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Many population statistics describe the characteristics of populations within and among species. These are useful for describing population dynamics, understanding how environmental factors alter demographic patterns, testing hypotheses related to the evolution of life history characteristics and informing the effective management of populations.In this study, we propose a population statistic: the interstage flow. The interstage flow is defined as the product of the element in the ith row, the jth column of the population projection matrix and the jth element of the normalized stable stage distribution.The sum of the interstage flow matrix elements is equal to the population growth rate (PGR), which is the dominant eigenvalue of the population projection matrix. The interstage flow matrix elements allow decomposition of PGR into component contributions made by transitions between developmental stages.We demonstrate the utility of interstage flow matrices using matrix population models from the COMPADRE plant matrix database. We compared interstage flows among four life history/functional groups (FGs) (semelparous herbs, iteroparous herbs, shrubs and trees) and described how PGR reflected individual transitions related to stasis, fecundity and growth. We found that the individual flows are different among FGs.Synthesis. The proposed population statistic, the interstage flow matrix, describes the contribution of individual developmental stage transitions to the PGR. The flow of individuals between developmental stages differs in distinctive ways among different life histories and FGs. The interstage flow matrix is a valuable statistic for describing these differences. [ABSTRACT FROM AUTHOR]

Application of herbicides to paddy fields in Japan has strong seasonality, and their environmental concentrations exhibit clear spatiotemporal variation. The authors developed an approach that combines a multimedia environmental exposure model (Grid- Catchment Integrated Modeling System) and density dynamics models for algae. This approach enabled assessment of ecological risk when the exposure concentration shows spatiotemporal variation. First, risk maps of 5 herbicides (pretilachlor, butachlor, simetryn, mefenacet, and esprocarb) were created from the spatial predictions of environmental concentrations and 50% inhibitory concentrations of the herbicides. Simulations of algal density dynamics at high-risk sites were then conducted by incorporating the predicted temporal dynamics of the environmental concentration of each herbicide at the sites. The results suggested that the risk of pretilachlor was clearly the highest of the 5 herbicides, in terms of both the spatial distributions and the temporal durations. The present study highlights the importance of integrating exposure models and effect models to clarify spatial and temporal risk and to develop management plans for chemical exposure that shows high spatiotemporal variation. [ABSTRACT FROM AUTHOR]

Field surveys provide valuable empirical information about the effects of heavy metals on the biological integrity of river ecosystems. To evaluate the effect of nickel (Ni) on aquatic organisms, we conducted field surveys of benthic invertebrates and Ni concentrations at 45 sites in 19 rivers in Japan. We examined the relationships between 11 structural or functional measures of benthic invertebrate communities and free Ni ion concentrations with a 90th quantile regression model. Among the measures, Ephemeroptera, Plecoptera, and Trichoptera (EPT) richness, total wet biomass of all invertebrates, and total abundance of filter feeders were negatively associated with free Ni ion concentrations. The total abundance of mud burrowers and their percentage contribution to the abundance of all invertebrates as well as the total abundances of collector‐gatherers and predators were positively associated with the Ni ion concentrations. The free ion concentrations of Ni associated with a 5% reduction of one of the 3 measures from its 90th quantile value at reference sites (EC5) were estimated to be 0.2 to 7.6 µg/L. The point estimates of EC5 were similar in order of magnitude to the environmental quality standard for Ni in the European Union. However, the usefulness of simple point estimates of effective concentrations based on quantile regression lines should be carefully examined because the uncertainties in our EC5 values were large. Environ Toxicol Chem 2019;38:1728–1737. © 2019 SETAC [ABSTRACT FROM AUTHOR]

Dispersal as well as population growth is a key demographic process that determines population dynamics. However, determining the effects of environmental covariates on dispersal from spatial‐temporal abundance proxy data is challenging owing to the complexity of model specification for directional dispersal permeability and the extremely high computational loads for numerical integration. In this paper, we present a case study estimating how environmental covariates affect the dispersal of Japanese sika deer by developing a spatially explicit state‐space matrix model coupled with an improved numerical integration technique (Markov chain Monte Carlo with particle filters). In particular, we explored the environmental drivers of inhomogeneous range expansion, characteristic of animals with short dispersal. Our model framework successfully reproduced the complex population dynamics of sika deer, including rapid changes in densely populated areas and distribution fronts within a decade. Furthermore, our results revealed that the inhomogeneous range expansion of sika deer seemed to be primarily caused by the dispersal process (i.e., movement barriers in fragmented forests) rather than population growth. Our state‐space matrix model enables the inference of population dynamics for a broad range of organisms, even those with low dispersal ability, in heterogeneous landscapes, and could address many pressing issues in conservation biology and ecosystem management. We present a case study estimating how environmental elements affect the dispersal of Japanese sika deer by developing a spatially explicit state‐space matrix model coupled with an improved numerical integration technique. Our results revealed that the inhomogeneous range expansion of sika deer was primarily caused by the dispersal process (i.e., movement barriers in fragmented forests) rather than population growth. [ABSTRACT FROM AUTHOR]

We review and synthesize recent developments in the study of the invasion of communities in heterogeneous environments, considering both the invasibility of the community and impacts to the community. We consider both empirical and theoretical studies. For each of three major kinds of environmental heterogeneity (temporal, spatial and invader-driven), we find evidence that heterogeneity is critical to the invasibility of the community, the rate of spread, and the impacts on the community following invasion. We propose an environmental heterogeneity hypothesis of invasions, whereby heterogeneity both increases invasion success and reduces the impact to native species in the community, because it promotes invasion and coexistence mechanisms that are not possible in homogeneous environments. This hypothesis could help to explain recent findings that diversity is often increased as a result of biological invasions. It could also explain the scale dependence of the diversity–invasibility relationship. Despite the undoubted importance of heterogeneity to the invasion of communities, it has been studied remarkably little and new research is needed that simultaneously considers invasion, environmental heterogeneity and community characteristics. As a young field, there is an unrivalled opportunity for theoreticians and experimenters to work together to build a tractable theory informed by data. [ABSTRACT FROM AUTHOR]