Seasonality, density dependence, and spatial population synchrony.

Studies of spatial population synchrony constitute a central approach for understanding the drivers of ecological dynamics. Recently, identifying the ecological impacts of climate change has emerged as a new important focus in population synchrony studies. However, while it is well known that climatic seasonality and sequential density dependence influences local population dynamics, the role of season-specific density dependence in shaping large-scale population synchrony has not received attention. Here, we present a widely applicable analytical protocol that allows us to account for both season and geographic context-specific density dependence to better elucidate the relative roles of deterministic and stochastic sources of population synchrony, including the renowned Moran effect. We exemplify our protocol by analyzing time series of seasonal (spring and fall) abundance estimates of cyclic rodent populations, revealing that season-specific density dependence is a major component of population synchrony. By accounting for deterministic sources of synchrony (in particular season-specific density dependence), we are able to identify stochastic components. These stochastic components include mild winter weather events, which are expected to increase in frequency under climate warming in boreal and Arctic ecosystems. Interestingly, these weather effects act both directly and delayed on the vole populations, thus enhancing the Moran effect. Our study demonstrates how different drivers of population synchrony, presently altered by climate warming, can be disentangled based on seasonally sampled population time-series data and adequate population models.

Path analysis reveals combined winter climate and pollution effects on the survival of a marine top predator.

Marine ecosystems are experiencing growing pressure from multiple threats caused by human activities, with far-reaching consequences for marine food webs. Determining the effects of multiple stressors is complex, in part, as they can affect different aspects of biological organisation (behaviour, individual traits and demographic rates). Determining the combined effects of stressors, through different biological pathways, is key to predict the consequences for the viability of populations threatened by global change. Due to their position in the food chain, top predators such as seabirds are considered more sensitive to environmental changes. Climate change is affecting the prey resources available for seabirds, through bottom-up effects, while organic pollutants can bioaccumulate in food chains with the greatest impacts on top predators. However, knowledge of their combined effects on population dynamics is scarce. Using a path analysis, we quantify the effects of climate change and pollution on the survival of adult great black-backed gulls, both directly and through effects of individuals' body mass. Warmer ocean temperatures in gulls' winter foraging areas in the North Sea were correlated with higher survival, potentially explained by shifts in prey availability associated with global climate change. We also found support for indirect negative effects of organochlorines, highly toxic pollutants to seabirds, on survival, which acted, in part, through a negative effect on body mass. The results from this path analysis highlight how, even for such long-lived species where variance in survival tends to be limited, two stressors still have had a marked influence on adult survival and illustrate the potential of path models to improve predictions of population variability under multiple stressors.

Climate variability and density-dependent population dynamics: Lessons from a simple High Arctic ecosystem.

Ecologists are still puzzled by the diverse population dynamics of herbivorous small mammals that range from high-amplitude, multiannual cycles to stable dynamics. Theory predicts that this diversity results from combinations of climatic seasonality, weather stochasticity, and density-dependent food web interactions. The almost ubiquitous 3- to 5-y cycles in boreal and arctic climates may theoretically result from bottom-up (plant-herbivore) and top-down (predator-prey) interactions. Assessing, empirically, the roles of such interactions and how they are influenced by environmental stochasticity has been hampered by food web complexity. Here, we take advantage of a uniquely simple High Arctic food web, which allowed us to analyze the dynamics of a graminivorous vole population not subjected to top-down regulation. This population exhibited high-amplitude, noncyclic fluctuations-partly driven by weather stochasticity. However, the predominant driver of the dynamics was overcompensatory density dependence in winter that caused the population to frequently crash. Model simulations showed that the seasonal pattern of density dependence would yield regular 2-y cycles in the absence of stochasticity. While such short cycles have not yet been observed in mammals, they are theoretically plausible if graminivorous vole populations are deterministically bottom-up regulated. When incorporating weather stochasticity in the model simulations, cyclicity became disrupted and the amplitude was increased-akin to the observed dynamics. Our findings contrast with the 3- to 5-y population cycles that are typical of graminivorous small mammals in more complex food webs, suggesting that top-down regulation is normally an important component of such dynamics.

