Karin Johst

Bio: Karin Johst is an academic researcher from Helmholtz Centre for Environmental Research - UFZ. The author has contributed to research in topics: Population & Biological dispersal. The author has an hindex of 34, co-authored 99 publications receiving 4166 citations. Previous affiliations of Karin Johst include University of Basel & Natural Environment Research Council.

Improving the forecast for biodiversity under climate change

Abstract: BACKGROUND As global climate change accelerates, one of the most urgent tasks for the coming decades is to develop accurate predictions about biological responses to guide the effective protection of biodiversity. Predictive models in biology provide a means for scientists to project changes to species and ecosystems in response to disturbances such as climate change. Most current predictive models, however, exclude important biological mechanisms such as demography, dispersal, evolution, and species interactions. These biological mechanisms have been shown to be important in mediating past and present responses to climate change. Thus, current modeling efforts do not provide sufficiently accurate predictions. Despite the many complexities involved, biologists are rapidly developing tools that include the key biological processes needed to improve predictive accuracy. The biggest obstacle to applying these more realistic models is that the data needed to inform them are almost always missing. We suggest ways to fill this growing gap between model sophistication and information to predict and prevent the most damaging aspects of climate change for life on Earth. ADVANCES On the basis of empirical and theoretical evidence, we identify six biological mechanisms that commonly shape responses to climate change yet are too often missing from current predictive models: physiology; demography, life history, and phenology; species interactions; evolutionary potential and population differentiation; dispersal, colonization, and range dynamics; and responses to environmental variation. We prioritize the types of information needed to inform each of these mechanisms and suggest proxies for data that are missing or difficult to collect. We show that even for well-studied species, we often lack critical information that would be necessary to apply more realistic, mechanistic models. Consequently, data limitations likely override the potential gains in accuracy of more realistic models. Given the enormous challenge of collecting this detailed information on millions of species around the world, we highlight practical methods that promote the greatest gains in predictive accuracy. Trait-based approaches leverage sparse data to make more general inferences about unstudied species. Targeting species with high climate sensitivity and disproportionate ecological impact can yield important insights about future ecosystem change. Adaptive modeling schemes provide a means to target the most important data while simultaneously improving predictive accuracy. OUTLOOK Strategic collections of essential biological information will allow us to build generalizable insights that inform our broader ability to anticipate species’ responses to climate change and other human-caused disturbances. By increasing accuracy and making uncertainties explicit, scientists can deliver improved projections for biodiversity under climate change together with characterizations of uncertainty to support more informed decisions by policymakers and land managers. Toward this end, a globally coordinated effort to fill data gaps in advance of the growing climate-fueled biodiversity crisis offers substantial advantages in efficiency, coverage, and accuracy. Biologists can take advantage of the lessons learned from the Intergovernmental Panel on Climate Change’s development, coordination, and integration of climate change projections. Climate and weather projections were greatly improved by incorporating important mechanisms and testing predictions against global weather station data. Biology can do the same. We need to adopt this meteorological approach to predicting biological responses to climate change to enhance our ability to mitigate future changes to global biodiversity and the services it provides to humans.

Metapopulation persistence in dynamic landscapes: the role of dispersal distance

Abstract: Species associated with transient habitats need efficient dispersal strategies to ensure their regional survival. Using a spatially explicit metapopulation model, we studied the effect of the dispersal range on the persistence of a metapopulation as a function of the local population and landscape dynamics (including habitat patch destruction and subsequent regeneration). Our results show that the impact of the dispersal range depends on both the local population and patch growth. This is due to interactions between dispersal and the dynamics of patches and populations via the number of potential dispersers. In general, long-range dispersal had a positive effect on persistence in a dynamic landscape compared to short-range dispersal. Long-range dispersal increases the number of couplings between the patches and thus the colonisation of regenerated patches. However, long-range dispersal lost its advantage for long-term persistence when the number of potential dispersers was low due to small population growth rates and/or small patch growth rates. Its advantage also disappeared with complex local population dynamics and in a landscape with clumped patch distribution.

Do simple models lead to generality in ecology

Abstract: Modellers of biological, ecological, and environmental systems cannot take for granted the maxim 'simple means general means good'. We argue here that viewing simple models as the main way to achieve generality may be an obstacle to the progress of ecological research. We show how complex models can be both desirable and general, and how simple and complex models can be linked together to produce broad-scale and predictive understanding of biological systems.

Deleterious Mutations Can Surf to High Densities on the Wave Front of an Expanding Population

Abstract: There is an increasing recognition that evolutionary processes play a key role in determining the dynamics of range expansion. Recent work demonstrates that neutral mutations arising near the edge of a range expansion sometimes surf on the expanding front leading them rather than that leads to reach much greater spatial distribution and frequency than expected in stationary populations. Here, we extend this work and examine the surfing behavior of nonneutral mutations. Using an individual-based coupled-map lattice model, we confirm that, regardless of its fitness effects, the probability of survival of a new mutation depends strongly upon where it arises in relation to the expanding wave front. We demonstrate that the surfing effect can lead to deleterious mutations reaching high densities at an expanding front, even when they have substantial negative effects on fitness. Additionally, we highlight that this surfing phenomenon can occur for mutations that impact reproductive rate (i.e., number of offspring produced) as well as mutations that modify juvenile competitive ability. We suggest that these effects are likely to have important consequences for rates of spread and the evolution of spatially expanding populations.

