The spread of a new highly pathogenic avian influenza virus (HPAIV‐H5N1) has, since 2021, triggered one of the most severe wildlife panzootic ever reported, with suspected population crashes in hundreds of bird and mammal species. However, to date no studies have evaluated the demographic mechanisms underlying these declines. We used Integrated Population Modelling (IPM) along with Bayesian population forecasting and resilience analysis, to evaluate the impact of HPAIV‐H5N1 on age‐structured survival, productivity, stage‐specific population dynamics and demographic resilience in a long‐lived bird, the peregrine falcon ( Falco peregrinus ), in the Netherlands. Our analyses revealed drastic declines in adult survival—the key driver of population dynamics in a long‐lived species—in 2022 and 2023, coinciding with a ~25% decline in breeding pairs. This suggests a shift in HPAIV dynamics compared to previous epizootics, with recurrent outbreaks during consecutive seasons and years, resulting in potentially stronger population impacts. Resilience analysis revealed that HPAIV outbreaks could cause long‐lasting demographic impacts in the population. The breeding population could take a decade to recover to pre‐panzootic levels and may ultimately stabilize at ~21% below its former size. Recovery could take longer if HPAIV outbreaks become more frequent in the future, which is likely under current epidemiological predictions. Synthesis and applications . Our findings demonstrate that the HPAIV panzootic can cause rapid and long‐lasting impacts on the dynamics of long‐lived species. This raises major concerns for the conservation and long‐term viability of the many severely affected long‐lived species worldwide. As wildlife disease is predicted to become a leading cause of biodiversity loss, a global‐scale conservation strategy is urgently needed, which includes improved management, surveillance and applied research efforts. Our combined use of IPMs, forecasts and resilience analyses also serves as a benchmark for evaluating the effects not only of zoonotics, but also of any other type of disturbance in wild populations.

The increasing ecological costs and constraints facing large carnivores, driven by habitat loss, poaching and human–wildlife conflict, represent a major challenge for global conservation. Although tigers have received significant conservation attention, knowledge gaps remain regarding their fundamental biology, including how they differ from sympatric carnivores such as leopards in habitat use and ecological requirements. We studied these two species across Bhutan's mosaic of protected and non-protected areas, using camera trap data from the second National Tiger Survey (2021–2022). We applied a scale-optimised spatial hierarchical occupancy model to examine habitat use by tigers and leopards, compare their ecological niches, and assess their co-occurrence patterns.Tigers were estimated to occupy 7359 km2 (∼19% of Bhutan), whereas leopards occupied 15,842 km2 (∼41%), reflecting their broader distribution and Bhutan's disproportionate contribution to the global ranges of both species. For tigers, maintaining the ecological integrity of existing protected areas is more critical than expanding their coverage. Conservation strategies should prioritise core habitats and connectivity beyond protected areas and across multi-use landscapes, while addressing developmental pressures. In contrast, higher leopard occupancy in non-protected, human-modified landscapes, highlights their adaptability but also signals greater risks of human–carnivore conflict. We recommend community-driven coexistence frameworks tailored to species-specific ecological and socio-economic contexts. Building on its strong conservation ethos, Bhutan is well-positioned to lead multidisciplinary strategies that secure the long-term persistence of both species while contributing to biodiversity gains regionally and globally.

ABSTRACT Montane species are predicted to respond to climate change by moving upslope, particularly high elevation specialists with thermal niches adapted to cold environments. Unfortunately, the accuracy of predictive species distribution models is often reduced by (1) the challenge of accounting for changes in habitat and resource availability and (2) the inability to account for complex life history strategies. Here we use the Wallcreeper (Tichodroma muraria) as a model species for predicting the response of high elevation specialists to climate change, leveraging unique aspects of its ecology as an obligate cliff specialist and altitudinal migrant. Using species distribution models based on citizen science data collected across Switzerland and intensive field surveys of abundance within its core range, we predict future range shifts and overlap among life cycle periods under different climate change scenarios. Principal environmental predictors varied among seasons, with temperature being more important during the winter. While the breeding range was predicted to shift upwards with little change in overall spatial extent, the overwintering range was predicted to expand upslope by up to 244%, leading to a 123% increase in seasonal overlap. Abundance models showed similar results while also providing the first robust density estimates for the species in Switzerland. In contrast to past studies of alpine biota that predict severe range contractions due to climate change, sufficient high elevation habitat exists in Switzerland to allow the Wallcreeper to shift and expand its range upslope, especially in the overwintering period when cold thermal constraints are relaxed. However, most of the current Wallcreeper distribution in Europe lies in mountain ranges likely to be outside of its breeding thermal range in the future, stressing the importance of the Swiss Alps as a stronghold for this species and alpine diversity in an era of rapidly warming temperatures.

