title: Predicting changes in the distribution and abundance of species under environmental change.
abstract: Environmental changes are expected to alter both the distribution and the abundance of organisms. A disproportionate amount of past work has focused on distribution only, either documenting historical range shifts or predicting future occurrence patterns. However, simultaneous predictions of abundance and distribution across landscapes would be far more useful. To critically assess which approaches represent advances towards the goal of joint predictions of abundance and distribution, we review recent work on changing distributions and on effects of environmental drivers on single populations. Several methods have been used to predict changing distributions. Some of these can be easily modified to also predict abundance, but others cannot. In parallel, demographers have developed a much better understanding of how changing abiotic and biotic drivers will influence growth rate and abundance in single populations. However, this demographic work has rarely taken a landscape perspective and has largely ignored the effects of intraspecific density. We advocate a synthetic approach in which population models accounting for both density dependence and effects of environmental drivers are used to make integrated predictions of equilibrium abundance and distribution across entire landscapes. Such predictions would constitute an important step forward in assessing the ecological consequences of environmental changes.
authors.affiliation: Department of Ecology, Environment and Plant Sciences, Stockholm University, Stockholm, Sweden.
authors.forename: Johan
authors.initials: J
authors.lastname: Ehrlén
authors.forename: William F
authors.initials: WF
authors.lastname: Morris
mesh_terms: D063147:Animal Distribution; D000818:Animals; D057231:Climate Change; D017753:Ecosystem; D004777:Environment; D008954:Models, Biological; D011156:Population Density; D011157:Population Dynamics
keywords: Abundance; biotic interactions; climate change; demography; density dependence; environmental drivers; geographical distribution; population model; species distribution model