Panel-based assessment of ecosystem condition as a platform for adaptive and knowledge driven management.

Ecosystems are subjected to increasing exposure to multiple anthropogenic drivers. This has led to the development of national and international accounting systems describing the condition of ecosystems, often based on few, highly aggregated indicators. Such accounting systems would benefit from a stronger theoretical and empirical underpinning of ecosystem dynamics. Operational tools for ecosystem management require understanding of natural ecosystem dynamics, consideration of uncertainty at all levels, means for quantifying driver-response relationships behind observed and anticipated future trajectories of change, and an efficient and transparent synthesis to inform knowledge-driven decision processes. There is hence a gap between highly aggregated indicator-based accounting tools and the need for explicit understanding and assessment of the links between multiple drivers and ecosystem condition as a foundation for informed and adaptive ecosystem management. We describe here an approach termed PAEC (Panel-based Assessment of Ecosystem Condition) for combining quantitative and qualitative elements of evidence and uncertainties into an integrated assessment of ecosystem condition at spatial scales relevant to management and monitoring. The PAEC protocol is founded on explicit predictions, termed phenomena, of how components of ecosystem structure and functions are changing as a result of acting drivers. The protocol tests these predictions with observations and combines these tests to assess the change in the condition of the ecosystem as a whole. PAEC includes explicit, quantitative or qualitative, assessments of uncertainty at different levels and integrates these in the final assessment. As proofs-of-concept we summarize the application of the PAEC protocol to a marine and a terrestrial ecosystem in Norway.

Raising offspring increases ageing: Differences in senescence among three populations of a long-lived seabird, the Atlantic puffin.

Actuarial senescence, the decline of survival with age, is well documented in the wild. Rates of senescence vary widely between taxa, to some extent also between sexes, with the fastest life histories showing the highest rates of senescence. Few studies have investigated differences in senescence among populations of the same species, although such variation is expected from population-level differences in environmental conditions, leading to differences in vital rates and thus life histories. We predict that, within species, populations differing in productivity (suggesting different paces of life) should experience different rates of senescence, but with little or no sexual difference in senescence within populations of monogamous, monomorphic species where the sexes share breeding duties. We compared rates of actuarial senescence among three contrasting populations of the Atlantic puffin Fratercula arctica. The dataset comprised 31 years (1990-2020) of parallel capture-mark-recapture data from three breeding colonies, Isle of May (North Sea), Røst (Norwegian Sea) and Hornøya (Barents Sea), showing contrasting productivities (i.e. annual breeding success) and population trends. We used time elapsed since first capture as a proxy for bird age, and productivity and the winter North Atlantic Oscillation Index (wNAO) as proxies for the environmental conditions experienced by the populations within and outside the breeding season, respectively. In accordance with our predictions, we found that senescence rates differed among the study populations, with no evidence for sexual differences. There was no evidence for an effect of wNAO, but the population with the lowest productivity, Røst, showed the lowest rate of senescence. As a consequence, the negative effect of senescence on the population growth rate (λ) was up to 3-5 times smaller on Røst (Δλ = -0.009) than on the two other colonies. Our findings suggest that environmentally induced differences in senescence rates among populations of a species should be accounted for when predicting effects of climate variation and change on species persistence. There is thus a need for more detailed information on how both actuarial and reproductive senescence influence vital rates of populations of the same species, calling for large-scale comparative studies.

Life history adaptations to fluctuating environments: Combined effects of demographic buffering and lability.

