TY - JOUR A1 - Geyer, Juliane A1 - Kiefer, Iris A1 - Kreft, Stefan A1 - Chavez, Veronica A1 - Salafsky, Nick A1 - Jeltsch, Florian A1 - Ibisch, Pierre L. T1 - Classification of climate-change-induced stresses on biological diversity JF - Conservation biology : the journal of the Society for Conservation Biology N2 - Conservation actions need to account for and be adapted to address changes that will occur under global climate change. The identification of stresses on biological diversity (as defined in the Convention on Biological Diversity) is key in the process of adaptive conservation management. We considered any impact of climate change on biological diversity a stress because such an effect represents a change (negative or positive) in key ecological attributes of an ecosystem or parts of it. We applied a systemic approach and a hierarchical framework in a comprehensive classification of stresses to biological diversity that are caused directly by global climate change. Through analyses of 20 conservation sites in 7 countries and a review of the literature, we identified climate-change-induced stresses. We grouped the identified stresses according to 3 levels of biological diversity: stresses that affect individuals and populations, stresses that affect biological communities, and stresses that affect ecosystem structure and function. For each stress category, we differentiated 3 hierarchical levels of stress: stress class (thematic grouping with the coarsest resolution, 8); general stresses (thematic groups of specific stresses, 21); and specific stresses (most detailed definition of stresses, 90). We also compiled an overview of effects of climate change on ecosystem services using the categories of the Millennium Ecosystem Assessment and 2 additional categories. Our classification may be used to identify key climate-change-related stresses to biological diversity and may assist in the development of appropriate conservation strategies. The classification is in list format, but it accounts for relations among climate-change-induced stresses. KW - adaptation of conservation strategies KW - adaptive management KW - climate change KW - conservation planning KW - conservation targets KW - hierarchical framework KW - threats to biological diversity Y1 - 2011 U6 - https://doi.org/10.1111/j.1523-1739.2011.01676.x SN - 0888-8892 VL - 25 IS - 4 SP - 708 EP - 715 PB - Wiley-Blackwell CY - Malden ER - TY - JOUR A1 - Esther, Alexandra A1 - Groeneveld, Jürgen A1 - Enright, Neal J. A1 - Miller, Ben P. A1 - Lamont, Byron B. A1 - Perry, George L. W. A1 - Tietjen, Britta A1 - Jeltsch, Florian T1 - Low-dimensional trade-offs fail to explain richness and structure in species-rich plant communities JF - Theoretical ecology N2 - Mathematical models and ecological theory suggest that low-dimensional life history trade-offs (i.e. negative correlation between two life history traits such as competition vs. colonisation) may potentially explain the maintenance of species diversity and community structure. In the absence of trade-offs, we would expect communities to be dominated by 'super-types' characterised by mainly positive trait expressions. However, it has proven difficult to find strong empirical evidence for such trade-offs in species-rich communities. We developed a spatially explicit, rule-based and individual-based stochastic model to explore the importance of low-dimensional trade-offs. This model simulates the community dynamics of 288 virtual plant functional types (PFTs), each of which is described by seven life history traits. We consider trait combinations that fit into the trade-off concept, as well as super-types with little or no energy constraints or resource limitations, and weak PFTs, which do not exploit resources efficiently. The model is parameterised using data from a fire-prone, species-rich Mediterranean-type shrubland in southwestern Australia. We performed an exclusion experiment, where we sequentially removed the strongest PFT in the simulation and studied the remaining communities. We analysed the impact of traits on performance of PFTs in the exclusion experiment with standard and boosted regression trees. Regression tree analysis of the simulation results showed that the trade-off concept is necessary for PFT viability in the case of weak trait expression combinations such as low seed production or small seeds. However, species richness and diversity can be high despite the presence of super-types. Furthermore, the exclusion of super-types does not necessarily lead to a large increase in PFT richness and diversity. We conclude that low-dimensional trade-offs do not provide explanations for multi-species co-existence contrary to the prediction of many conceptual models. KW - Plant diversity KW - Plant functional types KW - Co-existence KW - Spatially explicit model KW - Individual-based model KW - CART KW - Regression tree analysis KW - Boosted regression tree Y1 - 2011 U6 - https://doi.org/10.1007/s12080-010-0092-y SN - 1874-1738 VL - 4 IS - 4 SP - 495 EP - 511 PB - Springer CY - Heidelberg ER - TY - JOUR A1 - Giladi, Itamar A1 - Ziv, Yaron A1 - May, Felix A1 - Jeltsch, Florian T1 - Scale-dependent determinants of plant species richness in a semi-arid fragmented agro-ecosystem JF - Journal of vegetation science N2 - Aims: (1) Understanding how the relationship between species richness and its determinants depends on the interaction between scales at which the response