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We focus on distinctive data-driven measures of the fate of ongoing epidemics. The relevance of our pursuit is suggested by recent results proving that the short-term temporal evolution of infection spread is described by an epidemicity index related to the maximum instantaneous growth rate of new infections, echoing concepts and tools developed to study the reactivity of ecosystems. Suitable epidemicity indices can showcase the dynamics of infections, together with commonly employed effective reproduction numbers, especially when the latter assume values less than 1. In particular, epidemicity evaluates the short-term reactivity to perturbations of a disease-free equilibrium. Here, we show that sufficient epidemicity thresholds to prevent transient epidemic outbreaks in a spatially connected setting can be estimated by generalizing existing analogues derived when spatial effects are neglected. We specifically account for the discrete nature, in both space and time, of surveillance data of the type typically employed to estimate effective reproduction numbers that formed the bulk of the communication of the state of the COVID-19 pandemic and its controls. After analyzing the effects of spatial heterogeneity on the considered prognostic indicators, we perform a short- and long-term analysis on the COVID-19 pandemic in Italy, showing that endemic conditions were maintained throughout the duration of our simulation despite stringent control measures. Our method provides a portfolio of prognostic indices that are essential to pinpoint the ongoing pandemic in both a qualitative and quantitative manner, as our results demonstrate. We base our conclusions on extended investigations of the effects of spatial fragmentation of communities of different sizes owing to connectivity by human mobility and contact scenarios, within real geographic contexts and synthetic setups designed to test our framework. [ABSTRACT FROM AUTHOR]

Rocky Mountain spotted fever (RMSF) is a fatal tick-borne zoonotic disease that has emerged as an epidemic in western North America since the turn of the 21st century. Along the US south-western border and across northern Mexico, the brown dog tick, Rhipicephalus sanguineus, is responsible for spreading the disease between dogs and humans. The widespread nature of the disease and the ongoing epidemics contrast with historically sporadic patterns of the disease. Because dogs are amplifying hosts for the Rickettsia rickettsii bacteria, transmission dynamics between dogs and ticks are critical for understanding the epidemic. In this paper, we developed a compartment metapopulation model and used it to explore the dynamics and drivers of RMSF in dogs and brown dog ticks in a theoretical region in western North America. We discovered that there is an extended lagdas much as two yearsdbetween introduction of the pathogen to a naïve population and epidemic-level transmission, suggesting that infected ticks could disseminate extensively before disease is detected. A single large city-size population of dogs was sufficient to maintain the disease over a decade and serve as a source for disease in surrounding smaller towns. This model is a novel tool that can be used to identify high risk areas and key intervention points for epidemic RMSF spread by brown dog ticks. [ABSTRACT FROM AUTHOR]

Important metapopulation dynamics are disrupted by factors such as habitat loss, climate change, and human-induced mortality, culminating in isolated wildlife populations and threatening species survival. Source populations, where birth rates exceed mortality and connectivity facilitates dispersal, contrast with sink populations, where mortality outstrips births, risking localised extinction. Recolonisation by individuals from source populations is pivotal for species survival. The leopard is the last free-roaming apex predator in South Africa and plays an important ecological role. In the Eastern and Western Cape provinces in South Africa, leopard populations have low densities and fragmented population structures. We identified a leopard population that, after being locally extinct for a century, appeared to recolonise an 'island' of mountainous habitat. We aimed to understand potential factors driving this recolonisation using recent camera trapping surveys and historical statutory destruction permits. We employed spatially explicit capture–recapture (SECR) methods to estimate the leopard density and explore potential factors which best explain density. We found that the recently recolonised Piketberg population now exhibits some of the highest densities reported in the region (~1.8 leopards/100 km2; CI 1.4–2.5). Livestock, human presence, elevation, and the camera trap grid appeared to explain leopard detection rates. When considering the historic data, the re-emergence of leopards in the Piketberg coincided with the cessation of the extensive state-sponsored and state-enabled culling of the species, and the change in land use from livestock production to crop agriculture, which likely contributed to the recolonisation. Elucidating these factors deepens our understanding of leopard metapopulation dynamics in relation to land use and species management and highlights the crucial role of private land and state agencies and associated policies in species persistence. [ABSTRACT FROM AUTHOR]

Habitat loss and isolation caused by landscape fragmentation represent a growing threat to global biodiversity. Existing theory suggests that the process will lead to a decline in metapopulation viability. However, since most metapopulation models are restricted to simple networks of discrete habitat patches, the effects of real landscape fragmentation, particularly in stochastic environments, are not well understood. To close this major gap in ecological theory, we developed a spatially explicit, individual-based model applicable to realistic landscape structures, bridging metapopulation ecology and landscape ecology. This model reproduced classical metapopulation dynamics under conventional model assumptions, but on fragmented landscapes, it uncovered general dynamics that are in stark contradiction to the prevailing views in the ecological and conservation literature. Notably, fragmentation can give rise to a series of dualities: a) positive and negative responses to environmental noise, b) relative slowdown and acceleration in density decline, and c) synchronization and desynchronization of local population dynamics. Furthermore, counter to common intuition, species that interact locally ("residents") were often more resilient to fragmentation than long-ranging "migrants." This set of findings signals a need to fundamentally reconsider our approach to ecosystem management in a noisy and fragmented world. [ABSTRACT FROM AUTHOR]

This research explores the influence of individual mobility on COVID-19 transmission, utilizing a temporal mathematical model to clarify disease spread and vaccination dynamics across diverse regions. Employing a computationally efficient two-patch configuration that emphasizes regional interactions, our study aims to guide optimal disease control strategies. The introduced SEIR-V model with a two-patch setup estimates the vaccination reproduction number, Rv, while equilibrium points and system stability are identified. Visualizations from numerical simulations and sensitivity analyses illustrate key parameters affecting the vaccination reproduction number and COVID-19 control measures. Our findings underscore system responsiveness, emphasizing the intricate relationship between Rv, migration rates, and disease prevalence. [ABSTRACT FROM AUTHOR]

Understanding the processes that drive interpopulation differences in demography and population dynamics is central to metapopulation ecology. In colonial species, populations are limited by local resource availability. However, individuals from larger colonies will travel greater distances to overcome density‐dependent competition. Consequently, these individuals may also experience greater carry‐over effects and interpopulation differences in demography. To test this prediction, we use mark‐recapture data collected over four decades from two breeding colonies of a seabird, the Manx shearwater (Puffinus puffinus), that exhibit strong spatial overlap throughout the annual cycle but differ in population size and maximum foraging distances. We quantify interpopulation differences and synchrony in rates of survival and assess whether local mean wind speeds act to strengthen or disrupt synchrony. In addition, we examine whether the imputed interpopulation differences in survival can generate population‐level consequences. The colony where individuals travel further during the breeding season had slightly lower and more variable rates of survival, indicative of individuals experiencing greater carry‐over effects. Fluctuations in survival were highly synchronous between the colonies, but neither synchronous, nor asynchronous, variation could be strongly attributed to fluctuations in local mean wind speeds. Finally, we demonstrate that the imputed interpopulation differences in rates of survival could lead to considerable differences in population growth. We hypothesise that the observed interpopulation differences in rates of adult survival reflect carry‐over effects associated with foraging distances during the breeding season. More broadly, our results highlight that breeding season processes can be important for understanding interpopulation differences in the demographic rates and population dynamics of long‐lived species, such as seabirds. [ABSTRACT FROM AUTHOR]

