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Institute
P>Despite ample research, understanding plant spread and predicting their ability to track projected climate changes remain a formidable challenge to be confronted. We modelled the spread of North American wind-dispersed trees in current and future (c. 2060) conditions, accounting for variation in 10 key dispersal, demographic and environmental factors affecting population spread. Predicted spread rates vary substantially among 12 study species, primarily due to inter-specific variation in maturation age, fecundity and seed terminal velocity. Future spread is predicted to be faster if atmospheric CO2 enrichment would increase fecundity and advance maturation, irrespective of the projected changes in mean surface windspeed. Yet, for only a few species, predicted wind-driven spread will match future climate changes, conditioned on seed abscission occurring only in strong winds and environmental conditions favouring high survival of the farthest-dispersed seeds. Because such conditions are unlikely, North American wind-dispersed trees are expected to lag behind the projected climate range shift.
Effects of intraspecific and community density on the lifetime fecundity of long-lived shrubs
(2013)
Intra- and interspecific density dependence has profound consequences for plant population and community dynamics. In long-lived plants, however, lifetime patterns and mechanisms of density dependence are difficult to study. Here, we examine effects of intraspecific and community density on the lifetime fecundity of two long-lived shrub species from South African Fynbos: Protea repens (animal-pollinated, hermaphroditic) and Leucadendron rubrum (wind-pollinated, dioecious). Both species are serotinous, retaining seeds in cones until fire kills the mother plant. We measured lifetime fecundity as the product of cone number, proportion of cones that are not damaged by predation and seed set (fertile seeds per intact cone). Intraspecific and community densities were quantified by counting individuals of target species and all Proteaceae in small- and large-scale neighbourhoods (10 m and 50 m radius) around each focal individual. Additionally, we determined the age and size of focal individuals. We found that lifetime fecundity of the wind-pollinated L rubrum is density independent. In contrast, the lifetime fecundity of the animal-pollinated P. repens increases with large-scale intraspecific density and shows a hump-shaped relationship to large-scale community density. Community density has a hump-shaped effect on seed set (probably through partial absence of generalized pollinators at low and competition for pollinators at high densities) and negatively affects cone number per individual. For both species, plant age decreases seed set while increasing lifetime fecundity. The qualitative differences in the density dependence of lifetime fecundity may arise from differences between animal and wind pollination. In particular, interactions with generalized animal pollinators may cause community-level Allee effects with profound consequences for the future dynamics of long-lived plant populations and communities.
Aim The study and prediction of speciesenvironment relationships is currently mainly based on species distribution models. These purely correlative models neglect spatial population dynamics and assume that species distributions are in equilibrium with their environment. This causes biased estimates of species niches and handicaps forecasts of range dynamics under environmental change. Here we aim to develop an approach that statistically estimates process-based models of range dynamics from data on species distributions and permits a more comprehensive quantification of forecast uncertainties.
Innovation We present an approach for the statistical estimation of process-based dynamic range models (DRMs) that integrate Hutchinson's niche concept with spatial population dynamics. In a hierarchical Bayesian framework the environmental response of demographic rates, local population dynamics and dispersal are estimated conditional upon each other while accounting for various sources of uncertainty. The method thus: (1) jointly infers species niches and spatiotemporal population dynamics from occurrence and abundance data, and (2) provides fully probabilistic forecasts of future range dynamics under environmental change. In a simulation study, we investigate the performance of DRMs for a variety of scenarios that differ in both ecological dynamics and the data used for model estimation.
Main conclusions Our results demonstrate the importance of considering dynamic aspects in the collection and analysis of biodiversity data. In combination with informative data, the presented framework has the potential to markedly improve the quantification of ecological niches, the process-based understanding of range dynamics and the forecasting of species responses to environmental change. It thereby strengthens links between biogeography, population biology and theoretical and applied ecology.
Understanding and predicting the composition and spatial structure of communities is a central challenge in ecology. An important structural property of animal communities is the distribution of individual home ranges. Home range formation is controlled by resource heterogeneity, the physiology and behaviour of individual animals, and their intra- and interspecific interactions. However, a quantitative mechanistic understanding of how home range formation influences community composition is still lacking. To explore the link between home range formation and community composition in heterogeneous landscapes we combine allometric relationships for physiological properties with an algorithm that selects optimal home ranges given locomotion costs, resource depletion and competition in a spatially-explicit individual-based modelling framework. From a spatial distribution of resources and an input distribution of animal body mass, our model predicts the size and location of individual home ranges as well as the individual size distribution (ISD) in an animal community. For a broad range of body mass input distributions, including empirical body mass distributions of North American and Australian mammals, our model predictions agree with independent data on the body mass scaling of home range size and individual abundance in terrestrial mammals. Model predictions are also robust against variation in habitat productivity and landscape heterogeneity. The combination of allometric relationships for locomotion costs and resource needs with resource competition in an optimal foraging framework enables us to scale from individual properties to the structure of animal communities in heterogeneous landscapes. The proposed spatially-explicit modelling concept not only allows for detailed investigation of landscape effects on animal communities, but also provides novel insights into the mechanisms by which resource competition in space shapes animal communities.