Demographic buffering and lability have been identified as adaptive strategies to optimise fitness in a fluctuating environment. These are not mutually exclusive, however, we lack efficient methods to measure their relative importance for a given life history. Here, we decompose the stochastic growth rate (fitness) into components arising from nonlinear responses and variance-covariance of demographic parameters to an environmental driver, which allows studying joint effects of buffering and lability. We apply this decomposition for 154 animal matrix population models under different scenarios to explore how these main fitness components vary across life histories. Faster-living species appear more responsive to environmental fluctuations, either positively or negatively. They have the highest potential for strong adaptive demographic lability, while demographic buffering is a main strategy in slow-living species. Our decomposition provides a comprehensive framework to study how organisms adapt to variability through buffering and lability, and to predict species responses to climate change.

Temporal correlations among demographic parameters are ubiquitous but highly variable across species.

Temporal correlations among demographic parameters can strongly influence population dynamics. Our empirical knowledge, however, is very limited regarding the direction and the magnitude of these correlations and how they vary among demographic parameters and species' life histories. Here, we use long-term demographic data from 15 bird and mammal species with contrasting pace of life to quantify correlation patterns among five key demographic parameters: juvenile and adult survival, reproductive probability, reproductive success and productivity. Correlations among demographic parameters were ubiquitous, more frequently positive than negative, but strongly differed across species. Correlations did not markedly change along the slow-fast continuum of life histories, suggesting that they were more strongly driven by ecological than evolutionary factors. As positive temporal demographic correlations decrease the mean of the long-run population growth rate, the common practice of ignoring temporal correlations in population models could lead to the underestimation of extinction risks in most species.

From design to analysis: A roadmap for predicting distributions of rare species.

Rare species are challenging to study, in part because rarity can take many forms. Jeliazkov et al. guide us through the multiple decisions to be made-from sampling designs to field methods and analytical, integrated models. Improved monitoring methods are needed to improve our understanding of rare species importance for ecosystem structure and functions. This is a commentary on Jeliazkov et al., 2022, https://doi.org/10.1111/gcb.16114.

Detecting climate signals in populations across life histories.

Climate impacts are not always easily discerned in wild populations as detecting climate change signals in populations is challenged by stochastic noise associated with natural climate variability, variability in biotic and abiotic processes, and observation error in demographic rates. Detection of the impact of climate change on populations requires making a formal distinction between signals in the population associated with long-term climate trends from those generated by stochastic noise. The time of emergence (ToE) identifies when the signal of anthropogenic climate change can be quantitatively distinguished from natural climate variability. This concept has been applied extensively in the climate sciences, but has not been explored in the context of population dynamics. Here, we outline an approach to detecting climate-driven signals in populations based on an assessment of when climate change drives population dynamics beyond the envelope characteristic of stochastic variations in an unperturbed state. Specifically, we present a theoretical assessment of the time of emergence of climate-driven signals in population dynamics ( ToE pop ). We identify the dependence of ToE pop on the magnitude of both trends and variability in climate and also explore the effect of intrinsic demographic controls on ToE pop . We demonstrate that different life histories (fast species vs. slow species), demographic processes (survival, reproduction), and the relationships between climate and demographic rates yield population dynamics that filter climate trends and variability differently. We illustrate empirically how to detect the point in time when anthropogenic signals in populations emerge from stochastic noise for a species threatened by climate change: the emperor penguin. Finally, we propose six testable hypotheses and a road map for future research.

Nonlinear spatial and temporal decomposition provides insight for climate change effects on sub-Arctic herbivore populations.