Niche modeling is typically used to assess the effects of anthropogenic land use and climate change on species distributions and to inform spatial conservation planning. These models focus on the suitability of local biotic and abiotic conditions for a species in environmental space (E‐space). Although movements also affect species occurrence, efforts to formally integrate geographic space (G‐space) into niche modeling have been hindered by the lack of comprehensive theoretical frameworks. We propose the "functional habitat" framework to define areas that are simultaneously of high quality in E‐space, and functionally connected to other suitable habitats in G‐space. Originating in metapopulation ecology, approaches have been developed to assess the amount of suitable connected habitats, based on the proximity between pairs of locations. Using network theory, which operates in topological space (T‐space, defined by a network), we extended these metapopulation approaches to integrate movement constraints in G‐space with niche modeling in E‐space. We demonstrate the functional habitat framework using empirical data (GPS tracking and population monitoring) throughout the European wild mountain reindeer (Rangifer t. tarandus) distribution range. We show that functional habitat outperforms traditional suitability in explaining the species' distribution. This approach integrates effects from habitat loss and fragmentation for spatial conservation planning, and avoids overemphasizing small, inaccessible areas with locally suitable habitats. The functional habitat framework formally integrates biotic, abiotic, and movement constraints in niche modeling using network theory, thus opening a wide range of applications in spatial conservation planning. [ABSTRACT FROM AUTHOR]

When examining the probability of extinction of a given orchid species, the species must be viewed as a metapopulation composed of many individual populations connected by migration. In biology, much attention has been paid to the dynamics of metapopulations, especially in the situation where metapopulation dynamics are affected by active migration of individuals between populations. However, this is not the case with orchids. Their seeds are passively spread by wind, and therefore are unable to actively choose the point where they land (passive migrants, unlike, e.g., butterflies, which can actively look for a suitable site that hosts, hosted or can potentially host a population of their species (active migrants). Thus, while active migrants can often find a suitable destination for their migration, passive migrants often die after landing at an unsuitable site. One would therefore expect that, other things being equal, the proportion of suitable sites inhabited by active migrants is larger than that inhabited by passive migrants. In passive migrants (orchids) we may therefore meet metapopulation dynamics of a different, yet unexplored type, in which some existing localities die out and new localities appear, in the vast majority where no orchids have ever grown before. This type of dynamics has not yet been studied anywhere and this paper is intended to be the first step in this direction. The main goal here is therefore empirical determination of actual distributions of population sizes in different metapopulations. We do it in four regions of the Czech Republic and for four species of orchids, considering the factors that influence it. [ABSTRACT FROM AUTHOR]

Increasingly precise spatial data (e.g. high‐resolution imagery from remote sensing) allow for improved representations of the landscape network for assessing the combined effects of habitat loss and connectivity declines on biodiversity. However, evaluating large landscape networks presents a major computational challenge both in terms of working memory and computation time. We present the ConScape (i.e. "connected landscapes") software library implemented in the high‐performance open‐source Julia language to compute metrics for connected habitat and movement flow on high‐resolution landscapes.The combination of Julia's 'just‐in‐time' compiler, efficient algorithms and 'landmarks' to reduce the computational load allows ConScape to compute landscape ecological metrics—originally developed in metapopulation ecology (such as 'metapopulation capacity' and 'probability of connectivity')—for large landscapes. An additional major innovation in ConScape is the adoption of the randomized shortest paths framework to represent connectivity along the continuum from optimal to random movements, instead of only those extremes.We demonstrate ConScape's potential for using large datasets in sustainable land planning by modelling landscape connectivity based on remote‐sensing data paired with GPS tracking of wild reindeer in Norway. To guide users, we discuss other applications, and provide a series of worked examples to showcase all ConScape's functionalities in Supplementary Material.Built by a team of ecologists, network scientists and software developers, ConScape is able to efficiently compute landscape metrics for high‐resolution landscape representations to leverage the availability of large data for sustainable land use and biodiversity conservation. As a Julia implementation, ConScape combines computational efficiency with a transparent code base, which facilitates continued innovation through contributions from the rapidly growing community of landscape and connectivity modellers using Julia. [ABSTRACT FROM AUTHOR]

Copyright of European Bison Conservation Newsletter/ Żubr i Jego Ochrona Biuletyn is the property of European Bison Friends Society / Stowarzyszenie Milosnikow Zubrow and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Motivated by unique challenges faced in containing the 2014 Ebola outbreak in West Africa, we develop a framework to dynamically allocate limited resources to several possibly connected populations where the disease transmission is stochastic. We formulate this problem as a stochastic dynamic program. However, as the state and action spaces grow exponentially with the size of the problem, the standard solution techniques do not apply. We propose two solution methodologies along with several benchmark policies. The first approach considers a dynamic one-step look-ahead policy which is equivalent to a nonlinear integer knapsack that scales well with the problem size. The second approach is a modification of a myopic incidence policy found in the literature. In addition to testing the proposed policies in a simulation setting of the optimization framework, we develop a large-scale stochastic simulation for 2014 Ebola outbreak in a case study. We calibrate and validate the stochastic simulation model with real-world data from Sierra Leone. Our results provide insights on efficient prioritization and resource allocation in this setting. [ABSTRACT FROM AUTHOR]

We introduce a new model for plant metapopulations with a seed bank component, living in a fragmented environment in which local extinction events are frequent. This model is an intermediate between population dynamics models with a seed bank component, based on the classical Wright–Fisher model, and Stochastic Patch Occupancy Models (SPOMs) used in metapopulation ecology. Its main feature is the use of "ghost" individuals, which can reproduce but with a very strong selective disadvantage against "real" individuals, to artificially ensure a constant population size. We show the existence of an extinction threshold above which persistence of the subpopulation of "real" individuals is not possible, and investigate how the seed bank characteristics affect this extinction threshold. We also show the convergence of the model to a SPOM under an appropriate scaling, bridging the gap between individual-based models and occupancy models. [ABSTRACT FROM AUTHOR]

Keywords: biomat; geoecology; glaciation; granite dome; soil; succession EN biomat geoecology glaciation granite dome soil succession 1 4 4 06/06/22 20220601 NES 220601 Geologists have long documented crescentic gouges as conspicuous glacial landmarks on exposed granite domes throughout the world (Chamberlin, 1888). What constitutes true biocrust is hotly, though informally, debated in soil ecology circles.) The troughs of crescentic gouges trap wind- and water-borne sediments and propagules that would otherwise blow or wash off the mountains, initiating a series of successional stages that eventually support vascular plant establishment. [Extracted from the article]