Knowledge about spatial variation in survival is central to understanding population dynamics and guiding conservation, yet assessing it is very hard. This limitation arises because capture-mark-recapture (CMR) data required for such inference must be collected over large spatial extents, which is logistically demanding and seldom possible. By contrast, territory occupancy (TO) data are typically spatially rich and widely available for territorial species, but they do not directly inform individual survival. We developed an integrated model combining CMR and TO data. The model links site-level occupancy dynamics, governed by site persistence and colonization probabilities, to survival of the territory owner, allowing both data sources to jointly inform spatiotemporal variation in survival. To accommodate potential violations of this deterministic occupancy-survival link arising from breeding dispersal or alternative rescue dynamics, we included an estimable scaling parameter (κ). We evaluated model performance using simulation across different survival structures (constant, spatial, spatiotemporal), life histories, and CMR detection probabilities, and assessed robustness of inference when the occupancy-survival link is violated. We applied the model to long-term peregrine falcon (Falco peregrinus) data in Hungary, evaluating the effects on survival of the presence of a predator (eagle owl), and the proportion of agricultural land. Survival estimated with the integrated model showed negligible bias and good coverage across all simulation scenarios, while substantially improving precision relative to CMR-only analyses. Precision gains were largest for spatial regression coefficients (up to 80%) and temporal variance parameters (up to 88%); they increased with model complexity and declining detection probability. When the occupancy-survival link was violated, κ absorbed the resulting discrepancy and prevented bias in survival. In the case study, integration substantially improved the precision of spatiotemporal survival estimates and revealed a negative association with eagle owl presence and a positive one with the proportion of agricultural land. Our new integrated model improves estimation of spatial and temporal variation in survival by leveraging shared information across data sources, extending spatially explicit demographic inference to systems where CMR data alone are insufficient, and thereby allowing spatial survival inference in a broader range of populations.

The disappearance of the breeding population of Peregrine Falcon Falco peregrinus from Hungary in 1964 is likely to have been caused by extensive agricultural use of organochlorine pesticides. After proving harmful to humans and wildlife, organochlorine pesticides were banned in North America and many European countries, leading to a recovery in Peregrine populations and other raptors in most parts of the world. In Hungary, Peregrines returned as a breeding species in 1997. Using 26 years (1997-2022) of monitoring data, we investigated spatio-temporal patterns in site occupancy and reproductive success during population recovery. We found that: (i) Peregrines initially re-occupied traditional territories in mountainous and forested regions where suitable nest-sites were available on cliffs and in quarries; (ii) the Peregrine population then slowly expanded to lower elevations, predominantly agricultural areas, where they nested in trees and in artificial nest-sites on pylons; (iii) the overall mean (se) probability of successful nesting was 0.713 +/- 0.02 and the average brood size (number of young per successful nesting attempt) was 2.56 +/- 0.04, with spatial and temporal variation in both measures of reproductive success; (iv) March precipitation had a negative effect on brood size in the wettest region; (v) higher greenness levels in February negatively affected nesting success in the least forested region; and, finally, (vi) Peregrines breeding in artificial nestboxes on pylons had higher nesting success than pairs breeding in natural nests. Our results suggest that