Fitting individual-based models of spatial population 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, a fundamental assumption of cSDMs, that species distributions are in equilibrium with their environment, is rarely fulfilled in real data and limits the applicability of cSDMs for dynamic projections. Process-based, dynamic SDMs (dSDMs) promise to overcome these limitations as they explicitly represent transient dynamics and enhance spatiotemporal transferability. Software tools for implementing dSDMs are becoming increasingly available, but 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 nonequilibrium situation. We construct an individual-based model using the RangeShiftR modeling platform and use Bayesian inference for model calibration. This allows the integration of heterogeneous data sources, such as parameter estimates from published literature and observational data from monitoring schemes, with a 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 RangeShiftR. 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 spatiotemporal observations of abundance or presence/absence are available. The fitted model provides improved quantitative insights into the ecology of a species, which can greatly aid conservation and management efforts.

Nearby night lighting, rather than sky glow, is associated with habitat selection by a top predator in human-dominated landscapes.

Artificial light at night (ALAN) is increasing in extent and intensity across the globe. It has been shown to interfere with animal sensory systems, orientation and distribution, with the potential to cause significant ecological impacts. We analysed the locations of 102 mountain lions (Puma concolor) in a light-polluted region in California. We modelled their distribution relative to environmental and human-disturbance variables, including upward radiance (nearby lights), zenith brightness (sky glow) and natural illumination from moonlight. We found that mountain lion probability of presence was highly related to upward radiance, that is, related to lights within approximately 500 m. Despite a general pattern of avoidance of locations with high upward radiance, there were large differences in degree of avoidance among individuals. The amount of light from artificial sky glow was not influential when included together with upward radiance in the models, and illumination from moonlight was not influential at all. Our results suggest that changes in visibility associated with lunar cycles and sky glow are less important for mountain lions in their selection of light landscapes than avoiding potential interactions with humans represented by the presence of nearby lights on the ground. This article is part of the theme issue 'Light pollution in complex ecological systems'.

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

Dispersal is a key life-history trait for most species and is 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. Here, we introduce a statistical framework to estimate standardised dispersal kernels from biased data. Based on this, we compare empirical dispersal kernels for European breeding birds considering age (average dispersal; natal, before first breeding; and breeding dispersal, between subsequent breeding attempts) and sex (females and males) and test whether different dispersal properties are phylogenetically conserved. We 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 different age and sex-specific dispersal kernels for each bird species. The 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 prevalent phenomenon in almost all bird species. The phylogenetic signal in both median and long dispersal distances estimated from the best-fitted kernel was low (Pagel's λ < 0.25), while it reached high values (Pagel's λ >0.7) when comparing dispersal distance estimates for fat-tailed dispersal kernels. As expected in birds, natal dispersal was on average 5 km greater than breeding dispersal, but sex-biased dispersal was not detected. Our robust analytical framework allows sound use of widely available mark-recapture data in standardised dispersal estimates. We found strong evidence 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.

La dispersión es un rasgo clave del ciclo vital de la mayoría de las especies y es esencial para garantizar la conectividad y el flujo genético entre poblaciones y contribuir a la viabilidad de la población en contextos de ambiente variable. A pesar de que la dispersión es clave para estudiar los cambios en el área de distribución de las especies debido al cambio global, la dispersión es difícil de cuantificar, lo que limita la comprensión empírica de este rasgo fenotípico y su síntesis más amplia. Aquí introducimos un marco de trabajo estadístico para estimar de manera estandarizada los kernels de dispersión a partir de datos sesgados. Basándonos en este marco, comparamos los kernels de dispersión empíricos para las aves reproductoras europeas considerando la edad (dispersión media vital; natal, antes de la primera reproducción; y dispersión reproductora, entre los intentos de reproducción posteriores) y el sexo (hembras y machos), además de explorar si las diferentes propiedades de dispersión se conservan filogenéticamente. Estandarizamos y analizamos los datos de una extensa base de datos de anillamiento de aves en Europa (EURING), basada en voluntarios, teniendo en cuenta los sesgos relacionados con los diferentes umbrales de comunicación de las anillas entre países y con los movimientos migratorios. A continuación, ajustamos, en un marco bayesiano, cuatro funciones de probabilidad ampliamente utilizadas para comparar y proporcionar las mejores descripciones estadísticas de los diferentes kernels de dispersión por edad y sexo para cada especie de ave. Los movimientos de dispersión de las 234 especies de aves europeas analizadas se explicaron estadísticamente mejor mediante kernels de cola pesada, lo que significa que, aunque la mayoría de los individuos se dispersan en distancias cortas, la dispersión a larga distancia es un fenómeno prevalente en casi todas las especies de aves. La señal filogenética tanto en las distancias de dispersión medias como en las largas estimadas a partir del kernel mejor ajustado fue baja (λ de Pagel < 0,25), mientras que alcanzó valores altos (λ de Pagel >0,7) al comparar las estimas de distancia de dispersión para los kernels de cola pesada. Como se esperaba en las aves, la dispersión natal fue en promedio 5 km mayor que la dispersión reproductiva, pero no se detectó una dispersión sesgada por sexo. Nuestro robusto marco analítico permite un buen uso de los datos de marcaje y recaptura disponibles para la estimación estandarizada de las distancias de dispersión. Hemos encontrado pruebas sólidas de que la dispersión a larga distancia es común entre las especies de aves reproductoras europeas y en todas las etapas de la vida. Las estimas de dispersión ofrecen un primer paso para seleccionar los kernels de dispersión adecuados para los estudios de expansión del rango de distribución y proporcionar nuevas vías de investigación para mejorar nuestra comprensión de los mecanismos y procesos que subyacen a los eventos de dispersión.