Connectivity is a central concept in ecology, wildlife management, and conservation science. Understanding the role of connectivity in determining species persistence is increasingly important in the face of escalating anthropogenic impacts on climate and habitat. These connectivity augmenting processes can severely impact species distributions and community and ecosystem functioning. One general definition of connectivity is that it is an emergent process arising from a set of spatial interdependencies between individuals or populations, and increasingly realistic representations of connectivity are being sought. Generally, connectivity consists of a structural component, relating to the distribution of suitable and unsuitable habitat, and a functional component, relating to movement behavior, yet the interaction of both components often better describes ecological processes. Additionally, although implied by 'movement', demographic measures such as the occurrence or abundance of organisms are regularly overlooked when quantifying connectivity. Integrating such demographic contributions based on the knowledge of species distribution patterns is critical to understanding the dynamics of spatially structured populations. Demographically‐informed connectivity draws from fundamental concepts in metapopulation ecology while maintaining important conceptual developments from landscape ecology, and the methodological development of spatially‐explicit hierarchical statistical models that have the potential to overcome modeling and data challenges. Together, this offers a promising framework for developing ecologically realistic connectivity metrics. This review synthesizes existing approaches for quantifying connectivity and advocates for demographically‐informed connectivity as a general framework for addressing current problems across ecological fields reliant on connectivity‐driven processes such as population ecology, conservation biology and landscape ecology. Using supporting simulations to highlight the consequences of commonly made assumptions that overlook important demographic contributions, we show that even small amounts of demographic information can greatly improve model performance. Ultimately, we argue demographic measures are central to extending the concept of connectivity and resolves long‐standing challenges associated with accurately quantifying the influence of connectivity on fundamental ecological processes. [ABSTRACT FROM AUTHOR]

Legitimate For the information that is produced by conservation scientists to be used to promote biodiversity conservation, it must be considered legitimate, not only by researchers, but in the eyes of local communities, policymakers, and agents that create action. Thus, conservation scientists face great challenges in contributing practically, meaningfully, and ethically to the preservation of biodiversity, but it is equally evident that there are reasons to be optimistic. Keywords: community involvement in conservation; evaluation; knowledge to action pathway; university business model EN community involvement in conservation evaluation knowledge to action pathway university business model 530 535 6 05/10/22 20220501 NES 220501 INTRODUCTION Human actions have severely disrupted the earth's systems and impacted biodiversity. [Extracted from the article]

Long‐distance dispersal (LDD) is consequential to metapopulation ecology and evolution. In systems where dispersal is undertaken by small propagules, such as larvae in the ocean, documenting LDD is especially challenging. Genetic parentage analysis has gained traction as a method for measuring larval dispersal, but such studies are generally spatially limited, leaving LDD understudied in marine species. We addressed this knowledge gap by uncovering LDD with population assignment tests in the coral reef fish Elacatinus lori, a species whose short‐distance dispersal has been well‐characterized by parentage analysis. When adults (n = 931) collected throughout the species' range were categorized into three source populations, assignment accuracy exceeded 99%, demonstrating low rates of gene flow between populations in the adult generation. After establishing high assignment confidence, we assigned settlers (n = 3,828) to source populations. Within the settler cohort, <0.1% of individuals were identified as long‐distance dispersers from other populations. These results demonstrate an exceptionally low level of connectivity between E. lori populations, despite the potential for ocean currents to facilitate LDD. More broadly, these findings illustrate the value of combining genetic parentage analysis and population assignment tests to uncover short‐ and long‐distance dispersal, respectively. [ABSTRACT FROM AUTHOR]

Despite intensive management since the 1970s, recovery of the endangered northwestern Atlantic population of the Roseate Tern (Sterna dougallii dougallii) has not offset low productivity from a female-biased sex ratio, low adult survival, and habitat constriction. Now, >90% of individuals breed at three sites within 200 km from Long Island, NY, to Buzzards Bay, MA (warm-water subregion). To characterize the impact of historical bottlenecks, metapopulation structure, and demographic fluctuations on genetic variation, Roseate Terns from the warm-water (1870s, 1970s, 1997, 2016) and coldwater (Nova Scotia, Canada; 2018) subregions were genotyped at 8-16 microsatellites and 2-3 mitochondrial regions. Diversity declined in the warm-water subregion from the 1870s (expected heterozygosity [HE] = 0.44, allelic richness [AR] = 2.86) and 1970s (HE = 0.53, AR = 3.25) to 1997 (HE = 0.38, AR = 2.58). Genetic signatures of bottlenecks persisted in 1997 (P = <0.001-0.003) and 2016 (P = <0.001-0.005), but an increase in variation occurred by 2016 (HE = 0.50, AR = 2.85). Weak structure was detected between contemporary warm- and cold-water subregions (θ = 0.06) and within the warmwater subregion (θ = 0.04). Both demographic (3,439-3,821) and genetic (3,040) estimates suggested effective population size (Ne) stability over the last 100 years, despite large fluctuations in census size (4,000-8,662). Results suggest that 50 years of management (restoring habitat, preventing gull encroachment, controlling predators) at colony sites supported a small, stable Ne and maintained a hierarchical metapopulation that allowed gene flow to redistribute genetic variation throughout the northwest Atlantic. The metapopulation remains highly vulnerable to stochastic events but harbors resiliency and redundancy through gene flow and a stable Ne. For long-term persistence from a genetic perspective, managers must maintain the major source colonies, increase the availability of high-quality peripheral breeding sites, and protect concentrated nonbreeding sites that facilitate gene flow. [ABSTRACT FROM AUTHOR]

The effect of population structure on evolutionary dynamics is a long-lasting research topic in evolutionary ecology and population genetics. Evolutionary graph theory is a popular approach to this problem, where individuals are located on the nodes of a network and can replace each other via the links. We study the effect of complex network structure on the fixation probability, but instead of networks of individuals, we model a network of sub-populations with a probability of migration between them. We ask how the structure of such a meta-population and the rate of migration affect the fixation probability. Many of the known results for networks of individuals carry over to meta-populations, in particular for regular networks or low symmetric migration probabilities. However, when patch sizes differ we find interesting deviations between structured meta-populations and networks of individuals. For example, a two patch structure with unequal population size suppresses selection for low migration probabilities. [ABSTRACT FROM AUTHOR]

We analyze the stability of a unique coexistence equilibrium point of a system of ordinary differential equations (ODE system) modelling the dynamics of a metapopulation, more specifically, a set of local populations inhabiting discrete habitat patches that are connected to one another through dispersal or migration. We assume that the inter-patch migrations are detailed balanced and that the patches are identical with intra-patch dynamics governed by a mean-field ODE system with a coexistence equilibrium. By making use of an appropriate Lyapunov function coupled with LaSalle's invariance principle, we are able to show that the coexistence equilibrium point within each patch is locally asymptotically stable if the inter-patch dispersal network is heterogeneous, whereas it is neutrally stable in the case of a homogeneous network. These results provide a mathematical proof confirming the existing numerical simulations and broaden the range of networks for which they are valid. [ABSTRACT FROM AUTHOR]

