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Institute
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.
Fragmentation and loss of habitat are major threats to animal communities and are therefore important to conservation. Due to the complexity of the interplay of spatial effects and community processes, our mechanistic understanding of how communities respond to such landscape changes is still poor. Modelling studies have mostly focused on elucidating the principles of community response to fragmentation and habitat loss at relatively large spatial and temporal scales relevant to metacommunity dynamics. Yet, it has been shown that also small scale processes, like foraging behaviour, space use by individuals and local resource competition are also important factors. However, most studies that consider these smaller scales are designed for single species and are characterized by high model complexity. Hence, they are not easily applicable to ecological communities of interacting individuals. To fill this gap, we apply an allometric model of individual home range formation to investigate the effects of habitat loss and fragmentation on mammal and bird communities, and, in this context, to investigate the role of interspecific competition and individual space use. Results show a similar response of both taxa to habitat loss. Community composition is shifted towards higher frequency of relatively small animals. The exponent and the 95%-quantile of the individual size distribution (ISD, described as a power law distribution) of the emerging communities show threshold behaviour with decreasing habitat area. Fragmentation per se has a similar and strong effect on mammals, but not on birds. The ISDs of bird communities were insensitive to fragmentation at the small scales considered here. These patterns can be explained by competitive release taking place in interacting animal communities, with the exception of bird's buffering response to fragmentation, presumably by adjusting the size of their home ranges. These results reflect consequences of higher mobility of birds compared to mammals of the same size and the importance of considering competitive interaction, particularly for mammal communities, in response to landscape fragmentation. Our allometric approach enables scaling up from individual physiology and foraging behaviour to terrestrial communities, and disentangling the role of individual space use and interspecific competition in controlling the response of mammal and bird communities to landscape changes.
Habitat loss poses a severe threat to biodiversity. While many studies yield valuable information on how specific species cope with such environmental modification, the mechanistic understanding of how interacting species or whole communities are affected by habitat loss is still poor. Individual movement plays a crucial role for the space use characteristics of species, since it determines how individuals perceive and use their heterogeneous environment. At the community level, it is therefore essential to include individual movement and how it is influenced by resource sharing into the investigation of consequences of habitat loss. To elucidate the effects of foraging movement on communities in face of habitat loss, we here apply a recently published spatially-explicit and individual-based model of home range formation. This approach allows predicting the individual size distribution (ISD) of mammal communities in simulation landscapes that vary in the amount of suitable habitat. We apply three fundamentally different foraging movement approaches (central place forager (CPF), patrolling forager (PF) and body mass dependent nomadic forager (BNF)). Results show that the efficiency of the different foraging strategies depends on body mass, which again affects community structure in face of habitat loss. CPF is only efficient for small animals, and therefore yields steep ISD exponents on which habitat loss has little effect (due to a movement limitation of body mass). PF and particularly BNF are more efficient for larger animals, resulting in less steep ISDs with higher mass maxima, both showing a threshold behaviour with regard to loss of suitable habitat. These findings represent a new way of explaining observed extinction thresholds, and therefore indicate the importance of individual space use characterized by physiology and behaviour, i.e. foraging movement, for communities and their response to habitat loss. Findings also indicate the necessity to incorporate the crucial role of movement into future conservation efforts of terrestrial communities.
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.
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.