the general recovery pattern of Hungarian Peregrines was similar to those observed in other parts of Europe, but also highlight spatial variation in demographic parameters. A v & aacute;ndors & oacute;lyom (Falco peregrinus) magyarorsz & aacute;gi k & ouml;lt & odblac;& aacute;llom & aacute;nya 1964-ben t & udblac;nt el, feltehet & odblac;en az intenz & iacute;v mez & odblac;gazdas & aacute;gi termel & eacute;s sor & aacute;n alkalmazott szerves kl & oacute;rtartalm & uacute; n & ouml;v & eacute;nyv & eacute;d & odblac;szerek k & ouml;vetkezt & eacute;ben. Miut & aacute;n bebizonyosodott, hogy ezek a szerek k & aacute;rosak az emberre & eacute;s a vadon & eacute;l & odblac; & aacute;llatokra, & Eacute;szak-Amerik & aacute;ban & eacute;s sz & aacute;mos eur & oacute;pai orsz & aacute;gban betiltott & aacute;k & odblac;ket, aminek eredm & eacute;nyek & eacute;ppen helyre & aacute;lltak a v & aacute;ndors & oacute;lyom- & eacute;s m & aacute;s ragadoz & oacute;mad & aacute;r-fajok popul & aacute;ci & oacute;i a vil & aacute;g legt & ouml;bb r & eacute;sz & eacute;n. Magyarorsz & aacute;gon a v & aacute;ndors & oacute;lyom 1997-ben t & eacute;rt vissza f & eacute;szkel & odblac; fajk & eacute;nt. Huszon & ouml;t & eacute;v (1997-2022) megfigyel & eacute;si adatai alapj & aacute;n vizsg & aacute;ltuk a f & eacute;szkel & odblac;hely-foglal & aacute;s & eacute;s a szaporod & aacute;si siker t & eacute;rbeli & eacute;s id & odblac;beli mint & aacute;zatait a popul & aacute;ci & oacute; helyre & aacute;ll & aacute;sa sor & aacute;n. Meg & aacute;llap & iacute;tottuk, hogy (i) a v & aacute;ndors & oacute;lymok kezdetben a hagyom & aacute;nyos, hegyvid & eacute;ki & eacute;s erd & odblac;s & eacute;l & odblac;helyeket foglalt & aacute;k vissza, ahol megfelel & odblac; f & eacute;szkel & odblac;helyek & aacute;lltak rendelkez & eacute;sre szikl & aacute;kon & eacute;s k & odblac;b & aacute;ny & aacute;kban; (ii) ezt k & ouml;vet & odblac;en az & aacute;llom & aacute;ny lassan kih & uacute;z & oacute;dott az alacsonyabban fekv & odblac;, f & odblac;k & eacute;nt mez & odblac;gazdas & aacute;gi m & udblac;vel & eacute;s alatt & aacute;ll & oacute; ter & uuml;letekre, ahol f & aacute;kon vagy mesters & eacute;ges f & eacute;szkel & odblac;helyeken (pl. t & aacute;vvezet & eacute;k-oszlopokon) k & ouml;lt & ouml;ttek; (iii) az & aacute;tlagos k & ouml;lt & eacute;si siker 71,3 +/- 0,02%, a fi & oacute;kasz & aacute;m (a fi & oacute;k & aacute;k & aacute;tlaga a sikeres k & ouml;lt & eacute;sekre vonatkoztatva) 2,56 +/- 0,04 volt; mindk & eacute;t mutat & oacute; t & eacute;rbeli & eacute;s id & odblac;beli v & aacute;ltoz & eacute;konys & aacute;got mutatott; (iv) a m & aacute;rciusi csapad & eacute;k negat & iacute;v hat & aacute;st gyakorolt a fi & oacute;kasz & aacute;mra a legcsapad & eacute;kosabb r & eacute;gi & oacute;ban; (v) a febru & aacute;ri magasabb veget & aacute;ci & oacute;s index (greenness) cs & ouml;kkentette a k & ouml;lt & eacute;si sikert a legkev & eacute;sb & eacute; erd & odblac;s ter & uuml;leten V & eacute;g & uuml;l, (vi) a t & aacute;vvezet & eacute;k-oszlopokon, mesters & eacute;ges f & eacute;szekl & aacute;d & aacute;kban k & ouml;lt & odblac; p & aacute;rok k & ouml;lt & eacute;si sikere magasabb volt, mint a term & eacute;szetes f & eacute;szkekben k & ouml;lt & odblac;k & eacute;. Eredm & eacute;nyeink azt mutatj & aacute;k, hogy a magyarorsz & aacute

We introduce the evolving categories multinomial (ECM) distribution for multivariate count data taken over time. This distribution models the counts of individuals following iid stochastic dynamics among categories, with the number and identity of the categories also evolving over time. We specify the one-time and two-times marginal distributions of the counts and the first and second order moments. When the total number of individuals is unknown, placing a Poisson prior on it yields a new distribution (ECM-Poisson), whose main properties we also describe. Since likelihoods are intractable or impractical, we propose two estimating functions for parameter estimation: a Gaussian pseudo-likelihood and a pairwise composite likelihood. We show two application scenarios: the inference of movement parameters of animals moving continuously in space-time with irregular survey regions, and the inference of vote transfer in two-rounds elections. We give three illustrations: a simulation study with Ornstein-Uhlenbeck moving individuals, paying special attention to the autocorrelation parameter; the inference of movement and behavior parameters of lesser prairie-chickens; and the estimation of vote transfer in the 2021 Chilean presidential election.