Populations of many species of grassland‐associated butterflies, moths, and bumblebees in the Great Plains of North America are experiencing steep declines due to habitat loss and degradation—primarily conversion of grasslands to row‐crop agriculture and invasion of woody plants and exotic cool‐season grasses—and insecticide use. These declines are exacerbated by the generally limited dispersal ability of insects, which make local populations susceptible to extirpation following habitat fragmentation. Interest in pollinator conservation has grown substantially in recent years, but information to guide pollinator conservation across the region is limited. We used pollinator biology along with principles of landscape ecology and metapopulation dynamics to develop a simple decision matrix based on patch size and inter‐patch distances to guide landscape‐scale grassland conservation efforts in the U.S. northern Great Plains. When applied to spatial land cover data depicting potential pollinator habitat, the matrix uses landscape characteristics to guide placement of conservation treatments to help ensure persistence of target pollinator populations. Patch size and connectivity thresholds can be set to match characteristics of target species, but in all cases, local management will be necessary to ensure that fine‐grained features such as nectar sources and host plants are present. Applying the matrix to habitat layers for a nine‐state analysis region showed substantial geographic variation in conservation needs, opportunities, and potential treatments. We also demonstrate that non‐native planted cover such as alfalfa and certain grasslands enrolled in the Conservation Reserve Program can substantially enhance landscape structure by increasing grassland patch size and core area while decreasing distance between patches. Pollinators dependent on native prairie will also benefit from planted cover that provides nectar sources and serves as a buffer from pesticides associated with croplands. Consistent with the principles of strategic habitat conservation, targeted monitoring and research will be necessary to validate and adapt the model to meet local conditions. [ABSTRACT FROM AUTHOR]

Copyright of Libellula is the property of Gesellschaft Deutschsprachiger Odonatologen e.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Wetlands worldwide are under threat from anthropogenic impacts. In large protected North American areas such as Yellowstone and Wood Buffalo National Parks, aquatic habitats are disappearing and wetland-dependent fauna are in decline1–3. Here we investigate population dynamics of an indicator species in Canada's Peace-Athabasca Delta ("the delta"), a World Heritage Site. Based on population surveys, habitat mapping and genetic data from 288 muskrats, we use agent-based modeling and genetic analyses to explain population expansion and decline of the semi-aquatic muskrat (Ondatra zibethicus). Simulations quantify a large population (~500,000 individuals) following flood-induced habitat gains, with decreased size (~10,000 individuals) during drying. Genetic analyses show extremely low long-term effective population size (Ne: 60–127), supporting a legacy of population bottlenecks. Our simulations indicate that the muskrat population in the delta is a metapopulation with individuals migrating preferentially along riparian pathways. Related individuals found over 40 km apart imply dispersal distances far greater than their typical home range (130 m). Rapid metapopulation recovery is achieved via riparian corridor migration and passive flood-transport of individuals. Source-sink dynamics show wetland loss impacts on the muskrat metapopulation's spatial extent. Dramatic landscape change is underway, devastating local fauna, including this generalist species even in a protected ecosystem. Ward et al. investigate population dynamics of a wetland indicator species, the semi-aquatic muskrat, within the large and protected area of the Peace-Athabasca Delta in Canada. The authors found indications of rapid population increases associated with flood events, genetic signatures of population bottlenecks, long range dispersal dynamics, and declines in the spatial extent of the muskrat population indicative of the impacts of wetland loss even within a protected ecosystem. [ABSTRACT FROM AUTHOR]

Cyclic dominance of competing species is an intensively used working hypothesis to explain biodiversity in certain living systems, where the evolutionary selection principle would dictate a single victor otherwise. Technically the May–Leonard models offer a mathematical framework to describe the mentioned non-transitive interaction of competing species when individual movement is also considered in a spatial system. Emerging rotating spirals composed by the competing species are frequently observed character of the resulting patterns. But how do these spiraling patterns change when we vary the external environment which affects the general vitality of individuals? Motivated by this question we suggest an off-lattice version of the tradition May–Leonard model which allows us to change the actual state of the environment gradually. This can be done by introducing a local carrying capacity parameter which value can be varied gently in an off-lattice environment. Our results support a previous analysis obtained in a more intricate metapopulation model and we show that the well-known rotating spirals become evident in a benign environment when the general density of the population is high. The accompanying time-dependent oscillation of competing species can also be detected where the amplitude and the frequency show a scaling law of the parameter that characterizes the state of the environment. These observations highlight that the assumed non-transitive interaction alone is insufficient condition to maintain biodiversity safely, but the actual state of the environment, which characterizes the general living conditions, also plays a decisive role on the evolution of related systems. [ABSTRACT FROM AUTHOR]

The spread of an infectious disease is well approximated by metapopulation networks connected by human mobility flow and upon which an epidemiological model is defined. In order to account for travel restrictions or cancellation we introduce a model with a parameter that explicitly indicates the ratio between the time scales of the intervening processes. We study the critical properties of the epidemic process and its dependence on such a parameter. We find that the critical threshold separating the absorbing state from the active state depends on the scale parameter and exhibits a critical behavior itself: a metacritical point – a critical value in the curve of critical points – reflected in the behavior of the attack rate measured for a wide range of empirical metapopulation systems. Our results have potential policy implications, since they establish a non-trivial critical behavior between temporal scales of reaction (epidemic spread) and diffusion (human mobility) processes. The time scales of individual contagion and human mobility are both relevant to understand the evolution of epidemics. Here, the authors study a reaction-diffusion process for an epidemic metapopulation model, showing that modulating the relative time scale of these two processes produces different epidemic outcomes and can reproduce the effect of non-pharmaceutical interventions. [ABSTRACT FROM AUTHOR]

The land snail Ellobium chinense (L. Pfeiffer, 1855) (Eupulmonata, Ellobiida, Ellobiidae), which inhabits the salt marshes along the coastal areas of northwestern Pacific, is an endangered species on the IUCN Red List. Over recent decades, the population size of E. chinense has consistently decreased due to environmental interference caused by natural disasters and human activities. Here, we provide the first assessment of the genetic diversity and population genetic structures of northwestern Pacific E. chinense. The results analyzed with COI and microsatellites revealed that E. chinense population exhibit metapopulation characteristics, retaining under the influence of the Kuroshio warm currents through expansion of the Late-Middle and Late Pleistocene. We also found four phylogenetic groups, regardless of geographical distributions, which were easily distinguishable by four unidirectional and stepwise adenine-to-guanine transitions in COI (sites 207–282–354–420: A–A–A–A, A–A–G–A, G–A–G–A, and G–G–G–G). Additionally, the four COI hotspots were robustly connected with a high degree of covariance between them. We discuss the role of these covariate guanines which link to form four consecutive G-quadruplexes, and their possible beneficial effects under positive selection pressure. [ABSTRACT FROM AUTHOR]