Understanding spatial patterns of poaching pressure using ranger logbook data to optimize future patrolling strategies.

Poaching is driving many species toward extinction, and as a result, lowering poaching pressure is a conservation priority. This requires understanding where poaching pressure is high and which factors determine these spatial patterns. However, the cryptic and illegal nature of poaching makes this difficult. Ranger patrol data, typically recorded in protected area logbooks, contain information on patrolling efforts and poaching detection and should thus provide opportunities for a better understanding of poaching pressure. However, these data are seldom analyzed and rarely used to inform adaptive management strategies. We developed a novel approach to making use of analog logbook records to map poaching pressure and to test environmental criminology and predator-prey relationship hypotheses explaining poaching patterns. We showcase this approach for Golestan National Park in Iran, where poaching has substantially depleted ungulate populations. We digitized data from >4800 ranger patrols from 2014 to 2016 and used an occupancy modeling framework to relate poaching to (1) accessibility, (2) law enforcement, and (3) prey availability factors. Based on predicted poaching pressure and patrolling intensity, we provide suggestions for future patrol allocation strategies. Our results revealed a low probability (12%) of poacher detection during patrols. Poaching distribution was best explained by prey availability, indicating that poachers target areas with high concentrations of ungulates. Poaching pressure was estimated to be high (>0.49) in 39% of our study area. To alleviate poaching pressure, we recommend ramping up patrolling intensity in 12% of the national park, which could be achievable by reducing excess patrols in about 20% of the park. However, our results suggest that for 27% of the park, it is necessary to improve patrolling quality to increase detection probability of poaching, for example, by closing temporal patrolling gaps or expanding informant networks. Our approach illustrates that analog ranger logbooks are an untapped resource for evidence-based and adaptive planning of protected area management. Using this wealth of data can open up new avenues to better understand poaching and its determinants, to expand effectiveness assessments to the past, and, more generally, to allow for strategic conservation planning in protected areas.

Can dynamic occupancy models improve predictions of species' range dynamics? A test using Swiss birds.

Predictions of species' current and future ranges are needed to effectively manage species under environmental change. Species ranges are typically estimated using correlative species distribution models (SDMs), which have been criticized for their static nature. In contrast, dynamic occupancy models (DOMs) explicitily describe temporal changes in species' occupancy via colonization and local extinction probabilities, estimated from time series of occurrence data. Yet, tests of whether these models improve predictive accuracy under current or future conditions are rare. Using a long-term data set on 69 Swiss birds, we tested whether DOMs improve the predictions of distribution changes over time compared to SDMs. We evaluated the accuracy of spatial predictions and their ability to detect population trends. We also explored how predictions differed when we accounted for imperfect detection and parameterized models using calibration data sets of different time series lengths. All model types had high spatial predictive performance when assessed across all sites (mean AUC > 0.8), with flexible machine learning SDM algorithms outperforming parametric static and DOMs. However, none of the models performed well at identifying sites where range changes are likely to occur. In terms of estimating population trends, DOMs performed best, particularly for species with strong population changes and when fit with sufficient data, while static SDMs performed very poorly. Overall, our study highlights the importance of considering what aspects of performance matter most when selecting a modelling method for a particular application and the need for further research to improve model utility. While DOMs show promise for capturing range dynamics and inferring population trends when fitted with sufficient data, computational constraints on variable selection and model fitting can lead to reduced spatial accuracy of predictions, an area warranting more attention.