Understanding and accurately predicting species distribution dynamics is essential for effective biodiversity conservation and management. Spatial dynamic occupancy models (SpDynOcc models) provide a valuable framework for analyzing temporal changes in species occurrence but require substantial data, making it critical to understand their data needs for reliable estimates. In this study, we use a simulation approach to investigate the role of survey effort, both in terms of study duration and spatial coverage, in obtaining accurate predictions from a generic SpDynOcc model. We also test the efficacy of two alternative sampling designs compared to random sampling. We varied multiple factors influencing species occurrence and detection (initial occupancy, occupancy dynamics, and probability of detection) to study the way in which they affect the data requirements for accurate parameter estimation. Models performed best with longer study durations, higher spatial coverage, and higher effective probability of detection (i.e., over all survey occasions). Nevertheless, the specific minimum sampling coverage needed notably varied based on initial occupancy and on occupancy dynamics scenarios. Preferential habitat sampling performed particularly well for low initial occupancy and high-decrease scenarios. These results indicate that tailored survey strategies are essential and must be informed by the specific ecological context. Our findings provide guidance on the survey designs needed to obtain accurate SpDynOcc model predictions, aiding researchers in the effective application of these models for studying species spatial occupancy dynamics.

Generalized distance sampling (GDS) models are the distance sampling equivalent of temporary emigration N-mixture models. In addition to density and the perceptibility component of detection, both contain an additional parameter for availability for detection which becomes estimable when data from repeated 'visits' are available. GDS models thus account for open populations. This makes them more robust, since natural populations are hardly ever perfectly closed, arguably even over the course of a single breeding season. However, the performance of these models has not been tested thoroughly and prior (unpubl.) analyses suggested that biased estimates, especially for density (high) and availability (low), may typically occur under certain conditions. We conducted three simulation studies and found that bias arises in low-information scenarios, particularly with low sample sizes and low parameter values. Our simulations enable us to determine 'estimation frontiers', which separate satisfactory from unsatisfactory estimation performance. Typically, 4-5 replicates, 100-200 sites, and specific combinations of parameter values - particularly those linked to availability and detection probability - are required for reliable estimates. We found that inclusion of covariates in the models could improve estimates in some situations by reducing the incidence of extreme estimates. One novel result from our simulations is that while density and availability may be non-identifiable under some combinations of sample size and for certain parameter values, their product (i.e. the density of the available population) may be more reliably inferred. Our findings provide important insights for study design and for obtaining and interpreting abundance estimates in models with temporary emigration, all with important implications for ecology and wildlife management.