Ecosystem functioning depends on multiple successful interactions, many supported by individual movements. The degree to which the landscape allows these interactions to take place has been referred to as 'effective connectivity' (EC). Many of the cumulative impacts of anthropogenic activities on ecosystem functioning arise from changes in EC. Therefore, a coherent framework to quantify EC is urgently needed. Recent theoretical developments propose that studying EC requires the simultaneous consideration of spatial, environmental and species intrinsic characteristics (SEI framework). In this paper we further expand the SEI framework by integrating advances in geographic information science, ecological niche modelling, movement ecology, island biogeography and network sciences to develop a comprehensive three‐step methodological approach for quantifying EC. First, using niche modelling and movement ecology, we quantify the species movement probabilities with respect to local environmental conditions. Second, we quantify ecological distances between non‐adjacent locations by integrating species movement responses to the local environment with the spatial configuration of the landscape using the expected cost obtained from the randomized shortest paths (RSP) framework. This expected cost generalizes the two most frequently used ecological distance metrics, i.e. least‐cost distance and resistance distance. Moreover the 'absorbing random walk' properties of RSP allow the integration of new developments in connectivity research, i.e. spatial absorbing Markov chains, to account for movement‐related mortality. Third, drawing from island biogeography and metapopulation ecology, we scale ecological distances by relevant species‐ and area‐specific parameters to estimate EC for the ecological process of interest, e.g. migration, dispersal or gene flow. The integrative and highly interdisciplinary approach we propose can lead to increasingly more realistic measures of EC at different organizational levels. Moreover efficient computation allows its application to large‐scale high‐resolution landscapes for theoretical studies, conservation planning and sustainable management of real landscapes. [ABSTRACT FROM AUTHOR]

In organisms with discrete generations such as most insects, life-history traits including dispersal abilities often vary between generations. In particular, density-dependent differences in dispersal of bi- and multivoltine species may be expected because subsequent generations are usually characterized by a drastic increase in individual abundance. We investigated the inter-sexual and inter-generation differences in dispersal of a bivoltine butterfly, Lycaena helle, testing the following hypotheses: (1) male emigration is higher in spring generation, as males are prone to leave their natal habitat patches when the density of mating partners is low; (2) female emigration is higher in summer generation, when it helps to reduce intraspecific competition between offspring. The outcome of our analyses of dispersal parameters showed that females of the summer generation emigrated from their natal patches considerably more often than those of the spring generation, whereas an opposite trend was detected in males. These findings offer a novel perspective for our understanding of the advantages of voltinism for metapopulation functioning. The spring generation dispersal mainly improves the random mating opportunities favoured by the increase in male emigration. In turn, the dispersal of females of the summer generation appears the key to long-term metapopulation persistence. [ABSTRACT FROM AUTHOR]

When a novel disease strikes a naïve host population, there is evidence that the most immediate response can involve host evolution while the pathogen remains relatively unchanged. When hosts also live in metapopulations, there may be critical differences in the dynamics that emerge from the synergy among evolutionary, ecological, and epidemiological factors. Here we used a Susceptible-Infected-Recovery model to explore how spatial and temporal ecological factors may drive the epidemiological and rapid-evolutionary dynamics of host metapopulations. For simplicity, we assumed two host genotypes: wild type, which has a positive intrinsic growth rate in the absence of disease, and robust type, which is less likely to catch the infection given exposure but has a lower intrinsic growth rate in the absence of infection. We found that the robust-type host would be strongly selected for in the presence of disease when transmission differences between the two types is large. The growth rate of the wild type had dual but opposite effects on host composition: a smaller increase in wild-type growth increased wild-type competition and lead to periodical disease outbreaks over the first generations after pathogen introduction, while larger growth increased disease by providing more susceptibles, which increased robust host density but decreased periodical outbreaks. Increased migration had a similar impact as the increased differential susceptibility, both of which led to an increase in robust hosts and a decrease in periodical outbreaks. Our study provided a comprehensive understanding of the combined effects among migration, disease epidemiology, and host demography on host evolution with an unchanging pathogen. The findings have important implications for wildlife conservation and zoonotic disease control. [ABSTRACT FROM AUTHOR]

Accounting for individual decisions in mechanistic epidemiological models remains a challenge, especially for unregulated endemic animal diseases for which control is not compulsory. We propose a new integrative model by combining two sub-models. The first one for the dynamics of a livestock epidemic on a metapopulation network, grounded on demographic and animal trade data. The second one for farmers' behavior regarding the adoption of a control measure against the disease spread in their herd. The measure is specified as a protective vaccine with given economic implications, and the model is numerically studied through intensive simulations and sensitivity analyses. While each tested parameter of the model has an impact on the overall model behavior, the most important factor in farmers' decisions is their frequency, as this factor explained almost 30% of the variation in decision-related outputs of the model. Indeed, updating frequently local health information impacts positively vaccination, and limits strongly the propagation of the pathogen. Our study is relevant for the understanding of the interplay between decision-related human behavior and livestock epidemic dynamics. The model can be used for other structures of epidemic models or different interventions, by adapting its components. [ABSTRACT FROM AUTHOR]

In a world where biodiversity is on the decline, examples of conservation success especially of large carnivores are of interest to policy makers and conservation practitioners. Herein, we elucidate the conservation actions that have been responsible for the recovery of tigers and their ecosystems in India; a feat many range countries are struggling to achieve.Demand‐driven poaching resulted in extinctions at two prestigious Tiger Reserves. India's Prime Minister constituted a Tiger Task Force that led to the formation of the National Tiger Conservation Authority, the Wildlife Crime Control Bureau, scientific monitoring of tiger populations and incentivized voluntary relocation of human settlements from tiger reserves. Tiger Conservation Plans, cognizant of constraints imposed by small reserves embedded in human land uses, aimed to create source populations within tiger reserves with corridor links between sources and to sink habitats. Metapopulation management enhanced occupancy and long‐term viability of tiger populations. Tiger Protection Force and technology like MSTrIPES, E‐eye and drones effectively reduced poaching. Community support was attempted through profit sharing, mitigating human–tiger conflict with a fast, fair and transparent compensation process and removal of problem tigers. Reintroduction and reinforcement of tigers and prey assisted natural recovery. Political will ensured resources.Tigers were monitored using Spatially Explicit Capture–Recapture with camera traps and ecological covariates. In 2018–2019 from 381,000 km2 of tiger habitat, 89,000 km2 was occupied. Currently, 50 tiger reserves cover 72,750 km2 and harbour 65% of India's ~3,000 tigers. Tiger reserves are managed with an annual investment of ~1,000 USD/km2 with one staff per 6.5 km2. Tiger reserves were regularly evaluated for Management Effectiveness. Tiger reserves were valued to have benefit flows between 76,900 and 292,300 US$ km−2year−1.In the Anthropocene it is unlikely that tigers will survive without targeted conservation investments. Political commitment and resources can become available for conservation when people and tigers benefit simultaneously. Conscious balance by governments between development for rapid economic prosperity and long‐term ecological security will ensure that wild tigers and their intact ecosystems will survive for future generations. A free Plain Language Summary can be found within the Supporting Information of this article. A free Plain Language Summary can be found within the Supporting Information of this article. [ABSTRACT FROM AUTHOR]

In the early stages of an outbreak, the term 'pandemic' can be used to communicate about infectious disease risk, particularly by those who wish to encourage a large-scale public health response. However, the term lacks a widely accepted quantitative definition. We show that, under alternate quantitative definitions of 'pandemic', an epidemiological metapopulation model produces different estimates of the probability of a pandemic. Critically, we show that using different definitions alters the projected effects of key parameters—such as inter-regional travel rates, degree of pre-existing immunity, and heterogeneity in transmission rates between regions—on the risk of a pandemic. Our analysis provides a foundation for understanding the scientific importance of precise language when discussing pandemic risk, illustrating how alternative definitions affect the conclusions of modelling studies. This serves to highlight that those working on pandemic preparedness must remain alert to the variability in the use of the term 'pandemic', and provide specific quantitative definitions when undertaking one of the types of analysis that we show to be sensitive to the pandemic definition. [ABSTRACT FROM AUTHOR]

