Biology subjects

Fandos, G.

Publications and source records attributed to Fandos, G..

8 recordsLinked to original sources

bioRxiv2026

North American bird occupancy dynamics attributed to climate and land use change

Evidence is accumulating that global change is altering species distributions. Yet, detailed knowledge is missing about the relative and joint contribution of different drivers to observed species responses. Here, we implemented an impact attribution framework based on counterfactual simulations to assess the impact of climate and land use change on occupancy dynamics of North American breeding birds. We used a Bayesian framework to fit process-explicit dynamic occupancy models to long-term survey data for 159 species from 1995 to 2019, and quantified predictive performance using spatial and temporal cross-validation. We then assessed the relative importance and effect direction of climate and land use change while accounting for model predictive accuracy. Results indicate that climate change negatively affected 90 % of the species and land use change negatively impacted 96 %. Climate change emerged as more important than land use change for driving changes in occupancy across species. Remarkably, the effects of both drivers were mostly antagonistic rather than acting additively or synergistically. Climate was the most important driver for bird communities in the western USA, while land use change dominated in the southeast, and combined climate and land use change in the northeast. Our analysis demonstrates that recent changes in North American bird distributions are shaped by multiple global change drivers acting in concert. The effect of recent climate and land use change were mostly antagonistic, and thus trends in bird occupancy dynamics could not be understood by studying the impact of those drivers in isolation. By disentangling the effects of climate and land use change on biodiversity trends, impact attribution approaches can improve our understanding of global change impacts and can support conservation planning and more accurate and realistic projections of biodiversity response to global change.

ecology↗

bioRxiv2025

Landscape context drives within-species variation in dispersal kernels and limits transferability

Dispersal is a key ecological trait that ensures connectivity, gene flow, and range dynamics, yet empirical information about the dispersal process remains scarce. While interspecific differences have been synthesized, intraspecific variation driven by individual movement and landscape context remains poorly understood. Here, we use the individual-based modelling platform RangeShifter to simulate movement trajectories of four animal species, from insects to mammals, across neutral landscapes varying in habitat amount and fragmentation. From these simulations we derived dispersal kernels using five probability density functions and analysed their response to landscape context. Across species, log-normal (fat-tailed) kernels consistently best described dispersal, but both median and long-distance dispersal varied strongly with habitat configuration. Habitat loss consistently reduced abundances, whereas fragmentation per se more strongly shaped dispersal kernels, providing mechanistic insight into a central debate in landscape ecology. Our results highlight that dispersal kernels do not transfer reliably across environments and should be treated as emergent, context-dependent properties. Progress in predicting species responses to global change will require empirical studies explicitly integrated with mechanistic modelling to uncover generalizable links between dispersal, traits, and landscape context.

ecology↗

bioRxiv2025

Consistent covariation of dispersal, life history and thermal niches across terrestrial arthropods

Arthropods, as ectotherms, are experiencing global declines, with many species facing the need to either acclimate or disperse in response to climate change. Understanding to which degree life history, dispersal and thermal niche traits covary is key to improve distribution forecasting under climate change. We quantified life history, dispersal and thermal range covariation among 4000 Western European arthropod species spanning eight orders, considering phylogenetic relationships to account for common ancestry. We demonstrate the existence of two axes of life history variation: the fast-slow continuum and the reproductive strategy axis. Species at the fast end of the continuum have higher dispersal capacities and broader thermal niches than slower species. The resulting trait syndromes were surprisingly consistent across orders. These trait combinations, which generally enhance range-shifting potential, point to the emergence of two distinct groups of arthropods: those well-suited and those less equipped to mitigate the effects of future climate change.

ecology↗

bioRxiv2024

Dispersal syndromes allow understanding but not predicting dispersal ability across the tree of life.

Dispersal is fundamental to many ecological and evolutionary processes, yet understanding the determinants and predictability of dispersal remains a crucial challenge. Dispersal syndromes, which describe patterns in the covariation of traits associated with dispersal, can help to gain a deeper understanding of the evolutionary dynamics of dispersal and its implications for range dynamics and ecosystem functioning in the face of global change. However, the extent to which such dispersal syndromes are generalizable across a large taxonomic scale has been hampered by low availability of standardized dispersal data across species. In this study, we used the most comprehensive and up-to-date empirical dispersal dataset for European birds to investigate the formation of dispersal syndromes and their effectiveness in predicting dispersal across species. We found body mass, feeding guild, and life-history traits shape dispersal syndromes in birds. Yet, only body mass and life history accurately predicted dispersal for unassessed species, while even multi-trait dispersal syndromes poorly predicted dispersal for phylogenetically distant species. These results shed light on the complex nature of bird dispersal and emphasize the need for refined approaches in elucidating the mechanisms and constraints underlying dispersal evolution. Our study highlights the importance of considering multiple factors and expanding empirical datasets to enhance our understanding of dispersal in avian populations.

zoology↗

bioRxiv2022

Fitting individual-based models of species range dynamics to long-term monitoring data