Global temperatures are increasing, affecting timing and availability of vegetation along with relationships between plants and their consumers. We examined the effect of population density, herd body condition in the previous year, elevation, plant productivity and phenology, snow, and winter onset on juvenile body mass in 63 semi-domesticated populations of Rangifer tarandus throughout Norway using spatiotemporal generalized additive models (GAMs) and varying coefficient models (VCMs). Optimal climate windows were calculated at both the regional and national level using a novel nonlinear climate window algorithm optimized for prediction. Spatial and temporal variation in effects of population and environmental predictors were considered using a model including covariates decomposed into spatial, temporal, and residual components. The performance of this decomposed model was compared to spatiotemporal GAMs and VCMs. The decomposed model provided the best fit and lowest prediction errors. A positive effect of herd body condition in the previous year explained most of the deviance in calf body mass, followed by a more complex effect of population density. A negative effect of timing of spring and positive effect of winter onset on juvenile body mass suggested that a snow free season was positive for juvenile body mass growth. Our findings suggest early spring onset and later winter permanent snow cover as reinforcers of early-life conditions which support more robust reindeer populations. Our methodological improvements for climate window analyses and effect size measures for decomposed variables provide important contributions to account for, measure, and interpret nonlinear relationships between climate and animal populations at large scales.

Centennial relationships between ocean temperature and Atlantic puffin production reveal shifting decennial trends.

The current warming of the oceans has been shown to have detrimental effects for a number of species. An understanding of the underlying mechanisms may be hampered by the non-linearity and non-stationarity of the relationships between temperature and demography, and by the insufficient length of available time series. Most demographic time series are too short to study the effects of climate on wildlife in the classical sense of meteorological patterns over at least 30 years. Here we present a harvest time series of Atlantic puffins (Fratercula arctica) that goes back as far as 1880. It originates in the world's largest puffin colony, in southwest Iceland, which has recently experienced a strong decline. By estimating an annual chick production index for 128 years, we found prolonged periods of strong correlations between local sea surface temperature (SST) and chick production. The sign of decennial correlations switches three times during this period, where the phases of strong negative correlations between puffin productivity and SST correspond to the early 20th century Arctic warming period and to the most recent decades. Most of the variation (72%) in chick production is explained by a model in which productivity peaks at an SST of 7.1°C, clearly rejecting the assumption of a linear relationship. There is also evidence supporting non-stationarity: The SST at which puffins production peaked has increased by 0.24°C during the 20th century, although the increase in average SST during the same period has been more than three times faster. The best supported models indicate that the population's decline is at least partially caused by the increasing SST around Iceland.

The rise of a marine generalist predator and the fall of beta diversity.

Determining the importance of physical and biological drivers in shaping biodiversity in diverse ecosystems remains a global challenge. Advancements have been made towards this end in large marine ecosystems with several studies suggesting environmental forcing as the primary driver. However, both empirical and theoretical studies point to additional drivers of changes in diversity involving trophic interactions and, in particular, predation. Moreover, a more integrated but less common approach to the assessment of biodiversity changes involves analyses of spatial ß diversity, whereas most studies to date assess only changes in species richness (α diversity). Recent research has established that when cod, a dominant generalist predator, was overfished and collapsed in a northwest Atlantic food web, spatial ß diversity increased; that is, the spatial structure of the fish assemblage became increasingly heterogeneous. If cod were to recover, would this situation be reversible, given the inherent complexity and non-linear dynamics that typify such systems? A dramatic increase of cod in an ecologically similar large marine ecosystem may provide an answer. Here we show that spatial ß diversity of fish assemblages in the Barents Sea decreased with increasing cod abundance, while decadal scale changes in temperature did not play a significant role. These findings indicate a reversibility of the fish assemblage structure in response to changing levels of an apex predator and highlight the frequently overlooked importance of trophic interactions in determining large-scale biodiversity patterns. As increased cod abundance was largely driven by changes in fisheries management, our study also shows that management policies and practices, particularly those involving apex predators, can have a strong effect in shaping spatial diversity patterns, and one should not restrict the focus to effects of climate change alone.

End-user involvement to improve predictions and management of populations with complex dynamics and multiple drivers.