Meta-population and -community models have extended our understanding regarding the influence of habitat distribution, local patch dynamics, and dispersal on species distribution patterns. Currently, theoretical insights on spatial distribution patterns are limited by the dominant use of deterministic approaches for modeling species dispersal. In this work, we introduce a probabilistic, network-based framework to describe species dispersal by considering inter-patch connections as network-determined probabilistic events. We highlight important differences between a deterministic approach and our dispersal formalism. Exemplified for a meta-population, our results indicate that the proposed scheme provides a realistic relationship between dispersal rate and extinction thresholds. Furthermore, it enables us to investigate the influence of patch density on meta-population persistence and provides insight on the effects of probabilistic dispersal events on species persistence. Importantly, our formalism makes it possible to capture the transient nature of inter-patch connections, and can thereby provide short term predictions on species distribution, which might be highly relevant for projections on how climate and land use changes influence species distribution patterns. [ABSTRACT FROM AUTHOR]

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Antimicrobial resistance (AMR) is a global threat. A better understanding of how antibiotic use and between-ward patient transfers (or connectivity) impact population-level AMR in hospital networks can help optimize antibiotic stewardship and infection control strategies. Here, we used a metapopulation framework to explain variations in the incidence of infections caused by seven major bacterial species and their drug-resistant variants in a network of 357 hospital wards. We found that ward-level antibiotic consumption volume had a stronger influence on the incidence of the more resistant pathogens, while connectivity had the most influence on hospital-endemic species and carbapenem-resistant pathogens. Piperacillin-tazobactam consumption was the strongest predictor of the cumulative incidence of infections resistant to empirical sepsis therapy. Our data provide evidence that both antibiotic use and connectivity measurably influence hospital AMR. Finally, we provide a ranking of key antibiotics by their estimated population-level impact on AMR that might help inform antimicrobial stewardship strategies. [ABSTRACT FROM AUTHOR]

It is important to understand metapopulation dynamics and underlying demographic processes in heterogeneous landscapes. Traditionally, demographic parameters are estimated using capture–recapture data that can be difficult to collect. Spatially explicit dynamic N‐mixture models allow inference for demographic parameters, including dispersal, using count data of unmarked animals, but these models have only been shown effective under constant demographic parameters and dispersal between adjacent local populations.In this study, I aimed to compensate the weakness of spatially explicit dynamic N‐mixtures and multistate capture–recapture models by jointly analysing count and capture–recapture data. This spatially explicit integrated population model allows for spatiotemporal variation of demographic parameters in relation to environmental and density covariates and dispersal between any local populations. I conducted simulations to evaluate this model (a) for species with distinct life histories under different detection and capture probabilities, (b) when spatial sampling intensity varied, (c) when the length of survey period varied, (d) when the robust sampling design was adopted or not and (e) when auxiliary information is partially available. I also provided an empirical example of Gadwall Mareca strepera metapopulation dynamics in North American prairies.The results showed that the model provided unbiased parameter estimates under a variety of ecological and sampling conditions, even when the spatial sampling intensity of capture–recapture survey was low (20% of the patches) with the complement of count data (≥60% of the patches). Also, the model only required a relatively short survey period (6~8 years) to provide unbiased inferences. The robust sampling design was not necessary for the model to provide unbiased inferences when spatial counts were intense, but became critical when spatial counts were sparse. Parameter estimates remain unbiased when auxiliary information is partially available. The model showed that Gadwall had low emigration probability (11.8%) but could disperse more than 200 km.Based on the results, I provide recommendations about the trade‐off between spatial sampling intensity, length of survey period and the use of the robust sampling design when applying this model in real‐world studies. The model could have wide applications in the interface of metapopulation ecology and landscape ecology. [ABSTRACT FROM AUTHOR]

Aim: Idealized metacommunity structures (i.e. checkerboard, random, quasi‐structures, nested, Clementsian, Gleasonian and evenly spaced) have recently gained increasing attention, but their relationships with environmental heterogeneity and how they vary with organism groups remain poorly understood. Here, we tested two main hypotheses: (a) gradient‐driven patterns (Clementsian and Gleasonian) occur frequently in heterogeneous environments and (b) small organisms (here, diatoms) are more likely to exhibit gradient‐driven patterns than large organisms (here, macroinvertebrates). Location: Streams in three regions in China. Taxon: Diatoms and macroinvertebrates. Methods: The stream diatom and macroinvertebrate data, as well as the environmental data collected from the same set of sites were used to examine the idealized metacommunity structures via the elements of the metacommunity structure (EMS; coherence, turnover and boundary clumping) analysis in three regions. We extended the traditional EMS approach by ordering sites along known environmental gradients. Results: We found that Clementsian structure with high degrees of coherence and turnover, and significantly positive clumping was typically observed in the high‐heterogeneity regions, whereas randomness was prevalent in the low‐heterogeneity region. Macroinvertebrates exhibited clearer Clementsian structures compared with diatoms, while diatoms showed more randomness compared with macroinvertebrates, indicating a stronger role of environmental filtering for macroinvertebrates than diatoms. In most cases, the results of the more novel EMS approach differed from the results of the traditional EMS technique. Main conclusions: Our results suggested that the occurrence of different metacommunity structures may be related with the degree of regional environmental heterogeneity. However, diatom metacommunities were more random than those of macroinvertebrate, and such an unexpected result may result from different dispersal abilities between the two organism groups. In addition, we found that the novel EMS approach increased power in discerning metacommunity structure in comparison to the traditional EMS technique. [ABSTRACT FROM AUTHOR]

As anthropogenic impacts on the natural world escalate, there is increasing interest in the role of humans in dispersing seeds. But the consequences of this Human‐Mediated Dispersal (HMD) on plant spatial dynamics are little studied. In this paper, we ask how secondary dispersal by HMD affects the dynamics of a natural plant metapopulation. In addition to dispersal between patches, we suggest within‐patch processes can be critical. To address this, we assess how variation in local population dynamics, caused by small‐scale disturbances, affects metapopulation size. We created an empirically based model with stochastic population dynamics and dispersal among patches, which represented a real‐world, cliff‐top metapopulation of wild cabbage Brassica oleracea. We collected demographic data from multiple populations by tagging plants over eight years. We assessed seed survival, and establishment and survival of seedlings in intact vegetation vs. small disturbances. We modeled primary dispersal by wind using field data and used experimental data on secondary HMD by hikers. We monitored occupancy patterns over a 14‐yr period in the real metapopulation. Disturbance had large effects on local population growth rates, by increasing seedling establishment and survival. This meant that the modeled metapopulation grew in size only when the area disturbed in each patch was above 35%. In these growing metapopulations, although only 0.2% of seeds underwent HMD, this greatly enhanced metapopulation growth rates. Similarly, HMD allowed more colonizations in declining metapopulations under low disturbance, and this slowed the rate of decline. The real metapopulation showed patterns of varying patch occupancy over the survey years, which were related to habitat quality, but also positively to human activity along the cliffs, hinting at beneficial effects of humans. These findings illustrate that realistic changes to dispersal or demography, specifically by humans, can have fundamental effects on the viability of a species at the landscape scale. [ABSTRACT FROM AUTHOR]