Generating spatial predictions of species distribution is a central task for research and policy. Currently, correlative species distribution models (cSDMs) are among the most widely used tools for this purpose. However, cSDMs fundamental assumption of species distributions in equilibrium with their environment is rarely met in real data and limits their applicability for dynamic projections. Process-based, dynamic SDMs (dSDMs) promise to overcome these limitations as they explicitly represent transient dynamics and enhance spatio-temporal transferability. Software tools for implementing dSDMs become increasingly available, yet their parameter estimation can be complex. Here, we test the feasibility of calibrating and validating a dSDM using long-term monitoring data of Swiss red kites (Milvus milvus). This population has shown strong increases in abundance and a progressive range expansion over the last decades, indicating a non-equilibrium situation. We construct an individual-based model with the RangeShiftR modelling platform and use Bayesian inference for model calibration. This allows the integration of heterogeneous data sources, such as parameter estimates from published literature as well as observational data from monitoring schemes, with coherent assessment of parameter uncertainty. Our monitoring data encompass counts of breeding pairs at 267 sites across Switzerland over 22 years. We validate our model using a spatial-block cross-validation scheme and assess predictive performance with a rank-correlation coefficient. Our model showed very good predictive accuracy of spatial projections and represented well the observed population dynamics over the last two decades. Results suggest that reproductive success was a key factor driving the observed range expansion. According to our model, the Swiss red kite population fills large parts of its current range but has potential for further increases in density. We demonstrate the practicality of data integration and validation for dSDMs using RangeShifteR. This approach can improve predictive performance compared to cSDMs. The workflow presented here can be adopted for any population for which some prior knowledge on demographic and dispersal parameters as well as spatio-temporal observations of abundance or presence/absence are available. The fitted model provides improved quantitative insights into the ecology of a species, which may greatly help conservation and management actions. Open Research statementThis submission uses novel code which is provided in an external repository. All data and code required to replicate the presented analyses are provided as private-for-peer review via a public GitHub repository under the following link: https://github.com/UP-macroecology/Malchow_IBMcalibration_2023 Upon acceptance, this repository will be archived and versioned with Zenodo and its DOI provided. For this study, a tagged development version of the R package RangeShiftR was used that is available at: https://github.com/RangeShifter/RangeShiftR-package/releases/tag/v.1.1-beta.0

ecology↗

bioRxiv2022

bi-axial orientation could explain range expansion in a migratory songbird

The likelihood of a new migratory route evolving is a function of the associated fitness payoff, and the probability that the route arises in the first place. Cross-breeding studies suggest that young birds migrate in a direction intermediate between their parents, though this would seemingly not explain how highly divergent migratory trajectories arise in apparently sympatric populations. It has been suggested that diametrically opposed reverse migratory trajectories might be surprisingly common, and if such routes were heritable it follows that they could underlie the rapid evolution of divergent migratory trajectories. Here, we used Eurasian blackcap (Sylvia atricapilla; blackcap) ringing recoveries and geolocator trajectories to investigate whether a recently-evolved northwards autumn migratory route could be explained by the reversal of each individuals expected southwards migratory direction. We found that northwards migrants were recovered closer to the sites specified by a precise axis reversal than would be expected by chance, consistent with the rapid evolution of new migratory routes via bi-axial variation in orientation. We suggest that the surprisingly high probability of axis reversal might allow birds to expand their wintering ranges rapidly, and hence propose that understanding how direction is encoded is crucial when characterising the genetic basis of migratory direction and how this relates to route evolution.

zoology↗

bioRxiv2021

Standardised empirical dispersal kernels emphasise the pervasiveness of long-distance dispersal in European birds

O_LIDispersal is a key life-history trait for most species and essential to ensure connectivity and gene flow between populations and facilitate population viability in variable environments. Despite the increasing importance of range shifts due to global change, dispersal has proved difficult to quantify, limiting empirical understanding of this phenotypic trait and wider synthesis. C_LIO_LIHere we aim to estimate and compare empirical dispersal kernels for European breeding birds considering average dispersal, natal (before first breeding) and breeding dispersal (between subsequent breeding attempts), and test whether different dispersal properties are phylogenetically conserved. C_LIO_LIWe standardised and analysed data from an extensive volunteer-based bird ring-recoveries database in Europe (EURING) by accounting for biases related to different censoring thresholds in reporting between countries and to migratory movements. Then, we fitted four widely used probability density functions in a Bayesian framework to compare and provide the best statistical descriptions of the average, the natal and the breeding dispersal kernels for each bird species. C_LIO_LIThe dispersal movements of the 234 European bird species analysed were statistically best explained by heavy-tailed kernels, meaning that while most individuals disperse over short distances, long-distance dispersal is a feature in almost all bird species. The overall phylogenetic signal in both median and long dispersal distances was low (Pagels {lambda} < 0.40), implying a high degree of taxonomic generality in our findings. As expected in birds, natal dispersal was 5 Km greater as an average than breeding dispersal for most species (88% species analysed). C_LIO_LIOur comprehensive analysis of empirical kernels indicates that long-distance dispersal is common among European breeding bird species and across life stages. The dispersal estimates offer a first guide to selecting appropriate dispersal kernels in range expansion studies and provide new avenues to improve our understanding of the mechanisms and rules underlying dispersal events. C_LI

ecology↗

bioRxiv2018

Genome-wide signals of drift and local adaptation during rapid lineage divergence in a songbird

The formation of independent evolutionary lineages involves neutral and selective factors, and understanding their relative roles in population divergence is a fundamental goal of speciation research. Correlations between allele frequencies and environmental variability can reveal the role of selection, yet the relative contribution of drift can be difficult to establish. Recently diversified systems such as that of the Oregon junco (Aves: Emberizidae) of western North America provide ideal scenarios to apply genetic-environment association analyses (GEA) while controlling for population structure. Genome-wide SNP loci analyses revealed marked genetic structure consisting of differentiated populations in isolated, dry southern mountain ranges, and more admixed recently expanded populations in humid northern latitudes. We used correlations between genomic and environmental variance to test for three specific modes of evolutionary divergence: (i) drift in geographic isolation, (ii) differentiation along continuous selective gradients, and (iii) isolation by adaptation. We found evidence of strong drift in southern mountains, but also signals of local adaptation in several populations, driven by temperature, precipitation, elevation and vegetation, especially when controlling for population history. We identified numerous variants under selection scattered across the genome, suggesting that local adaptation can promote rapid differentiation over short periods when acting over multiple independent loci.

evolutionary biology↗