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Competition is a key process in plant populations and communities. We thus need, if we are to predict the responses of ecological systems to environmental change, a comprehensive and mechanistic understanding of plant competition. Considering competition, however, only at the population level is not sufficient because plant individuals usually are different, interact locally, and can adapt their behaviour to the current state of themselves and of their biotic and abiotic environment. Therefore, simulation models that are individual-based and spatially explicit are increasingly used for studying competition in plant systems. Many different individual-based modelling approaches exist to represent competition, but it is not clear how good they are in reflecting essential aspects of plant competition. We therefore first summarize current concepts and theories addressing plant competition. Then, we review individual-based approaches for modelling competition among plants. We distinguish between approaches that are used for more than 10 years and more recent ones. We identify three major gaps that need to be addressed more in the future: the effects of plants on their local environment, adaptive behaviour, and below-ground competition. To fill these gaps, the representation of plants and their interactions have to be more mechanistic than most existing approaches. Developing such new approaches is a challenge because they are likely to be more complex and to require more detailed knowledge and data on individual-level processes underlying competition. We thus need a more integrated research strategy for the future, where empirical and theoretical ecologists as well as computer scientists work together on formulating, implementing, parameterization, testing, comparing, and selecting the new approaches. (c) 2008 Rubel Foundation, ETH Zurich. Published by Elsevier GmbH. All rights reserved.
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.
The 2009 British Ecological Society"s Annual Symposium entitled 'Facilitation in Plant Communities' was held at the University of Aberdeen, Scotland, from 20 to 22 April 2009. This was the first ever international meeting dedicated to the rapidly expanding field of facilitation. The aim of the symposium was to assess the current 'state-of- play' by contrasting findings from different systems and by looking outwards in an attempt to integrate this field with other related fields. It was also aimed at understanding how knowledge of facilitation can help understand community dynamics and be applied to ecosystem restoration. The symposium identified several key areas where future work is likely to be most profitable.
Morphological plasticity is a striking characteristic of plants in natural communities. In the context of foraging behavior particularly, root plasticity has been documented for numerous species. Root plasticity is known to mitigate competitive interactions by reducing the overlap of the individuals' rhizospheres. But despite its obvious effect on resource acquisition, plasticity has been generally neglected in previous empirical and theoretical studies estimating interaction intensity among plants. In this study, we developed a semi-mechanistic model that addresses this shortcoming by introducing the idea of compensatory growth into the classical-zone-of influence (ZOI) and field-of-neighborhood (FON) approaches. The model parameters describing the belowground plastic sphere of influence (PSI) were parameterized using data from an accompanying field experiment. Measurements of the uptake of a stable nutrient analogue at distinct distances to the neighboring plants showed that the study species responded plastically to belowground competition by avoiding overlap of individuals' rhizospheres. An unexpected finding was that the sphere of influence of the study species Bromus hordeaceus could be best described by a unimodal function of distance to the plant's center and not with a continuously decreasing function as commonly assumed. We employed the parameterized model to investigate the interplay between plasticity and two other important factors determining the intensity of competitive interactions: overall plant density and the distribution of individuals in space. The simulation results confirm that the reduction of competition intensity due to morphological plasticity strongly depends on the spatial structure of the competitive environment. We advocate the use of semi-mechanistic simulations that explicitly consider morphological plasticity to improve our mechanistic understanding of plant interactions.
1.Interactions among plants are key processes that strongly influence the structure and dynamics of plant populations and communities. However, most empirical studies of plant-plant interactions failed to repeatedly measure the plants? response to neighboring individuals and thereby neglected possible changes in interactions throughout the life history of the plants.2.Here, we tested the hypothesis that competition between annual species intensifies from early to late life history stages. To test this hypothesis, we sequentially measured interactions at different levels of water stress. 3.For this purpose, we conducted neighbor-removal experiments in three study sites located along a climatic gradient in Israel. The two annual species Biscutella didyma and Hymenocarpos circinnatus were used as target plants. They grew with and without neighbors in their natural habitats. Five response variables, according to the consecutive life-history stages, (seedling survival, juvenile biomass, adult survival, number of seeds and final biomass) were recorded throughout the whole growing season. 4.The results suggest that direction and intensity of interactions varied considerably between environments and life stages. On average, growth-related response variables indicated higher competition intensity at the productive end of the climatic gradient, while survival indicated either facilitation at the dry end or no trend along the gradient. 5.Considering the temporal aspect, moderate facilitation short after germination shifted to strong competition at the end of the growing season. 6.Our results highlight that the outcome of experimental studies on plant-plant interactions may not only depend on the environmental productivity but even more on the life stage at which a target plant is found.
Disturbances' role in shaping communities is well documented but highly disputed. We suggest replacing the overused two-trait trade-off approach with a functional group scheme, constructed from combinations of four key traits that represent four classes of species' responses to disturbances. Using model results and field observations from sites affected by two highly different disturbances, we demonstrated that popular dichotomous trade-offs are not sufficient to explain community dynamics, even if some emerge under certain conditions. Without disturbances, competition was only sufficient to predict species survival but not relative success, which required some escape mechanism (e.g., long-term dormancy). With highly predictable and large-scale disturbances, successful species showed a combination of high individual tolerance to disturbance and, more surprisingly, high competitive ability. When disturbances were less predictable, high individual tolerance and long-term seed dormancy were favored, due to higher environmental uncertainty. Our study demonstrates that theories relying on a small number of predefined trade-offs among traits (e.g., competition-colonization trade-off) may lead to unrealistic results. We suggest that the understanding of disturbance-community relationships can be significantly improved by employing sets of relevant trait assemblies instead of the currently common approach in which trade-offs are assumed in advance.