by 5-30%. In some cases, differences up to 70% in predicted species ranges were observed. Main conclusionsMethods for summarizing landcover features are often an afterthought in species distribution modelling. Inaccurate range areas resulting from treatment of landcover features as binary or proportional could lead to the prioritization of conservation efforts in areas where the species do not occur or cause the importance of crucial habitats to be missed. Importantly, our results suggest that at finer grain sizes, binary variables might be more useful for accurately measuring species distributions. For studies using relatively coarse grain sizes, we recommend fitting models with proportional land cover variables.

ecology↗

bioRxiv2023

BeeDC: An R package and globally synthesised and flagged bee occurrence dataset

Species occurrence data are foundational for research, conservation, and science communication, but the limited availability and accessibility of reliable data represents a major obstacle, particularly for insects, which face mounting pressures. We present BeeBDC, a new R package, and a global bee occurrence dataset to address this issue. We combined >18.3 million bee occurrence records from multiple public repositories (GBIF, SCAN, iDigBio, USGS, ALA) and smaller datasets, then standardised, flagged, deduplicated, and cleaned the data using the reproducible BeeBDC R-workflow. Specifically, we harmonised species names (following established global taxonomy), country names, and collection dates and we added record-level flags for a series of potential quality issues. These data are provided in two formats, "cleaned" and "flagged-but-uncleaned". The BeeBDC package with online documentation provides end users the ability to modify filtering parameters to address their research questions. By publishing reproducible R workflows and globally cleaned datasets, we can increase the accessibility and reliability of downstream analyses. This workflow can be implemented for other taxa to support research and conservation.

ecology↗

bioRxiv2023

A phylogeny-informed characterization of global tetrapod traits addresses data gaps and biases

Tetrapods (amphibian, reptiles, birds and mammals) are model systems for global biodiversity science, but continuing data gaps, limited data standardisation, and ongoing flux in taxonomic nomenclature constrain integrative research on this group and potentially cause biased inference. We combined and harmonised taxonomic, spatial, phylogenetic, and attribute data with phylogeny-based multiple imputation to provide a comprehensive data resource (TetrapodTraits 1.0.0) that includes values, predictions, and sources for body size, activity time, micro- and macrohabitat, ecosystem, threat status, biogeography, insularity, environmental preferences and human influence, for all 33,281 tetrapod species covered in recent fully sampled phylogenies. We assess gaps and biases across taxa and space, finding that shared data missing in attribute values increased with taxon-level completeness and richness across clades. Prediction of missing attribute values using multiple imputation revealed substantial changes in estimated macroecological patterns. These results highlight biases incurred by non-random missingness and strategies to best address them. While there is an obvious need for further data collection and updates, our phylogeny--informed database of tetrapod traits can support a more comprehensive representation of tetrapod species and their attributes in ecology, evolution, and conservation research.

ecology↗

bioRxiv2022

The build-up of the present-day tropical diversity of tetrapods

The extraordinary number of species in the tropics when compared to the extra-tropics is probably the most prominent and consistent pattern in biogeography, suggesting that overarching processes regulate this diversity gradient. A major challenge to characterizing which processes are at play relies on quantifying how the frequency and determinants of tropical and extra-tropical speciation, extinction and dispersal events shaped evolutionary radiations. We address this question by developing and applying spatio-temporal phylogenetic and paleontological models of diversification for tetrapod species incorporating paleoenvironmental variation. Our phylogenetic model results show that area, energy or species richness did not uniformly affect speciation rates across tetrapods and dispute expectations of a latitudinal gradient in speciation rates. Instead, both neontological and fossil evidence coincide in underscoring the role of extra-tropical extinctions and the outflow of tropical species in shaping biodiversity. These diversification dynamics accurately predict present-day levels of species richness across latitudes and uncover temporal idiosyncrasies but spatial generality across the major tetrapod radiations.

evolutionary biology↗

bioRxiv2022

Diverse strategies for tracking seasonal environmental niches at hemispheric scale

Species depend upon a constrained set of environmental conditions, or niches, for survival and reproduction that are increasingly lost under climatic change. Seasonal environments require species to either track their niches via movement or undergo physiological or behavioral changes to survive. Here we identify the tracking of both environmental niche position and breadth across 619 New World bird species and assess their phylogenetic and functional underpinning. Partitioning niche position and breadth tracking can inform whether climatic means or extremes limit seasonal distributions. We uncover diverse strategies, including the tracking of niche position, breadth, both, or neither, suggesting highly variable sensitivity to ongoing climatic change. There was limited phylogenetic determinism to this variation, but a strong association with functional attributes that differed between niche position and breadth tracking. Our findings imply significant functional consequences for communities and ecosystems as impending climate change affects some niche tracking strategies more than others.

ecology↗

bioRxiv2022

EDGE2: advancing the prioritisation of threatened evolutionary history for conservation action