Sustainable management of wildlife populations can be aided by building models that both identify current drivers of natural dynamics and provide near-term predictions of future states. We employed a Strategic Foresight Protocol (SFP) involving stakeholders to decide the purpose and structure of a dynamic state-space model for the population dynamics of the Willow Ptarmigan, a popular game species in Norway. Based on local knowledge of stakeholders, it was decided that the model should include food web interactions and climatic drivers to provide explanatory predictions. Modeling confirmed observations from stakeholders that climate change impacts Ptarmigan populations negatively through intensified outbreaks of insect defoliators and later onset of winter. Stakeholders also decided that the model should provide anticipatory predictions. The ability to forecast population density ahead of the harvest season was valued by the stakeholders as it provides the management extra time to consider appropriate harvest regulations and communicate with hunters prior to the hunting season. Overall, exploring potential drivers and predicting short-term future states, facilitate collaborative learning and refined data collection, monitoring designs, and management priorities. Our experience from adapting a SFP to a management target with inherently complex dynamics and drivers of environmental change, is that an open, flexible, and iterative process, rather than a rigid step-wise protocol, facilitates rapid learning, trust, and legitimacy.

Fifty thousand years of Arctic vegetation and megafaunal diet.

Although it is generally agreed that the Arctic flora is among the youngest and least diverse on Earth, the processes that shaped it are poorly understood. Here we present 50 thousand years (kyr) of Arctic vegetation history, derived from the first large-scale ancient DNA metabarcoding study of circumpolar plant diversity. For this interval we also explore nematode diversity as a proxy for modelling vegetation cover and soil quality, and diets of herbivorous megafaunal mammals, many of which became extinct around 10 kyr bp (before present). For much of the period investigated, Arctic vegetation consisted of dry steppe-tundra dominated by forbs (non-graminoid herbaceous vascular plants). During the Last Glacial Maximum (25-15 kyr bp), diversity declined markedly, although forbs remained dominant. Much changed after 10 kyr bp, with the appearance of moist tundra dominated by woody plants and graminoids. Our analyses indicate that both graminoids and forbs would have featured in megafaunal diets. As such, our findings question the predominance of a Late Quaternary graminoid-dominated Arctic mammoth steppe.

Integrated Methods for Monitoring the Invasive Potential and Management of Heracleum mantegazzianum (giant hogweed) in Switzerland.

Biological invasions are a major driver of human-induced global environmental change. This makes monitoring of potential spread, population changes and control measures necessary for guiding management. We illustrate the value of integrated methods (species distribution modelling (SDM), plant population monitoring and questionnaires) for monitoring and assessing invasions of Heracleum mantegazzianum (giant hogweed) over time in Switzerland. SDMs highlighted the potential spread of the species, uncovered ecological mechanisms underlying invasions and guided monitoring at a regional level. We used adaptive and repeat plant sampling to monitor invasive population status and changes, and assess the effectiveness of H. mantegazzianum management over three periods (2005, 2013 and 2018) within the pre-Alps, Vaud. We also conducted questionnaire surveys with managers and the public. Multiscale modelling, and integrating global and regional SDMs, provided the best predictions, showing that H. mantegazzianum can potentially invade large parts of Switzerland, especially below 2 000 m a.s.l. Over time, populations of invasive H. mantegazzianum in the Vaud pre-Alps have declined, which is most likely due to a sharp rise in management uptake post 2007 (7% of municipalities before 2007 to 86% in 2018). The level of known invasive populations has decreased by 54% over time. Some municipalities have even successfully eradicated H. mantegazzianum within their borders. However, a few areas, particularly in the rural, higher-altitude municipalities, where management was not implemented effectively, populations have expanded, which could hamper control efforts at lower altitudes. We provide encouraging evidence that control measures can be effective in reducing plant invasions with long-term commitment, as well as a good template for using integrated methodological approaches to better study and monitor invasive alien species.

Spatial synchrony in sub-arctic geometrid moth outbreaks reflects dispersal in larval and adult life cycle stages.