Reintroduction is a widely used management tool for restoring wildlife populations, with the goal of creating functional and self-sustaining populations. Evaluating the success or failure of such programmes requires a thorough understanding of the dynamics of the reintroduced population. The Iberian lynx (Lynx pardinus), an iconic conservation flagship species, illustrates the value of reintroduction initiatives. On the brink of extinction 25 years ago, this species has now recovered thanks to intensive conservation management. However, the demography underlying the dynamics of the reintroduced Iberian lynx populations is poorly known, which hinders future management decisions. Using data from camera trapping and radio-tagging, we reviewed the reintroduced population in Extremadura, Spain (2014-2024), using an integrated population model (IPM). We conducted both retrospective and prospective analyses to identify the demographic drivers of population growth and evaluate management scenarios using IPM-based population viability analysis (PVA). In 2024, 10 years after the reintroduction began, the Extremadura population was estimated at 164 individuals (95% CRI: 141-189), including 28 breeding females. Female population size was regulated by density-dependence, driven by subadult dispersal leading to increased roadkill mortality. During the early stages of the reintroduction programme, variation in population structure was the main driver of changes in growth rate. However, as the population increased, adult survival and recruitment became the dominant contributors to population dynamics. Meanwhile, female breeding propensity and litter size remained stable, having limited effects on growth rate variability. PVA projections suggest that the lynx population will stabilize around 32 breeding females within the next 15 years. To increase the stationary population size, it is necessary to improve habitats to increase the number of breeding territories and reduce roadkill mortality. Synthesis and applications. Demographic performance reviews are essential for understanding the drivers of population growth and for evaluating the outcomes of reintroduction initiatives. IPMs as exemplified by our Iberian lynx case study provide a powerful and flexible framework for quantifying reintroduction performance and addressing key research and management questions. By using insights from demography, conservation practitioners can better guide effective management strategies and ensure the long-term viability of restored populations. La reintroducci & oacute;n es una herramienta de gesti & oacute;n ampliamente utilizada para restaurar poblaciones de fauna silvestre, con el objetivo de crear poblaciones funcionales y autosuficientes. Evaluar el & eacute;xito o el fracaso de estos programas requiere un conocimiento profundo de la din & aacute;mica de la poblaci & oacute;n reintroducida. El lince ib & eacute;rico (Lynx pardinus), una especie emblem & aacute;tica en conservaci & oacute;n, ejemplifica el valor de las iniciativas de reintroducci & oacute;n. Al borde de la extinci & oacute;n hace 25 a & ntilde;os, esta especie se ha recuperado gracias a una gesti & oacute;n de conservaci & oacute;n intensiva. Sin embargo, la demograf & iacute;a que subyace en la din & aacute;mica de las poblaciones reintroducidas sigue siendo poco conocida, lo que complica las decisiones de gesti & oacute;n futuras. Utilizando datos de c & aacute;maras trampa y radiomarcaje, hemos analizado la poblaci & oacute;n reintroducida en Extremadura, Espa & ntilde;a (2014-2024), mediante un modelo de poblaci & oacute;n integrado (IPM). Hemos realizado an & aacute;lisis retrospectivos y prospectivos para identificar los factores demogr & aacute;ficos que impulsan el crecimiento de la poblaci & oacute;n y para evaluar los escenarios de gesti & oacute;n, utilizando un an & aacute;lisis de viabilidad de la poblaci & oacute;n (PVA) basado en IPM. En 2024, diez a & ntilde;os despu & eacute;s del inicio de la reintroducci & oacute;n, la poblaci & oacute;n de lince ib & eacute;rico en Extremadura se estim & oacute; en 164 individuos (95% CRI: 141-189), incluidas 28 hembras reproductoras. Mostramos como la regulaci & oacute;n del tama & ntilde;o poblacional de hembras fue denso-dependiente, impulsada por la dispersi & oacute;n de subadultos, lo que deriv & oacute; en un incremento de la mortalidad por atropellos. Durante