Modelling and empirical studies have shown that input from the regional seed pool is essential to maintain local species diversity. However, most of these studies have concentrated on simplified, if not neutral, model systems, and focus on a limited subset of species or on aggregated measures of diversity only (e.g., species richness or Shannon diversity). Thus they ignore more complex species interactions and important differences between species. To gain a better understanding of how seed immigration affects community structure at the local scale in real communities we conducted computer simulation experiments based on plant functional types (PFTs) for a species-rich, fire-prone Mediterranean-type shrubland in Western Australia. We developed a spatially explicit simulation model to explore the community dynamics of 38 PFTs, defined by seven traits - regeneration mode, seed production, seed size, maximum crown diameter, drought tolerance, dispersal mode and seed bank type - representing 78 woody species. Model parameterisation is based on published and unpublished data on the population dynamics of shrub species collected over 18 years. Simulation experiments are based on two contrasting seed immigration scenarios: (1) the 'equal seed input number' scenario, where the number of immigrant seeds is the same for all PFTs, and (2) the 'equal seed input mass' scenario, where the cumulative mass of migrating seeds is the same for all PFTs. Both scenarios were systematically tested and compared for different overall seed input values. Without immigration the local community drifts towards a state with only 13 coexisting PFTs. With increasing immigration rates in terms of overall mass of seeds the simulated number of coexisting PFTs and Shannon diversity quickly approaches values observed in the field. The equal seed mass scenario resulted in a more diverse community than did the seed number scenario. The model successfully approximates the frequency distributions (relative densities) of all individual plant traits except seed size for scenarios associated with equal seed input mass and high immigration rate. However, no scenario satisfactorily approximated the frequency distribution for all traits in combination. Our results show that regional seed input can explain the more aggregated measures of local community structure, and some, but not all, aspects of community composition. This points to the possible importance of other (untested) processes and traits (e.g., dispersal vectors) operating at the local scale. Our modelling framework can readily allow new factors to be systematically investigated, which is a major advantage compared to previous simulation studies, as it allows us to find structurally realistic models, which can address questions pertinent to ecological theory and to conservation management.
1. Anthropogenic changes in the global climate are shifting the potential ranges of many plant species. 2. Changing climates will allow some species the opportunity to expand their range, others may experience a contraction in their potential range, while the current and future ranges of some species may not overlap. Our capacity to generalize about the threat these range shifts pose to plant diversity is limited by many sources of uncertainty. 3. In this paper we summarize sources of uncertainty for migration forecasts and suggest a research protocol for making forecasts in the context of uncertainty.
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.
Plant population modelling has been around since the 1970s, providing a valuable approach to understanding plant ecology from a mechanistic standpoint. It is surprising then that this area of research has not grown in prominence with respect to other approaches employed in modelling plant systems. In this review, we provide an analysis of the development and role of modelling in the field of plant population biology through an exploration of where it has been, where it is now and, in our opinion, where it should be headed. We focus, in particular, on the role plant population modelling could play in ecological forecasting, an urgent need given current rates of regional and global environmental change. We suggest that a critical element limiting the current application of plant population modelling in environmental research is the trade-off between the necessary resolution and detail required to accurately characterize ecological dynamics pitted against the goal of generality, particularly at broad spatial scales. In addition to suggestions how to overcome the current shortcoming of data on the process-level we discuss two emerging strategies that may offer a way to overcome the described limitation: (1) application of a modern approach to spatial scaling from local processes to broader levels of interaction and (2) plant functional-type modelling. Finally we outline what we believe to be needed in developing these approaches towards a 'science of forecasting'.