Spatial synchrony in population dynamics can be caused by dispersal or spatially correlated variation in environmental factors like weather (Moran effect). Distinguishing between these mechanisms is challenging for natural populations, and the study of dispersal-induced synchrony in particular has been dominated by theoretical modelling and laboratory experiments. The goal of the present study was to evaluate the evidence for dispersal as a cause of meso-scale (distances of tens of kilometres) spatial synchrony in natural populations of the two cyclic geometrid moths Epirrita autumnata and Operophtera brumata in sub-arctic mountain birch forest in northern Norway. To infer the role of dispersal in geometrid synchrony, we applied three complementary approaches, namely estimating the effect of design-based dispersal barriers (open sea) on synchrony, comparing the strength of synchrony between E. autumnata (winged adults) and the less dispersive O. brumata (wingless adult females), and relating the directionality (anisotropy) of synchrony to the predominant wind directions during spring, when geometrid larvae engage in windborne dispersal (ballooning). The estimated effect of dispersal barriers on synchrony was almost three times stronger for the less dispersive O. brumata than E. autumnata. Inter-site synchrony was also weakest for O. brumata at all spatial lags. Both observations argue for adult dispersal as an important synchronizing mechanism at the spatial scales considered. Further, synchrony in both moth species showed distinct anisotropy and was most spatially extensive parallel to the east-west axis, coinciding closely to the overall dominant wind direction. This argues for a synchronizing effect of windborne larval dispersal. Congruent with most extensive dispersal along the east-west axis, E. autumnata also showed evidence for a travelling wave moving southwards at a speed of 50-80 km/year. Our results suggest that dispersal processes can leave clear signatures in both the strength and directionality of synchrony in field populations, and highlight wind-driven dispersal as promising avenue for further research on spatial synchrony in natural insect populations.

Earlier colony arrival but no trend in hatching timing in two congeneric seabirds (Uria spp.) across the North Atlantic.

A global analysis recently showed that seabird breeding phenology (as the timing of egg-laying and hatching) does not, on average, respond to temperature changes or advance with time (Keogan et al. 2018 Nat. Clim. Change8, 313-318). This group, the most threatened of all birds, is therefore prone to spatio-temporal mismatches with their food resources. Yet, other aspects of the breeding phenology may also have a marked influence on breeding success, such as the arrival date of adults at the breeding site following winter migration. Here, we used a large tracking dataset of two congeneric seabirds breeding in 14 colonies across 18° latitudes, to show that arrival date at the colony was highly variable between colonies and species (ranging 80 days) and advanced 1.4 days/year while timing of egg-laying remained unchanged, resulting in an increasing pre-laying duration between 2009 and 2018. Thus, we demonstrate that potentially not all components of seabird breeding phenology are insensitive to changing environmental conditions.

Identifying key needs for the integration of social-ecological outcomes in arctic wildlife monitoring.

For effective monitoring in social-ecological systems to meet needs for biodiversity, science, and humans, desired outcomes must be clearly defined and routes from direct to derived outcomes understood. The Arctic is undergoing rapid climatic, ecological, social, and economic changes and requires effective wildlife monitoring to meet diverse stakeholder needs. To identify stakeholder priorities concerning desired outcomes of arctic wildlife monitoring, we conducted in-depth interviews with 29 arctic scientists, policy and decision makers, and representatives of indigenous organizations and nongovernmental organizations. Using qualitative content analysis, we identified and defined desired outcomes and documented links between outcomes. Using network analysis, we investigated the structure of perceived links between desired outcomes. We identified 18 desired outcomes from monitoring and classified them as either driven by monitoring information, monitoring process, or a combination of both. Highly cited outcomes were make decisions, conserve, detect change, disseminate, and secure food. These reflect key foci of arctic monitoring. Infrequently cited outcomes (e.g., govern) were emerging themes. Three modules comprised our outcome network. The modularity highlighted the low strength of perceived links between outcomes that were primarily information driven or more derived (e.g., detect change, make decisions, conserve, or secure food) and outcomes that were primarily process driven or more derived (e.g., cooperate, learn, educate). The outcomes expand monitoring community and disseminate created connections between these modules. Key desired outcomes are widely applicable to social-ecological systems within and outside the Arctic, particularly those with wildlife subsistence economies. Attributes and motivations associated with outcomes can guide development of integrated monitoring goals for biodiversity conservation and human needs. Our results demonstrated the disconnect between information- and process-driven goals and how expansion of the monitoring community and improved integration of monitoring stakeholders will help connect information- and process-derived outcomes for effective ecosystem stewardship.