las primeras etapas del programa de reintroducci & oacute;n, la variaci & oacute;n en la estructura de la poblaci & oacute;n fue el principal factor que determin & oacute; los cambios en la tasa de crecimiento. Sin embargo, a medida que la poblaci & oacute;n aument & oacute;, la supervivencia y el reclutamiento de los adultos se convirtieron en los factores que m & aacute;s contribuyeron a la din & aacute;mica de la poblaci & oacute;n. Durante el estudio, la propensi & oacute;n a la reproducci & oacute;n de las hembras y el tama & ntilde;o de las camadas se mantuvieron estables, con efectos limitados sobre la variabilidad de la tasa de crecimiento. Las proyecciones del PVA sugieren que la poblaci & oacute;n de linces se estabilizar & aacute; en torno a 32 hembras reproductoras en los pr & oacute;ximos 15 a & ntilde;os. Para aumentar el tama & ntilde;o de la poblaci & oacute;n estacionaria, ser & iacute;a necesario realizar mejoras de h & aacute;bitat con el fin de aumentar los territorios reproductores y adem & aacute;s reducir la mortalidad por atropello. S & iacute;ntesis y aplicaciones. Los an & aacute;lisis del rendimiento demogr & aacute;fico son esenciales para comprender los factores que impulsan el crecimiento de la poblaci & oacute;n y para evaluar los resultados de las iniciativas de reintroducci & oacute;n. Los IPM, como lo ejemplifica nuestro caso de estudio con el lince ib & eacute;rico, proporcionan un marco potente y flexible para cuantificar el rendimiento de la reintroducci & oacute;n, y abordar cuestiones clave de investigaci & oacute;n y gesti & oacute;n. Al utilizar los conocimientos de

The Swiss Common Breeding Bird Monitoring ("Monitoring Häufige Brutvögel" MHB) is a long-term study organized by the Swiss Ornithological Institute. Its main goal is to collect data for estimating breeding population trends of relatively abundant and widespread species. Since 1999, 267 one-km squares laid out in a mostly systematic grid across all of Switzerland have been surveyed annually by skilled, mostly volunteer ornithologists. The sampling sites thus cover a wide range of typical Western European habitats, and an altitudinal range from 250 up to 2750 m above sea level. Bird populations are recorded using a simplified territory mapping protocol with two visits per square above the timberline and three elsewhere. Surveys are conducted during the breeding season (mid-April to early July) along a square-specific transect route that does not change over the years. A typical transect route is between 4 and 6 km long, and each visit usually lasts 3 to 4 h. The location of all visually or acoustically detected birds is recorded on topographical maps or using a smartphone app. Records that meet predefined criteria in terms of species-specific breeding period and observed behavior are retained for the subsequent step of territory delimitation. This is done automatically for most species by the program Autoterri since 2022 and was done manually before, with subsequent checks by an expert. This process finally results in an estimate of the total number of detected territories per species, square and year. The design also explicitly generates detection histories, consisting of two to three numbers that represent the number of territories found to be occupied during each respective visit, enabling the analysis with binomial N-mixture and site-occupancy models. The dataset currently covers the breeding seasons from 1999 to 2024 and includes 6852 site-by-year combinations with estimates of detected territory numbers. It covers 162 of the 166 bird species recorded at least once as potential breeders, excluding four species to prevent potential disturbance at nesting sites. Besides informing about population trends, data from the Swiss Common Breeding Bird Monitoring were used to illustrate several methodological developments in N-mixture, occupancy and related models and to answer scientific and applied questions. With its clearly defined survey method, the largely systematic distribution of its survey sites, and the long timespan covered, it is likely that this dataset will continue to make important contributions in biological and biostatistical research. Herewith, we make the annually updated data set available with a CC BY 4.0 license, allowing researchers and conservationists to use and analyze the data for their own research and conservation efforts.