Influence of mowing on the persistence of two endangered large blue butterfly species

Abstract: Mowing influences two endangered butterfly species, Maculinea nausithous and Maculinea teleius, directly through egg destruction and larval mortality on the mown plants and indirectly through altering the abundance of their sequential resources in meadows (Sanguisorba plants for oviposition and early larval development and Myrmica ant nests for later larval development and pupation). Although conservation biologists have argued that mowing during the adult stage is detrimental to population persistence, it is not obvious how the timing and frequency of mowing impact on population dynamics. A simulation model was used to investigate how current 'traditional' mowing regimes could be altered to reconcile butterfly conservation with agriculture. The key mechanism affecting the impact of mowing on population persistence was the interaction between density-independent and density-dependent mortalities in different larval stages of each life cycle. Because of this interaction, optimal mowing regimes for butterfly conservation were sensitive to the type of density regulation displayed by each species, and to landscape attributes such as the influence of climate on resource availability and the level of parasitism. Despite this sensitivity, we were able to identify robust mowing regimes appropriate for a wide range of landscape attributes and to derive general management recommendations. Synthesis and applications. Our results showed that the 'traditional' mowing regime (twice per year with the second cut during the flight period) was always detrimental to the two butterfly species at both local (single population) and regional (metapopulation) scales. However, mowing once a year, or every second or third year, before or after the flight period, was appropriate for both species in the considered landscapes. Maculinea teleius could persist only at a regional scale, assuming dispersal among the meadows, whereas M. nausithous could persist at both local and regional scales. Thus it is essential that the recommended mowing regimes are applied across several connected meadows within reach of dispersing butterflies if both butterflies are to be conserved in a region

Climate Change 2007: Impacts, Adaptation and Vulnerability.

Abstract: Impatti, adattamento e vulnerabilita Le cause e le responsabilita dei cambiamenti climatici sono state trattate sul numero di ottobre della rivista Cda. Approfondiamo l’argomento presentando il documento: “Cambiamenti climatici 2007: impatti, adattamento e vulnerabilita” votato ad aprile 2007 dal secondo gruppo di lavoro del Comitato Intergovernativo sui Cambiamenti Climatici (Intergovernmental Panel on Climate Change). Si tratta del secondo di tre documenti che compongono il quarto rapporto sui cambiamenti climatici.

Causes and consequences of animal dispersal strategies: relating individual behaviour to spatial dynamics.

Abstract: Knowledge of the ecological and evolutionary causes of dispersal can be crucial in understanding the behaviour of spatially structured populations, and predicting how species respond to environmental change. Despite the focus of much theoretical research, simplistic assumptions regarding the dispersal process are still made. Dispersal is usually regarded as an unconditional process although in many cases fitness gains of dispersal are dependent on environmental factors and individual state. Condition-dependent dispersal strategies will often be superior to unconditional, fixed strategies. In addition, dispersal is often collapsed into a single parameter, despite it being a process composed of three interdependent stages: emigration, inter-patch movement and immigration, each of which may display different condition dependencies. Empirical studies have investigated correlates of these stages, emigration in particular, providing evidence for the prevalence of conditional dispersal strategies. Ill-defined use of the term ‘dispersal’, for movement across many different spatial scales, further hinders making general conclusions and relating movement correlates to consequences at the population level. Logistical difficulties preclude a detailed study of dispersal for many species, however incorporating unrealistic dispersal assumptions in spatial population models may yield inaccurate and costly predictions. Further studies are necessary to explore the importance of incorporating specific condition-dependent dispersal strategies for evolutionary and population dynamic predictions.

Individual-based modeling and ecology

Abstract: Individual-based modeling is a new, exciting discipline that allows ecologists to explore, using computer simulations, how properties of populations and ecosystems might evolve from the characteristics and behaviors of individual organisms. Individual-based Modeling and Ecology, written by Volker Grimm and Steven F. Railsback, gives an excellent introduction and overview of this field. It should be read by everyone interested in individual-based modeling, and especially by anyone contemplating developing, or being involved with a group developing, an individualbased model.

Opposing effects of competitive exclusion on the phylogenetic structure of communities

Abstract: Though many processes are involved in determining which species coexist and assemble into communities, competition is among the best studied. One hypothesis about competition's contribution to community assembly is that more closely related species are less likely to coexist. Though empirical evidence for this hypothesis is mixed, it remains a common assumption in certain phylogenetic approaches for inferring the effects of environmental filtering and competitive exclusion. Here, we relate modern coexistence theory to phylogenetic community assembly approaches to refine expectations for how species relatedness influences the outcome of competition. We argue that two types of species differences determine competitive exclusion with opposing effects on relatedness patterns. Importantly, this means that competition can sometimes eliminate more different and less related taxa, even when the traits underlying the relevant species differences are phylogenetically conserved. Our argument leads to a reinterpretation of the assembly processes inferred from community phylogenetic structure.