Predicting the dynamics of biotic communities is difficult because species' environmental responses are not independent, but covary due to shared or contrasting ecological strategies and the influence of species interactions. We used latent‐variable joint species distribution models to analyze paired historical and contemporary inventories of 585 vascular plant species on 471 islands in the southwest Finnish archipelago. Larger, more heterogeneous islands were characterized by higher colonization rates and lower extinction rates. Ecological and taxonomical species groups explained small but detectable proportions of variance in species' environmental responses. To assess the potential influence of species interactions on community dynamics, we estimated species associations as species‐to‐species residual correlations for historical occurrences, for colorizations, and for extinctions. Historical species associations could to some extent predict joint colonization patterns, but the overall estimated influence of species associations on community dynamics was weak. These results illustrate the benefits of considering metacommunity dynamics within a joint framework, but also suggest that any influence of species interactions on community dynamics may be hard to detect from observational data. [ABSTRACT FROM AUTHOR]

Recent observations have found plant‐species‐specific fly‐host selection (i.e., specialization) of wasp parasitoids (wasps) in plant–fly–wasp (P–F–W) tripartite networks, yet no study has explored the dynamical implications of such high‐order specialization for the persistence of this network. Here we develop a patch‐dynamic framework for a unique P–F–W tripartite network with specialization observed in eastern Tibetan Plateau and explore its metacommunity robustness to habitat loss. We show that specialization in parasitoidism promotes fly species diversity, while the richness of both plant and wasp decreases. Compared to other two null models, real network structure favors plant species coexistence but increases the extinction risk for both flies and wasps. However, these effects of specialization and network structure would be weakened and ultimately disappear with increasing habitat loss. Interestingly, intermediate levels of habitat loss can maximize the diversity of flies and wasps, while increasing or decreasing habitat loss results in more species losses, supporting intermediate disturbance hypothesis. Finally, we observe that high levels of habitat loss initiate a bottom‐up cascade of species extinction from plants to both flies and wasps, resulting in a rapid collapse of the whole tripartite networks. Overall, this theoretical framework is the first attempt to characterize the dynamics of whole tripartite metacommunities interacting in realistic high‐order ways, offering new insights into complex multipartite networks. [ABSTRACT FROM AUTHOR]

Biotic interactions are fundamental drivers governing biodiversity locally, yet their effects on geographical variation in community composition (i.e. incidence‐based) and community structure (i.e. abundance‐based) at regional scales remain controversial. Ecologists have only recently started to integrate different types of biotic interactions into community assembly in a spatial context, a theme that merits further empirical quantification. Here, we applied partial correlation networks to infer the strength of spatial dependencies between pairs of organismal groups and mapped the imprints of biotic interactions on the assembly of pond metacommunities. To do this, we used a comprehensive empirical dataset from Mediterranean landscapes and adopted the perspective that community assembly is best represented as a network of interacting organismal groups. Our results revealed that the co‐variation among the beta diversities of multiple organismal groups is primarily driven by biotic interactions and, to a lesser extent, by the abiotic environment. These results suggest that ignoring biotic interactions may undermine our understanding of assembly mechanisms in spatially extensive areas and decrease the accuracy and performance of predictive models. We further found strong spatial dependencies in our analyses which can be interpreted as functional relationships among several pairs of organismal groups (e.g. macrophytes–macroinvertebrates, fish–zooplankton). Perhaps more importantly, our results support the notion that biotic interactions make crucial contributions to the species sorting paradigm of metacommunity theory and raise the question of whether these biologically‐driven signals have been equally underappreciated in other aquatic and terrestrial ecosystems. Although more research is still required to empirically capture the importance of biotic interactions across ecosystems and at different spatial resolutions and extents, our findings may allow decision makers to better foresee the main consequences of human‐driven impacts on inland waters, particularly those associated with the addition or removal of key species. [ABSTRACT FROM AUTHOR]

Summary: Pure (single) cultures of microorganisms and mixed microbial communities (microbiomes) have been important for centuries in providing renewable energy, clean water and food products to human society and will continue to play a crucial role to pursue the Sustainable Development Goals. To use microorganisms effectively, microbial engineered processes require adequate control. Microbial communities are shaped by manageable deterministic processes, but also by stochastic processes, which can promote unforeseeable variations and adaptations. Here, we highlight the impact of stochasticity in single culture and microbiome engineering. First, we discuss the concepts and mechanisms of stochasticity in relation to microbial ecology of single cultures and microbiomes. Second, we discuss the consequences of stochasticity in relation to process performance and human health, which are reflected in key disadvantages and important opportunities. Third, we propose a suitable decision tool to deal with stochasticity in which monitoring of stochasticity and setting the boundaries of stochasticity by regulators are central aspects. Stochasticity may give rise to some risks, such as the presence of pathogens in microbiomes. We argue here that by taking the necessary precautions and through clever monitoring and interpretation, these risks can be mitigated. [ABSTRACT FROM AUTHOR]

The metacommunity concept incorporates spatial dynamics into community ecology, shedding light on how local and regional processes interact in structuring ecological communities, and to which measure they are deterministic or stochastic. We reviewed metacommunity studies on freshwater meiobenthos published since 2004, when the main principles of metacommunity theory were conceptualized. The studies (together 19) were observational, focused mainly on ostracods, and rarely on rotifers and nematodes. In accordance with general expectations, the prevalent structuring force was species sorting. Ostracods showed more dispersal limitations than nematodes and rotifers, and there was very little support for dispersal surplus. We discussed the role of body size, dispersal mode, and attachment to sediment for the meiofauna dispersal. Effects of metacommunity context (habitat connectivity, spatial extent, and environmental heterogeneity), study design (e.g., sample size), and statistical approach could not be sufficiently disentangled due to the low number of studies. Local stochasticity, consistent with neutral theory and patch dynamics, was indicated for taxa with weak specialization and metacommunities in small habitats. Our understanding of meiofaunal metacommunities is only fragmentary and it would highly benefit from direct comparisons of taxa with different species traits and between different spatial scales, and studies incorporating temporal dynamics and hypothesis-driven experiments. [ABSTRACT FROM AUTHOR]

Dispersal is crucial for both individual fitness and spatiotemporal population dynamics. In sexual organisms, females and males have different reproductive strategies and therefore have different reproductive demands (i.e., reproductive resources and mating partners, respectively), which leads to differences in dispersal decision making between sexes. Although many studies have described sexual differences in dispersal behavior, little is known about the consequences for spatiotemporal population dynamics because metapopulation theory has considered only either nonrandom dispersal in asexual systems or random dispersal in sexual systems. To fill the knowledge gap, we propose a modeling framework that incorporates nonrandom and sex‐specific dispersal into metapopulation theory. It allows us to ask how female‐biased (e.g., in mammals) or male‐biased (e.g., in birds) dispersal can influence persistence of sexual organisms. [ABSTRACT FROM AUTHOR]