and explanatory variables are measured. (2) Quantifying the relative contributions of local, intermediate and large-scale determinants of species richness in a fragmented agro-ecosystem. (3) Testing the hypothesis that the relative contribution of these determinants varies with the grain size at which species richness is measured. Location: A fragmented agro-ecosystem in the Southern Judea Lowland, Israel, within a desert-Mediterranean transition zone. Methods: Plant species richness was estimated using hierarchical nested sampling in 81 plots, positioned in 38 natural vegetation patches within an agricultural matrix (mainly wheat fields) among three land units along a sharp precipitation gradient. Explanatory variables included position along that gradient, patch area, patch isolation, habitat heterogeneity and overall plant density. We used general linear models and hierarchical partitioning of variance to test and quantify the effect of each explanatory variable on species richness at four grain sizes (0.0625, 1, 25 and 225m(2)). Results: Species richness was mainly affected by position along a precipitation gradient and overall plant density, and to a lesser extent by habitat heterogeneity. It was also significantly affected by patch area and patch isolation, but only for small grain sizes. The contribution of each explanatory variable to explained variance in species richness varied with grain size, i.e. scale-dependent. The influence of geographic position and habitat heterogeneity on species richness increased with grain size, while the influence of plant density decreased with grain size. Main conclusions: Species richness is determined by the combined effect of several scale-dependent determinants. Ability to detect an effect and effect size of each determinant varies with the scale (grain size) at which it is measured. The combination of a multi-factorial approach and multi-scale sampling reveals that conclusions drawn from studies that ignore these dimensions are restricted and potentially misleading. KW - Habitat fragmentation KW - Hierarchical partitioning of variance KW - Multi-grain sampling KW - Scale-dependence KW - Species density KW - Uniform sampling Y1 - 2011 U6 - https://doi.org/10.1111/j.1654-1103.2011.01309.x SN - 1100-9233 VL - 22 IS - 6 SP - 983 EP - 996 PB - Wiley-Blackwell CY - Malden ER - TY - JOUR A1 - Schiffers, Katja A1 - Tielboerger, Katja A1 - Tietjen, Britta A1 - Jeltsch, Florian T1 - Root plasticity buffers competition among plants theory meets experimental data JF - Ecology : a publication of the Ecological Society of America N2 - 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. KW - Bromus hordeaceus KW - competition intensity KW - morphological plasticity KW - nutrient analogues KW - plant density KW - PSI (plastic sphere of influence) KW - zone-of-influence model Y1 - 2011 SN - 0012-9658 VL - 92 IS - 3 SP - 610 EP - 620 PB - Wiley CY - Washington ER - TY - JOUR A1 - Buchmann, Carsten M. A1 - Schurr, Frank Martin A1 - Nathan, Ran A1 - Jeltsch, Florian T1 - An allometric model of home range formation explains the structuring of animal communities exploiting heterogeneous resources JF - Oikos N2 - 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. Y1 - 2011 U6 - https://doi.org/10.1111/j.1600-0706.2010.18556.x SN - 0030-1299 VL - 120 IS - 1 SP - 106 EP - 118 PB - Wiley-Blackwell CY - Malden ER - TY - JOUR A1 - Blaum, Niels A1 - Mosner, Eva A1 - Schwager, Monika A1 - Jeltsch, Florian T1 - How functional is functional?Ecological groupings in terrestrial animal ecology - towards an animal functional type approach JF - Biodiversity and conservation N2 - Understanding mechanisms to predict changes in plant and animal communities is a key challenge in ecology. The need to transfer knowledge gained from single species to a more generalized approach has led to the development of categorization systems where species' similarities in life strategies and traits are classified into ecological groups (EGs) like functional groups/types or guilds. While approaches in plant ecology undergo a steady improvement and refinement of methodologies, progression in animal ecology is lagging behind. With this review, we aim to initiate a further development of functional classification systems in animal ecology, comparable to recent developments in plant ecology. We here (i) give an overview of terms and definitions of EGs in animal ecology, (ii) discuss existing classification systems, methods and application areas of EGs (focusing on terrestrial vertebrates), and (iii) provide a "roadmap towards an animal functional type approach" for improving the application of EGs and classifications in animal ecology. We found that an animal functional type approach requires: (i) the identification of core traits describing species' dependency on their habitat and life history traits, (ii) an optimization of trait selection by clustering traits into hierarchies, (iii) the assessment of "soft traits" as substitute for hardly measurable traits, e.g. body size for dispersal ability, and (iv) testing of delineated groups for validation including experiments. KW - Ecological classification KW - Functional type KW - Guild KW - Functional trait KW - Trait selection KW - Effect group KW - Response group KW - Environmental relationships Y1 - 2011 U6 - https://doi.org/10.1007/s10531-011-9995-1 SN - 0960-3115 VL - 20 IS - 11 SP - 2333 EP - 2345 PB - Springer CY - Dordrecht ER -