Effects of intrinsic environmental predictability on intra-individual and intra-population variability of plant reproductive traits and eco-evolutionary consequences.

BACKGROUND AND AIMS: It is widely accepted that changes in the environment affect mean trait expression, but little is known about how the environment shapes intra-individual and intra-population variance. Theory suggests that intra-individual variance might be plastic and under natural selection, rather than reflecting developmental noise, but evidence for this hypothesis is scarce. Here, we experimentally tested whether differences in intrinsic environmental predictability affect intra-individual and intra-population variability of different reproductive traits, and whether intra-individual variability is under selection. METHODS: Under field conditions, we subjected Onobrychis viciifolia to more and less predictable precipitation over 4 generations and 4 years. We analysed effects on the coefficient of intra-individual variation (CVi-i) and the coefficient of intra-population variation (CVi-p), assessed whether the coefficients of intra-individual variation (CsVi-i) are under natural selection and tested for transgenerational responses (ancestor environmental effects on offspring). KEY RESULTS: Less predictable precipitation led to higher CsVi-i and CsVi-p, consistent with plastic responses. The CsVi-i of all studied traits were under consistent stabilizing selection, and precipitation predictability affected the strength of selection and the location of the optimal CVi-i of a single trait. All CsVi-i differed from the optimal CVi-i and the maternal and offspring CsVi-i were positively correlated, showing that there was scope for change. Nevertheless, no consistent transgenerational effects were found in any of the three descendant generations, which contrasts with recent studies that detected rapid transgenerational responses in the trait means of different plant species. This suggests that changes in intra-individual variability take longer to evolve than changes in trait means, which may explain why high intra-individual variability is maintained, despite the stabilizing selection. CONCLUSIONS: The results indicate that plastic changes of intra-individual variability are an important determinant of whether plants will be able to cope with changes in environmental predictability induced by the currently observed climatic change.

Habitat destruction and overexploitation drive widespread declines in all facets of mammalian diversity in the Gran Chaco.

Global biodiversity is under high and rising anthropogenic pressure. Yet, how the taxonomic, phylogenetic, and functional facets of biodiversity are affected by different threats over time is unclear. This is particularly true for the two main drivers of the current biodiversity crisis: habitat destruction and overexploitation. We provide the first long-term assessment of multifaceted biodiversity changes caused by these threats for any tropical region. Focussing on larger mammals in South America's 1.1 million km2 Gran Chaco region, we assessed changes in multiple biodiversity facets between 1985 and 2015, determined which threats drive those changes, and identified remaining key areas for all biodiversity facets. Using habitat and threat maps, we found, first, that between 1985 and 2015 taxonomic (TD), phylogenetic (PD) and functional (FD) diversity all declined drastically across over half of the area assessed. FD declined about 50% faster than TD and PD, and these declines were mainly driven by species loss, rather than species turnover. Second, habitat destruction, hunting, and both threats together contributed ~57%, ~37%, and ~6% to overall facet declines, respectively. However, hunting pressure increased where TD and PD declined most strongly, whereas habitat destruction disproportionally contributed to FD declines. Third, just 23% of the Chaco would have to be protected to safeguard the top 17% of all three facets. Our findings uncover a widespread impoverishment of mammal species richness, evolutionary history, and ecological functions across broad areas of the Chaco due to increasing habitat destruction and hunting. Moreover, our results pinpoint key areas that should be preserved and managed to maintain all facets of mammalian diversity across the Chaco. More generally, our work highlights how long-term changes in biodiversity facets can be assessed and attributed to specific threats, to better understand human impacts on biodiversity and to guide conservation planning to mitigate them.

Seasonal niche tracking of climate emerges at the population level in a migratory bird.