A fundamental goal of community ecology is to understand the drivers of community assembly and diversity. Local factors acting on community assembly are typically related to environmental conditions while regional factors are typically related to dispersal. Previous research has not consistently demonstrated the importance of local or regional factors, but this is likely because these factors act in concert and not in isolation. Studies that simultaneously integrate local and regional factors into analyses of community assembly can be a useful avenue to further our understanding of this core concept in community ecology.Here, we aimed to identify metacommunity structure and diversity and the local and regional drivers of community assembly at the continental scale.We evaluated metacommunity structure and drivers of assembly of macroinvertebrate communities in 941 rivers and streams nested within nine ecoregions distributed across the conterminous United States. Pattern‐based metacommunity analyses and boosted regression tree techniques were used to (a) assign metacommunity structures and (b) identify the environmental, landscape and network drivers of assembly. We also evaluated how biodiversity scaled across hierarchical levels and varied among ecoregions.Metacommunity structures were consistent for the conterminous United States and each of the nine ecoregion subsets, with each ecoregional metacommunity displaying a Clementsian structure. Environmental variables were the predominant drivers of assembly, suggesting the importance of species sorting and environmental filtering on community structure; however, the identity of the most influential environmental variables differed among ecoregions and suggested hierarchical filtering on assembly. Partitioned diversity was found to be lower at the local and ecoregional levels, but turnover in diversity among ecoregions was higher than expected.Our results demonstrate contingencies in community assembly, notwithstanding consistency in metacommunity structure and support the importance of environmental control over community assembly and biodiversity. Moreover, biodiversity at the continental scale is likely maintained through this inherent variation in the drivers of assembly and concomitant changes in community composition among ecoregions. We suggest that further work should evaluate the assembly of other facets of community structure and the underlying mechanisms of the contingency in assembly drivers. [ABSTRACT FROM AUTHOR]

To effectively manage wildlife populations, it is essential to reliably estimate their abundance. This is particularly the case for small, isolated populations, which are vulnerable to extirpation. Lake Nakuru National Park in Kenya is one such small, isolated area where an introduced population of African lions (Panthera leo) is vulnerable to genetic degradation and catastrophic events. A founder population of six individuals was introduced between 1984 and 1992, with no further recorded immigration. We used Bayesian spatially‐explicit capture–recapture models to estimate lion density and abundance based on unstructured spatial sampling. For individuals over the age of 1 year, posterior mean lion density was estimated to be 6.75 (mode = 5.93, posterior SD = 0.92) individuals/100 km2, with a mean abundance of 11.37 (mode = 10, posterior SD = 1.54), and a sex ratio of 1.38♀:1♂. Previous reports provided abundance figures much higher than ours. However, our estimates are the result of the first scientifically robust survey and we discuss why they should be viewed as a baseline rather than being suggestive of population decline, and how the discrepancy highlights the need for regular systematic surveys using a standardized framework. Given the small population size and prolonged genetic isolation, we provide long‐term management recommendations to secure this lion population. [ABSTRACT FROM AUTHOR]

Many metacommunities are distributed across habitat patches that are themselves aggregated into groups. Perhaps the clearest example of this nested metacommunity structure comes from multi‐species parasite assemblages, which occupy individual hosts that are aggregated into host populations. At both spatial scales, we expect parasite community diversity in a given patch (either individual host or population) to depend on patch characteristics that affect colonization rates and species sorting. But, are these patch effects consistent across spatial scales? Or, do different processes govern the distribution of parasite community diversity among individual hosts, versus among host patches? To answer these questions, we document the distribution of parasite richness among host individuals and among populations in a metapopulation of threespine stickleback Gasterosteus aculeatus. We find some host traits (host size, gape width) are associated with increased parasite richness at both spatial scales. Other patch characteristics affect parasite richness only among individuals (sex), or among populations (lake size, lake area, elevation and population mean heterozygosity). These results demonstrate that some rules governing parasite richness in this metacommunity are shared across scales, while others are scale‐specific. [ABSTRACT FROM AUTHOR]

Population dynamics of a predator-prey system is usually simulated by the classical Lotka-Volterra models, which were successfully applied to the population dynamics of snowshoe hare and lynx and many other predator-prey systems. Attempts were made to apply them also to insect predator-prey systems, but in terms of biological control, they did not reveal the features of the predators that control the abundance of their prey. The most conspicuous example of failure of Lotka-Volterra models applied to insect predator-prey systems are ladybird-aphid systems, in which these models usually fail to fit empirical data. Because of their practical importance and because they are very well studied, we have chosen aphid-ladybird systems as a model. We summarize the results published on various aspects of the population dynamics of aphid-ladybird systems and present them in the context of empirical data. Using new data, we more closely specify the existing metapopulation model of aphid-ladybird interactions. Based on the arguments presented here, we conclude that the ladybird-aphid case can be generalized to insect (and maybe even other) predator-prey systems, where the ratio of the generation times of the predator to that of the prey (GTR) is large. In such systems, the main selection pressure on predators is choosing the best strategy to maximize survival of their offspring, rather than on maximization of the amount of prey eaten. Thus voracity, which is the main determinant of population dynamics in Lotka-Volterra models, loses its role and is replaced by optimization of the choice of oviposition sites in systems with large GTRs. [ABSTRACT FROM AUTHOR]

We aim to understand general consequences of niche construction on metapopulation dynamics in ephemeral landscapes. To this effect, a contact process-like stochastic spatial model is introduced where local populations colonize and go extinct on a dynamic landscape of habitable and destroyed patches. In contrast to previous models, where the extinction threshold is a consequence of available niche rendered by global rates of patch destruction/renewal, here we investigate how the metapopulation persists when they are the sole generators of their own niche. Niche construction is full-filled by localized populations through the transformation of destroyed patches in their neighborhood to viable habitat for future colonization. With this theoretical framework we are able to address the dual nature of niche construction by investigating the ephemerality of the landscape (destruction rate) and the continuum of population level strategies, where construction comes at a cost to colonization. Using mean field theory and Monte Carlo simulations of the model, we are able to quantify optimal population level strategies in a wide range of ephemeral landscapes. Interestingly, we observe qualitative differences at the extinction threshold between analytic and numeric results. Investigating this discrepancy further, we find that increasing niche construction neighborhood in the spatial model leads to two interrelated effects i) an increased rate in range expansion ii) a loss in resiliency and return of the discontinuous transition at the extinction threshold. Furthermore, in the discontinuous regime of the model, spatial clustering prior to a critical transition disappears. This is a significant finding as spatial clustering has been considered to be an early warning signal before ecosystems reach their 'tipping point'. In addition to maintaining stability, we find local niche construction strategies have an advantage when in scramble competition with an exploiter strategy because of their ability to monopolize the constructed niche due to spatial adjacency. As the niche construction neighborhood expands this advantage disappears and the exploiter strategy out-competes the niche constructor. In some cases the exploiter pushes the niche constructor to extinction, thus a tragedy of the commons ensues leading to 'ecological suicide' and a collapse of the niche. [ABSTRACT FROM AUTHOR]