Trait-based studies have become extremely common in plant ecology. Trait-based approaches often rely on the tacit assumption that intraspecific trait variability (ITV) is negligible compared to interspecific variability, so that species can be characterized by mean trait values. Yet, numerous recent studies have challenged this assumption by showing that ITV significantly affects various ecological processes. Accounting for ITV may thus strengthen trait-based approaches, but measuring trait values on a large number of individuals per species and site is not feasible. Therefore, it is important and timely to synthesize existing knowledge on ITV in order to (1) decide critically when ITV should be considered, and (2) establish methods for incorporating this variability. Here we propose a practical set of rules to identify circumstances under which ITV should be accounted for. We formulate a spatial trait variance partitioning hypothesis to highlight the spatial scales at which ITV cannot be ignored in ecological studies. We then refine a set of four consecutive questions on the research question, the spatial scale, the sampling design, and the type of studied traits, to determine case-by-case if a given study should quantify ITV and test its effects. We review methods for quantifying ITV and develop a step-by-step guideline to design and interpret simulation studies that test for the importance of ITV. Even in the absence of quantitative knowledge on ITV, its effects can be assessed by varying trait values within species within realistic bounds around the known mean values. We finish with a discussion of future requirements to further incorporate ITV within trait-based approaches. This paper thus delineates a general framework to account for ITV and suggests a direction towards a more quantitative trait-based ecology.
Genetic differentiation in the competitive and reproductive ability of invading populations can result from genetic Allee effects or r/K selection at the local or range-wide scale. However, the neutral relatedness of populations may either mask or falsely suggest adaptation and genetic Allee effects.
In a common-garden experiment, we investigated the competitive and reproductive ability of invasive Senecio inaequidens populations that vary in neutral genetic diversity, population age and field vegetation cover. To account for population relatedness, we analysed the experimental results with 'animal models' adopted from quantitative genetics.
Consistent with adaptive r/K differentiation at local scales, we found that genotypes from low-competition environments invest more in reproduction and are more sensitive to competition. By contrast, apparent effects of large-scale r/K differentiation and apparent genetic Allee effects can largely be explained by neutral population relatedness.
Invading populations should not be treated as homogeneous groups, as they may adapt quickly to small-scale environmental variation in the invaded range. Furthermore, neutral population differentiation may strongly influence invasion dynamics and should be accounted for in analyses of common-garden experiments.
2. We present a hierarchical model that integrates observations from multiple sources to estimate spatio-temporal abundance trends. The model links annual population densities on a spatial grid to both long-term count data and to opportunistic occurrence records from a citizen science programme. Specific observation models for both data types explicitly account for differences in data structure and quality.
3. We test this novel method in a virtual study with simulated data and apply it to the estimation of abundance dynamics across the range of a butterfly species (Pyronia tithonus) in Great Britain between 1985 and 2004. The application to simulated and real data demonstrates how the hierarchical model structure accommodates various sources of uncertainty which occur at different stages of the link between observational data and the modelled abundance, thereby it accounts for these uncertainties in the inference of abundance variations.
4. We show that by using hierarchical observation models that integrate different types of commonly available data sources, we can improve the estimates of variation in species abundances across space and time. This will improve our ability to detect regional trends and can also enhance the empirical basis for understanding range dynamics.
The long-term persistence of populations and species depends on the successful recruitment of individuals. The generative recruitment of plants may be limited by a lack of suitable germination and establishment conditions. Establishment limitation may especially be caused by the competitive effect of surrounding dense vegetation, which is believed to restrict the recruitment success of many plant species to small open patches ('safe sites'). We conducted experiments to clarify the roles of germination and seedling establishment as limiting processes in the recruitment of Juncus atratus Krock., a rare and threatened herbaceous perennial river corridor plant in Central Europe. Light intensity had a positive effect on germination. However, some seedlings emerged even in total darkness and the germination rate at 1% light intensity was more than half of that at 60% light intensity. Seedling establishment in the field after 10 weeks was 30% on bare ground, but it was close to zero in grassland. Establishment in the growth chamber after 8 weeks was close to 75% for seedlings that germinated underwater, but only about 35% for seedlings that germinated afloat. Furthermore, establishment decreased with flooding duration on bare ground, but increased with flooding duration in grassland. These data indicate that establishment, rather than germination, is a critical life stage in Central European populations off. atratus. They furthermore indicate that the competition of surrounding vegetation for water limits seedling establishment under field conditions without flooding, largely restricting establishment success to bare ground habitats. In contrast, grassland is more suitable for the recruitment off. atratus than bare ground under prolonged flooding. Grassland may facilitate the establishment off. atratus seedlings during long- lasting floods by supplying oxygen to the soil through aerenchyma. The shift from competition to facilitation in grassland occurred after 30 days of flooding, i.e. within the ontogeny of individual plants. The specific recruitment requirements off. arrows may be a main cause of its rarity in modern Central Europe. In order to prevent regional extinction off. atratus, we suggest maintaining or re-establishing natural hydrodynamics in the species' habitats.
Improving our understanding of biodiversity and ecosystem functioning and our capacity to inform ecosystem management requires an integrated framework for functional biodiversity research (FBR). However, adequate integration among empirical approaches (monitoring and experimental) and modelling has rarely been achieved in FBR. We offer an appraisal of the issues involved and chart a course towards enhanced integration. A major element of this path is the joint orientation towards the continuous refinement of a theoretical framework for FBR that links theory testing and generalization with applied research oriented towards the conservation of biodiversity and ecosystem functioning. We further emphasize existing decision-making frameworks as suitable instruments to practically merge these different aims of FBR and bring them into application. This integrated framework requires joint research planning, and should improve communication and stimulate collaboration between modellers and empiricists, thereby overcoming existing reservations and prejudices. The implementation of this integrative research agenda for FBR requires an adaptation in most national and international funding schemes in order to accommodate such joint teams and their more complex structures and data needs.