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The role of species interactions in controlling the interplay between the stability of ecosystems and their biodiversity is still not well understood. The ability of ecological communities to recover after small perturbations of the species abundances (local asymptotic stability) has been well studied, whereas the likelihood of a community to persist when the conditions change (structural stability) has received much less attention. Our goal is to understand the effects of diversity, interaction strengths and ecological network structure on the volume of parameter space leading to feasible equilibria. We develop a geometrical framework to study the range of conditions necessary for feasible coexistence. We show that feasibility is determined by few quantities describing the interactions, yielding a nontrivial complexity–feasibility relationship. Analysing more than 100 empirical networks, we show that the range of coexistence conditions in mutualistic systems can be analytically predicted. Finally, we characterize the geometric shape of the feasibility domain, thereby identifying the direction of perturbations that are more likely to cause extinctions. A central question in theoretical ecology is how diverse species can coexist in communities, and how that coexistence depends on network properties. Here, Grilli et al . quantify the extent of feasible coexistence of empirical networks, showing that it is smaller for trophic than mutualism networks.

Quantifying the abundance of species is essential to ecology, evolution, and conservation. The distribution of species abundances is fundamental to numerous longstanding questions in ecology, yet the empirical pattern at the global scale remains unresolved, with a few species’ abundance well known but most poorly characterized. In large part because of heterogeneous data, few methods exist that can scale up to all species across the globe. Here, we integrate data from a suite of well-studied species with a global dataset of bird occurrences throughout the world—for 9,700 species (∼92% of all extant species)—and use missing data theory to estimate species-specific abundances with associated uncertainty. We find strong evidence that the distribution of species abundances is log left skewed: there are many rare species and comparatively few common species. By aggregating the species-level estimates, we find that there are ∼50 billion individual birds in the world at present. The global-scale abundance estimates that we provide will allow for a line of inquiry into the structure of abundance across biogeographic realms and feeding guilds as well as the consequences of life history (e.g., body size, range size) on population dynamics. Importantly, our method is repeatable and scalable: as data quantity and quality increase, our accuracy in tracking temporal changes in global biodiversity will increase. Moreover, we provide the methodological blueprint for quantifying species-specific abundance, along with uncertainty, for any organism in the world.

A consistent determinant of the establishment success of alien species appears to be the number of individuals that are introduced to found a population (propagule pressure), yet variation in the form of this relationship has been largely unexplored. Here, we present the first quantitative systematic review of this form, using Bayesian meta-analytical methods. The relationship between propagule pressure and establishment success has been evaluated for a broad range of taxa and life histories, including invertebrates, herbaceous plants and long-lived trees, and terrestrial and aquatic vertebrates. We found a positive mean effect of propagule pressure on establishment success to be a feature of every hypothesis we tested. However, establishment success most critically depended on propagule pressures in the range of 10-100 individuals. Heterogeneity in effect size was associated primarily with different analytical approaches, with some evidence of larger effect sizes in animal rather than plant introductions. Conversely, no variation was accounted for in any analysis by the scale of study (field to global) or methodology (observational, experimental, or proxy) used. Our analyses reveal remarkable consistency in the form of the relationship between propagule pressure and alien population establishment success.

Over the past decade, technological advances in experimental and animal tracking techniques have motivated a renewed theoretical interest in animal collective motion and, in particular, locust swarming. This review offers a comprehensive biological background followed by comparative analysis of recent models of locust collective motion, in particular locust marching, their settings, and underlying assumptions. We describe a wide range of recent modeling and simulation approaches, from discrete agent-based models of self-propelled particles to continuous models of integro-differential equations, aimed at describing and analyzing the fascinating phenomenon of locust collective motion. These modeling efforts have a dual role: The first views locusts as a quintessential example of animal collective motion. As such, they aim at abstraction and coarse-graining, often utilizing the tools of statistical physics. The second, which originates from a more biological perspective, views locust swarming as a scientific problem of its own exceptional merit. The main goal should, thus, be the analysis and prediction of natural swarm dynamics. We discuss the properties of swarm dynamics using the tools of statistical physics, as well as the implications for laboratory experiments and natural swarms. Finally, we stress the importance of a combined-interdisciplinary, biological-theoretical effort in successfully confronting the challenges that locusts pose at both the theoretical and practical levels.

Quantifying animals' home ranges is a key problem in ecology and has important conservation and wildlife management applications. Kernel density estimation (KDE) is a workhorse technique for range delineation problems that is both statistically efficient and nonparametric. KDE assumes that the data are independent and identically distributed (IID). However, animal tracking data, which are routinely used as inputs to KDEs, are inherently autocorrelated and violate this key assumption. As we demonstrate, using realistically autocorrelated data in conventional KDEs results in grossly underestimated home ranges. We further show that the performance of conventional KDEs actually degrades as data quality improves, because autocorrelation strength increases as movement paths become more finely resolved. To remedy these flaws with the traditional KDE method, we derive an autocorrelated KDE (AKDE) from first principles to use autocorrelated data, making it perfectly suited for movement data sets. We illustrate the vastly improved performance of AKDE using analytical arguments, relocation data from Mongolian gazelles, and simulations based upon the gazelle's observed movement process. By yielding better minimum area estimates for threatened wildlife populations, we believe that future widespread use of AKDE will have significant impact on ecology and conservation biology.