Shrub encroachment, i.e. the increase in woody plant cover, is a major concern for livestock farming in southern Kalahari savannas. We developed a grid-based computer model simulating the population dynamics of Grewia flava, a common, fleshy-fruited encroaching shrub. In the absence of large herbivores, seeds of Grewia are largely deposited in the sub-canopy of Acacia erioloba. Cattle negate this dispersal limitation by browsing on the foliage of Grewia and dispersing seeds into the grassland matrix. In this study we first show that model predictions of Grewia cover dynamics are realistic by comparing model output with shrub cover estimates obtained from a time series of aerial photographs. Subsequently, we apply a realistic range of intensity of cattle-induced seed dispersal combined with potential precipitation and fire scenarios. Based on the simulation results we suggest that cattle may facilitate shrub encroachment of Grewia. The results show that the severity of shrub encroachment is governed by the intensity of seed dispersal. For a high seed dispersal intensity without fire (equivalent to a high stocking rate) the model predicts 56% shrub cover and 85% cell cover after 100 yr. With fire both recruitment and shrub cover are reduced, which may, under moderate intensities, prevent shrub encroachment. Climate change scenarios with two-fold higher frequencies of drought and wet years intensified shrub encroachment rates, although long-term mean of precipitation remained constant. As a management recommendation we suggest that shrub encroachment on rangelands may be counteracted by frequent fires and controlling cattle movements to areas with a high proportion of fruiting Grewia shrubs
Aim Biotic interactions within guilds or across trophic levels have widely been ignored in species distribution models (SDMs). This synthesis outlines the development of species interaction distribution models (SIDMs), which aim to incorporate multispecies interactions at large spatial extents using interaction matrices. Location Local to global. Methods We review recent approaches for extending classical SDMs to incorporate biotic interactions, and identify some methodological and conceptual limitations. To illustrate possible directions for conceptual advancement we explore three principal ways of modelling multispecies interactions using interaction matrices: simple qualitative linkages between species, quantitative interaction coefficients reflecting interaction strengths, and interactions mediated by interaction currencies. We explain methodological advancements for static interaction data and multispecies time series, and outline methods to reduce complexity when modelling multispecies interactions. Results Classical SDMs ignore biotic interactions and recent SDM extensions only include the unidirectional influence of one or a few species. However, novel methods using error matrices in multivariate regression models allow interactions between multiple species to be modelled explicitly with spatial co-occurrence data. If time series are available, multivariate versions of population dynamic models can be applied that account for the effects and relative importance of species interactions and environmental drivers. These methods need to be extended by incorporating the non-stationarity in interaction coefficients across space and time, and are challenged by the limited empirical knowledge on spatio-temporal variation in the existence and strength of species interactions. Model complexity may be reduced by: (1) using prior ecological knowledge to set a subset of interaction coefficients to zero, (2) modelling guilds and functional groups rather than individual species, and (3) modelling interaction currencies and species effect and response traits. Main conclusions There is great potential for developing novel approaches that incorporate multispecies interactions into the projection of species distributions and community structure at large spatial extents. Progress can be made by: (1) developing statistical models with interaction matrices for multispecies co-occurrence datasets across large-scale environmental gradients, (2) testing the potential and limitations of methods for complexity reduction, and (3) sampling and monitoring comprehensive spatio-temporal data on biotic interactions in multispecies communities.
Assessing the risk of gene flow from genetically modified trees carrying mitigation transgenes
(2008)
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.
In common garden experiments, a number of genotypes are raised in a common environment in order to quantify the genetic component of phenotypic variation. Common gardens are thus ideally suited for disentangling how genetic and environmental factors contribute to the success of invasive species in their new non-native range. Although common garden experiments are increasingly employed in the study of invasive species, there has been little discussion about how these experiments should be designed for greatest utility. We argue that this has delayed progress in developing a general theory of invasion biology. We suggest a minimum optimal design (MOD) for common garden studies that target the ecological and evolutionary processes leading to phenotypic differentiation between native and invasive ranges. This involves four elements: (A) multiple, strategically sited garden locations, involving at the very least four gardens (2 in the native range and 2 in the invaded range); (B) careful consideration of the genetic design of the experiment; (C) standardization of experimental protocols across all gardens; and (D) care to ensure the biosafety of the experiment. Our understanding of the evolutionary ecology of biological invasions will be greatly enhanced by common garden studies, if and only if they are designed in a more systematic fashion, incorporating at the very least the MOD suggested here.
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.
Growing recognition of the importance of long-distance dispersal (LDD) of plant seeds for various ecological and evolutionary processes has led to an upsurge of research into the mechanisms underlying LDD. We summarize these findings by formulating six generalizations stating that LDD is generally more common in open terrestrial landscapes, and is typically driven by large and migratory animals, extreme meteorological phenomena, ocean currents and human transportation, each transporting a variety of seed morphologies. LDD is often associated with unusual behavior of the standard vector inferred from plant dispersal morphology, or mediated by nonstandard vectors. To advance our understanding of LDD, we advocate a vector-based research approach that identifies the significant LDD vectors and quantifies how environmental conditions modify their actions.
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.
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.