Point counts (PCs) are widely used in biodiversity surveys, but despite numerous advantages, simple PCs suffer from several problems: detectability, and therefore abundance, is unknown; systematic spatiotemporal variation in detectability produces biased inferences, and unknown survey area prevents formal density estimation and scaling-up to the landscape level. We introduce integrated distance sampling (IDS) models that combine distance sampling (DS) with simple PC or detection/nondetection (DND) data and capitalize on the strengths and mitigate the weaknesses of each data type. Key to IDS models is the view of simple PC and DND data as aggregations of latent DS surveys that observe the same underlying density process. This enables estimation of separate detection functions, along with distinct covariate effects, for all data types. Additional information from repeat or time-removal surveys, or variable survey duration, enables separate estimation of the availability and perceptibility components of detectability. IDS models reconcile spatial and temporal mismatches among data sets and solve the above-mentioned problems of simple PC and DND data. To fit IDS models, we provide JAGS code and the new IDS() function in the R package unmarked. Extant citizen-science data generally lack adjustments for detection biases, but IDS models address this shortcoming, thus greatly extending the utility and reach of these data. In addition, they enable formal density estimation in hybrid designs, which efficiently combine distance sampling with distance-free, point-based PC or DND surveys. We believe that IDS models have considerable scope in ecology, management, and monitoring.

Species distribution models (SDMs) are increasingly applied across macroscales. Such models typically assume that a single set of regression coefficients can adequately describe species-environment relationships and/or population trends. However, such relationships often show nonlinear and/or spatially-varying patterns that arise from complex interactions with abiotic and biotic processes that operate at different scales. Spatially-varying coefficient (SVC) models can readily account for variability in the effects of environmental covariates. Yet, their use in ecology is relatively scarce due to gaps in understanding the inferential benefits that SVC models can provide compared to simpler frameworks. Here we demonstrate the inferential benefits of SVC SDMs, with a particular focus on how this approach can be used to generate and test ecological hypotheses regarding the drivers of spatial variability in population trends and species-environment relationships. We illustrate the inferential benefits of SVC SDMs with simulations and two case studies: one that assesses spatially-varying trends of 51 forest bird species in the eastern US over two decades and a second that evaluates spatial variability in the effects of five decades of land cover change on Grasshopper Sparrow occurrence across the continental US. We found strong support for SVC SDMs compared to simpler alternatives in both empirical case studies. These applications display the utility of SVC SDMs to help reveal the environmental factors that drive species distributions across both local and broad scales. We conclude by discussing the potential applications of SVC SDMs in ecology and conservation.

Integrated fisheries stock assessment models (SAMs) and integrated population models (IPMs) are used in biological and ecological systems to estimate abundance and demographic rates. The approaches are fundamentally very similar, but historically have been considered as separate endeavors, resulting in a loss of shared vision, practice and progress. We review the two approaches to identify similarities and differences, with a view to identifying key lessons that would benefit more generally the overarching topic of population ecology. We present a case study for each of SAM (snapper from the west coast of New Zealand) and IPM (woodchat shrikes from Germany) to highlight differences and similarities. The key differences between SAMs and IPMs appear to be the objectives and parameter estimates required to meet these objectives, the size and spatial scale of the populations, and the differing availability of various types of data. In addition, up to now, typical SAMs have been applied in aquatic habitats, while most IPMs stem from terrestrial habitats. SAMs generally aim to assess the level of sustainable exploitation of fish populations, so absolute abundance or biomass must be estimated, although some estimate only relative trends. Relative abundance is often sufficient to understand population dynamics and inform conservation actions, which is the main objective of IPMs. IPMs are often applied to small populations of conservation concern, where demographic uncertainty can be important, which is more conveniently implemented using Bayesian approaches. IPMs are typically applied at small to moderate spatial scales (1 to 104 km2), with the possibility of collecting detailed longitudinal individual data, whereas SAMs are typically applied to large, economically valuable fish stocks at very large spatial scales (104 to 106 km2) with limited possibility of collecting detailed individual data. There is a sense in which a SAM is more data- (or information-) hungry than an IPM because of its goal to estimate absolute biomass or abundance, and data at the individual level to inform demographic rates are more difficult to obtain in the (often marine) systems where most SAMs are applied. SAMs therefore require more 'tuning' or assumptions than IPMs, where the 'data speak for themselves', and consequently techniques such as data weighting and model evaluation are more nuanced for SAMs than for IPMs. SAMs would benefit from being fit to more disaggregated data to quantify spatial and individual variation and allow richer inference on demographic processes. IPMs would benefit from more attempts to estimate absolute abundance, for example by using unconditional models for capture-recapture data.