Species moved by human activities beyond the limits of their native geographic ranges into areas in which they do not naturally occur (termed aliens) can cause a broad range of significant changes to recipient ecosystems; however, their impacts vary greatly across species and the ecosystems into which they are introduced. There is therefore a critical need for a standardised method to evaluate, compare, and eventually predict the magnitudes of these different impacts. Here, we propose a straightforward system for classifying alien species according to the magnitude of their environmental impacts, based on the mechanisms of impact used to code species in the International Union for Conservation of Nature (IUCN) Global Invasive Species Database, which are presented here for the first time. The classification system uses five semi-quantitative scenarios describing impacts under each mechanism to assign species to different levels of impact-ranging from Minimal to Massive-with assignment corresponding to the highest level of deleterious impact associated with any of the mechanisms. The scheme also includes categories for species that are Not Evaluated, have No Alien Population, or are Data Deficient, and a method for assigning uncertainty to all the classifications. We show how this classification system is applicable at different levels of ecological complexity and different spatial and temporal scales, and embraces existing impact metrics. In fact, the scheme is analogous to the already widely adopted and accepted Red List approach to categorising extinction risk, and so could conceivably be readily integrated with existing practices and policies in many regions.

Despite the ecological importance of long-distance dispersal in insects, its mechanistic basis is poorly understood in genetic model species, in which advanced molecular tools are readily available. One critical question is how insects interact with the wind to detect attractive odor plumes and increase their travel distance as they disperse. To gain insight into dispersal, we conducted release-and-recapture experiments in the Mojave Desert using the fruit fly, Drosophila melanogaster. We deployed chemically baited traps in a 1 km radius ring around the release site, equipped with cameras that captured the arrival times of flies as they landed. In each experiment, we released between 30,000 and 200,000 flies. By repeating the experiments under a variety of conditions, we were able to quantify the influence of wind on flies’ dispersal behavior. Our results confirm that even tiny fruit flies could disperse ∼12 km in a single flight in still air and might travel many times that distance in a moderate wind. The dispersal behavior of the flies is well explained by an agent-based model in which animals maintain a fixed body orientation relative to celestial cues, actively regulate groundspeed along their body axis, and allow the wind to advect them sideways. The model accounts for the observation that flies actively fan out in all directions in still air but are increasingly advected downwind as winds intensify. Our results suggest that dispersing insects may strike a balance between the need to cover large distances while still maintaining the chance of intercepting odor plumes from upwind sources.

In recent years, ecologists have stepped up to address the challenges imposed by rapidly changing climates. Some researchers have developed niche-based methods to predict how species will shift their ranges. Such methods have evolved rapidly, resulting in models that incorporate physiological and behavioral mechanisms. Despite their sophistication, these models fail to account for environmental heterogeneity at the scale of an organism. We used an individual-based model to quantify the effects of operative environmental temperatures, as well as their heterogeneity and spatial structure, on the thermoregulation, movement, and energetics of ectotherms. Our simulations showed that the heterogeneity and spatial structure of a thermal landscape are as important as its mean temperature. In fact, temperature and heterogeneity interact to determine organismal performance. Consequently, the popular index of environmental quality (d e), which ignores variance and spatial structure, is inherently flawed as a descriptor of the thermal quality of an environment. Future efforts to model species’ distributions should link thermoregulation and activity to environmental heterogeneity at fine scales.

Well-managed and enforced no-take marine reserves generate important larval subsidies to neighboring habitats and thereby contribute to the long-term sustainability of fisheries. However, larval dispersal patterns are variable, which leads to temporal fluctuations in the contribution of a single reserve to the replenishment of local populations. Identifying management strategies that mitigate the uncertainty in larval supply will help ensure the stability of recruitment dynamics and minimize the volatility in fishery catches. Here, we use genetic parentage analysis to show extreme variability in both the dispersal patterns and recruitment contribution of four individual marine reserves across six discrete recruitment cohorts for coral grouper (Plectropomus maculatus) on the Great Barrier Reef. Together, however, the asynchronous contributions from multiple reserves create temporal stability in recruitment via a connectivity portfolio effect. This dampening effect reduces the variability in larval supply from individual reserves by a factor of 1.8, which effectively halves the uncertainty in the recruitment contribution of individual reserves. Thus, not only does the network of four marine reserves generate valuable larval subsidies to neighboring habitats, the aggregate effect of individual reserves mitigates temporal fluctuations in dispersal patterns and the replenishment of local populations. Our results indicate that small networks of marine reserves yield previously unrecognized stabilizing benefits that ensure a consistent larval supply to replenish exploited fish stocks.

There is increasing evidence that personality traits may drive dispersal patterns of animals, including invasive species. We investigated, using the widespread signal crayfish Pacifastacus leniusculus as a model invasive species, whether effects of personality traits on dispersal were independent of, or affected by, other factors including population density, habitat, crayfish size, sex and limb loss, along an invasion gradient. Behavioural traits (boldness, activity, exploration, willingness to climb) of 310 individually marked signal crayfish were measured at fully-established, newly-established and invasion front sites of two upland streams. After a period at liberty, recaptured crayfish were reassessed for behavioural traits (newly-established, invasion front). Dispersal distance and direction of crayfish movement, local population density, fine-scale habitat characteristics and crayfish size, sex and limb loss were also measured. Individual crayfish exhibited consistency in behavioural traits over time which formed a behavioural syndrome. Dispersal was both positively and negatively affected by personality traits, positively by local population density and negatively by refuge availability. No effect of size, sex and limb loss was recorded. Personality played a role in promoting dispersal but population density and local habitat complexity were also important determinants. Predicting biological invasion in animals is likely to require better integration of these processes.