Identificación de las Necesidades Clave para la Integración de Resultados Socio-Ecológicos en el Monitoreo de Fauna en el Ártico Resumen Para que el monitoreo efectivo en los sistemas socio-ecológicos cumpla con las necesidades de la biodiversidad, la ciencia, y los humanos, se deben definir claramente los resultados deseados y se deben entender las rutas que se toman de los resultados directos hacia los resultados derivados. El Ártico está sufriendo rápidamente cambios climáticos, ecológicos, y económicos, y requiere de un monitoreo efectivo de fauna para cumplir con las necesidades de diversos accionistas. Realizamos entrevistas a profundidad con 29 científicos del Ártico, responsables de decisiones y políticas, y representativos de organizaciones indígenas y organizaciones no gubernamentales para identificar las prioridades de los accionistas con respecto a los resultados deseados del monitoreo de fauna ártica. Mediante un análisis cualitativo de contenido identificamos y definimos los resultados deseados y documentamos las conexiones entre los resultados. Con un análisis de redes investigamos la estructura de las conexiones percibidas y las clasificamos como causadas por el monitoreo de información, el monitoreo del proceso, o una combinación de ambos. Los resultados con un mayor número de menciones fueron tomar decisiones, conservar, detectar cambios, diseminar, y asegurar alimento. Estos reflejan los enfoques más importantes del monitoreo en el Ártico. Los resultados con poca frecuencia en las menciones (p. ej.: regular) correspondían a temas emergentes. Nuestra red de resultados estuvo compuesta por tres módulos. La modularidad resaltó la poca fuerza de las conexiones percibidas entre los resultados que fueron causados principalmente por la información o que estuvieron más derivados (p. ej.: detectar el cambio, tomar decisiones, conservar o asegurar alimento) y los resultados que fueron causados principalmente por el proceso o que estuvieron más derivados (p. ej.: cooperar, aprender, educar). Los resultados expanden la comunidad monitora y diseminan las conexiones creadas entre estos módulos. Los resultados clave deseados se pueden aplicar extensamente a los sistemas socio-ecológicos dentro y fuera del Ártico, particularmente aquellos con economías de sustento basadas en la fauna. Los atributos y motivaciones asociados con los resultados pueden guiar el desarrollo de los objetivos integrados de monitoreo para la conservación de la biodiversidad y las necesidades humanas. Nuestros resultados demostraron la desconexión entre los objetivos conducidos por la información y aquellos conducidos por el proceso y cómo la expansión de la comunidad monitora y una mejor integración de los accionistas monitores ayudarán a conectar los resultados derivados de la información y derivados del proceso para una administración efectiva del ecosistema.

Ecological correlates of the spatial co-occurrence of sympatric mammalian carnivores worldwide.

The composition of local mammalian carnivore communities has far-reaching effects on terrestrial ecosystems worldwide. To better understand how carnivore communities are structured, we analysed camera trap data for 108 087 trap days across 12 countries spanning five continents. We estimate local probabilities of co-occurrence among 768 species pairs from the order Carnivora and evaluate how shared ecological traits correlate with probabilities of co-occurrence. Within individual study areas, species pairs co-occurred more frequently than expected at random. Co-occurrence probabilities were greatest for species pairs that shared ecological traits including similar body size, temporal activity pattern and diet. However, co-occurrence decreased as compared to other species pairs when the pair included a large-bodied carnivore. Our results suggest that a combination of shared traits and top-down regulation by large carnivores shape local carnivore communities globally.