The global biodiversity crisis threatens the natural world and its capacity to provide benefits to humans into the future. The conservation of evolutionary history, captured by the measure phylogenetic diversity (PD), is linked to the maintenance of these benefits and future options. The Evolutionarily Distinct and Globally Endangered (EDGE) metric has, since 2007, been used to identify species for conservation action that embody large amounts of threatened evolutionary history. In 2017, we convened a workshop to update the EDGE metric to incorporate advances in the field of phylogenetically-informed conservation. Building on that workshop, we devised the metric EDGE2, which we present here. EDGE2 uses a modular, tiered approach to provide priority rankings--and associated measures of uncertainty in both phylogenetic and extinction risk data--for all species in a clade. EDGE2 takes into account the extinction risk of closely-related species to better reflect the contribution a species is expected to make to overall PD in the future. We applied EDGE2 to the worlds mammals to identify an updated list of priority EDGE species and compare the results with the original EDGE approach. Despite similarity in the priority lists produced between EDGE and EDGE2, EDGE2 places greater priority on species with fewer close relatives on the Tree of Life. As we approach a crossroads for global biodiversity policy, EDGE2 exemplifies how academic and applied conservation biologists can collaborate to guide effective priority-setting to conserve the most irreplaceable components of biodiversity upon which humanity depends.

zoology↗

bioRxiv2022

The Global Register of Introduced and Invasive Species: Country Compendium

The Country Compendium of the Global Register of Introduced and Invasive Species (GRIIS) is a collation of data across 196 individual country checklists of alienspecies, along with a designation of those species with evidence of impact at a country level. The Compendium provides a baseline for monitoring the distribution and invasion status of all major taxonomic groups, and can be used for the purpose of global analyses of Introduced (alien, non-native, exotic) and Invasive species (invasive alien species), including regional, single and multi-species taxon assessments and comparisons. It enables exploration of gaps and inferred absences of species for countries, and provides a means for short to medium term refinement of GRIIS Checklists. The Country Compendium is, for example, instrumental, along with data on first records of introduction, for assessing and reporting on invasive alien species targets, including for the Convention on Biological Diversity and Sustainable Development Goals. The GRIIS Country Compendium provides a baseline and mechanism for tracking the spread of introduced and invasive alien species across countries globally. O_TBL View this table: org.highwire.dtl.DTLVardef@eb30fdorg.highwire.dtl.DTLVardef@dd338aorg.highwire.dtl.DTLVardef@62b8daorg.highwire.dtl.DTLVardef@1561763org.highwire.dtl.DTLVardef@119988e_HPS_FORMAT_FIGEXP M_TBL C_TBL

ecology↗

bioRxiv2021

Macroevolutionary dynamics of climatic niche space

How and why lineages evolve along niche space as they diversify and adapt to different environments is fundamental to evolution. Progress has been hampered by the difficulties of linking a comprehensive empirical characterization of species niches with flexible evolutionary models that describe their evolution. Consequently, the relative influence of external episodic and biotic factors remains poorly understood. Here we characterize species two-dimensional temperature and precipitation niche space occupied (i.e., species niche envelope) as complex geometries and assess their evolution across a large vertebrate radiation (all Aves) using a model that captures heterogeneous evolutionary rates on time-calibrated phylogenies. We find that extant birds coevolved from warm, mesic climatic niches into colder and drier environments and responded to the K-Pg boundary with a dramatic increase in disparity. Contrary to expectations of subsiding rates of niche evolution as lineages diversify, our results show that overall rates have increased steadily, with some lineages experiencing exceptionally high evolutionary rates, associated with colonization of novel niche spaces, and others showing niche stasis. Both competition- and environmental change-driven niche evolution transpire and result in highly heterogeneous rates near the present. Our findings share the limitations of all work based purely on extant taxa but highlight the growing ecological and conservation insights arising from the model-based integration of increasingly comprehensive and robust environmental and phylogenetic information.

evolutionary biology↗

bioRxiv2021

Policy-relevant indicators for invasive alien species assessment and reporting

Invasive alien species are repeatedly shown to be amongst the top threats to biodiversity globally. Robust indicators for measuring the status and trends of biological invasions are lacking, but essential for monitoring biological invasions and the effectiveness of interventions. Here, we formulate and demonstrate three such indicators that capture the key dimensions of species invasions, each a significant and necessary advance to inform invasive alien species policy targets: 1) Rate of Invasive Alien Species Spread, which provides modelled rates of ongoing introductions of species based on invasion discovery and reporting. 2) Impact Risk, that estimates invasive alien species impacts on the environment in space and time and provides a basis for nationally targeted prioritization of where best to invest in management efforts. 3) Status Information on invasive alien species, that tracks improvement in the essential dimensions of information needed to guide relevant policy and data collection and in support of assessing invasive alien species spread and impact. We show how proximal, model-informed status and trend indicators on invasive alien species can provide more effective global (and national) reporting on biological invasions, and how countries can contribute to supporting these indicators.

ecology↗

bioRxiv2021

Targeted, collaborative biodiversity conservation in the global ocean can benefit fisheries economies

Marine protected areas (MPAs) are key to averting continued loss of species and ecosystem services in our oceans, but concerns around economic trade-offs hamper progress. Here we provide optimized planning scenarios for global MPA networks that secure species habitat while minimizing impacts on fisheries revenues. We found that MPA coverage requirements differ vastly among nations, and that two-thirds of nations benefit economically from a collaborative approach. Immediate global protection of marine biodiversity habitat comes with losses of ~19% of total fisheries revenues, but international cooperation in concert with high seas protection improves economic losses for most countries, safeguards all species, and could save ~5B USD annually worldwide. Nations and fishery economies both share benefits from a coordinated approach to conserving marine biodiversity, with direct relevance to current international policies.

ecology↗