Seasonal animal migration is a widespread phenomenon. At the species level, it has been shown that many migratory animal species track similar climatic conditions throughout the year. However, it remains unclear whether such a niche tracking pattern is a direct consequence of individual behaviour or emerges at the population or species level through behavioural variability. Here, we estimated seasonal niche overlap and seasonal niche tracking at the individual and population level of central European white storks (Ciconia ciconia). We quantified niche tracking for both weather and climate conditions to control for the different spatio-temporal scales over which ecological processes may operate. Our results indicate that niche tracking is a bottom-up process. Individuals mainly track weather conditions while climatic niche tracking mainly emerges at the population level. This result may be partially explained by a high degree of intra- and inter-individual variation in niche overlap between seasons. Understanding how migratory individuals, populations and species respond to seasonal environments is key for anticipating the impacts of global environmental changes.

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 taxa like the Oregon junco (Aves, Passerellidae, Junco hyemalis oreganus) of western North America provide ideal scenarios to apply genetic-environment association analyses (GEA) while controlling for population structure. Analysis of genome-wide SNP loci revealed marked genetic structure consisting of differentiated populations in isolated, dry southern mountain ranges, and less divergent, recently expanded populations in humid northern latitudes. We used correlations between genomic and environmental variance to test for three specific modes of evolutionary divergence: (a) drift in geographic isolation, (b) differentiation along continuous selective gradients and (c) isolation-by-adaptation. We found evidence of strong drift in southern mountains, but also signals of local adaptation 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 when acting over multiple independent loci.

Linking seasonal home range size with habitat selection and movement in a mountain ungulate.

BACKGROUND: Space use by animals is determined by the interplay between movement and the environment, and is thus mediated by habitat selection, biotic interactions and intrinsic factors of moving individuals. These processes ultimately determine home range size, but their relative contributions and dynamic nature remain less explored. We investigated the role of habitat selection, movement unrelated to habitat selection and intrinsic factors related to sex in driving space use and home range size in Iberian ibex, Capra pyrenaica. We used GPS collars to track ibex across the year in two different geographical areas of Sierra Nevada, Spain, and measured habitat variables related to forage and roost availability. RESULTS: By using integrated step selection analysis (iSSA), we show that habitat selection was important to explain space use by ibex. As a consequence, movement was constrained by habitat selection, as observed displacement rate was shorter than expected under null selection. Selection-independent movement, selection strength and resource availability were important drivers of seasonal home range size. Both displacement rate and directional persistence had a positive relationship with home range size while accounting for habitat selection, suggesting that individual characteristics and state may also affect home range size. Ibex living at higher altitudes, where resource availability shows stronger altitudinal gradients across the year, had larger home ranges. Home range size was larger in spring and autumn, when ibex ascend and descend back, and smaller in summer and winter, when resources are more stable. Therefore, home range size decreased with resource availability. Finally, males had larger home ranges than females, which might be explained by differences in body size and reproductive behaviour. CONCLUSIONS: Movement, selection strength, resource availability and intrinsic factors related to sex determined home range size of Iberian ibex. Our results highlight the need to integrate and account for process dependencies, here the interdependence of movement and habitat selection, to understand how animals use space. This study contributes to understand how movement links environmental and geographical space use and determines home range behaviour in large herbivores.

Effect of Climate Change on Mediterranean Winter Ranges of Two Migratory Passerines.

We studied the effect of climate change on the distribution of two insectivorous passerines (the meadow pipit Anthus pratensis and the chiffchaff Phylloscopus collybita) in wintering grounds of the Western Mediterranean basin. In this region, precipitation and temperature can affect the distribution of these birds through direct (thermoregulation costs) or indirect effects (primary productivity). Thus, it can be postulated that projected climate changes in the region will affect the extent and suitability of their wintering grounds. We studied pipit and chiffchaff abundance in several hundred localities along a belt crossing Spain and Morocco and assessed the effects of climate and other geographical and habitat predictors on bird distribution. Multivariate analyses reported a positive effect of temperature on the present distribution of the two species, with an additional effect of precipitation on the meadow pipit. These climate variables were used with Maxent to model the occurrence probabilities of species using ring recoveries as presence data. Abundance and occupancy of the two species in the study localities adjusted to the distribution models, with more birds in sectors of high climate suitability. After validation, these models were used to forecast the distribution of climate suitability according to climate projections for 2050-2070 (temperature increase and precipitation reduction). Results show an expansion of climatically suitable sectors into the highlands by the effect of warming on the two species, and a retreat of the meadow pipit from southern sectors related to rain reduction. The predicted patterns show a mean increase in climate suitability for the two species due to the warming of the large highland expanses typical of the western Mediterranean.