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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.
Intraspecific trait variation (ITV) is thought to play a significant role in community assembly, but the magnitude and direction of its influence are not well understood. Although it may be critical to better explain population persistence, species interactions, and therefore biodiversity patterns, manipulating ITV in experiments is challenging. We therefore incorporated ITV into a trait‐ and individual‐based model of grassland community assembly by adding variation to the plants’ functional traits, which then drive life‐history tradeoffs. Varying the amount of ITV in the simulation, we examine its influence on pairwise‐coexistence and then on the species diversity in communities of different initial sizes. We find that ITV increases the ability of the weakest species to invade most, but that this effect does not scale to the community level, where the primary effect of ITV is to increase the persistence and abundance of the competitively‐average species. Diversity of the initial community is also of critical importance in determining ITV's efficacy; above a threshold of interspecific diversity, ITV does not increase diversity further. For communities below this threshold, ITV mainly helps to increase diversity in those communities that would otherwise be low‐diversity. These findings suggest that ITV actively maintains diversity by helping the species on the margins of persistence, but mostly in habitats of relatively low alpha and beta diversity.
Use of large Acacia trees by the cavity dwelling Black-tailed Tree Rat in the southern Kalahari
(2006)
Recent extensive harvesting of large, often dead Acacia trees in and savanna of southern Africa is cause for concern about the conservation status of the arid savanna and its animal community. We mapped vegetation and nests of the Black-tailed Tree Rat Thallomy's nigricauda to assess the extent to which the rats depend on particular tree species and on the existence of dead, standing trees. The study was conducted in continuous Acacia woodland on the southern and eastern edge of the Kalahari, South Africa. Trees in which there were tree rat nests were compared with trees of similar size and vigour to identify the characteristics of nest sites. Spatial analysis of tree rat distribution was conducted using Ripley's-L function. We found that T nigricauda was able to utilize all available tree species, as long as trees were large and old enough so that cavities were existing inside the stem. The spatial distribution of nest trees did not show clumping at the investigated scale, and we therefore reject the notion of the rats forming colonies when inhabiting continuous woodlands. The selection of a particular tree as a nest site was furthermore depending on the close proximity of the major food plant, Acacia mellifera. This may limit the choice of suitable nest sites. since A. mellifera was less likely to grow within a vegetation patch containing a large trees than in patches without large trees.
Question: The majority of studies investigating the impact of climate change on local plant communities ignores changes in regional processes, such as immigration from the regional seed pool. Here we explore: (i) the potential impact of climate change on composition of the regional seed pool, (ii) the influence of changes in climate and in the regional seed pool on local community structure, and (iii) the combinations of life history traits, i.e. plant functional types (PFTs), that are most affected by environmental changes. Location: Fire-prone, Mediterranean-type shrublands in southwestern Australia. Methods: Spatially explicit simulation experiments were conducted at the population level under different rainfall and fire regime scenarios to determine the effect of environmental change on the regional seed pool for 38 PFTs. The effects of environmental and seed immigration changes on local community dynamics were then derived from community-level experiments. Classification tree analyses were used to investigate PFT- specific vulnerabilities to climate change. Results: The classification tree analyses revealed that responses of PFTs to climate change are determined by specific trait characteristics. PFT-specific seed production and community patterns responded in a complex manner to climate change. For example, an increase in annual rainfall caused an increase in numbers of dispersed seeds for some PFTs, but decreased PFT diversity in the community. Conversely, a simulated decrease in rainfall reduced the number of dispersed seeds and diversity of PFTs. Conclusions: PFT interactions and regional processes must be considered when assessing how local community structure will be affected by environmental change.
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.
Low-dimensional trade-offs fail to explain richness and structure in species-rich plant communities
(2011)
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.
East Africa hosts a striking diversity of terrestrial ecosystems, which vary both in space and time due to complex regional topography and a dynamic climate. The structure and functioning of these ecosystems under this environmental setting can be studied with dynamic vegetation models (DVMs) in a spatially explicit way. Yet, regional applications of DVMs to East Africa are rare and a comprehensive validation of such applications is missing. Here, we simulated the present-day and mid-Holocene vegetation of East Africa with the DVM, LPJ-GUESS and we conducted an exhaustive comparison of model outputs with maps of potential modern vegetation distribution, and with pollen records of local change through time. Overall, the model was able to reproduce the observed spatial patterns of East African vegetation. To see whether running the model at higher spatial resolutions (10′ × 10′) contribute to resolve the vegetation distribution better and have a better comparison scale with the observational data (i.e. pollen data), we run the model with coarser spatial resolution (0.5° × 0.5°) for the present-day as well. Both the area- and point-wise comparison showed that a higher spatial resolution allows to better describe spatial vegetation changes induced by the complex topography of East Africa. Our analysis of the difference between modelled mid-Holocene and modern-day vegetation showed that whether a biome shifts to another is best explained by both the amount of change in precipitation it experiences and the amount of precipitation it received originally. We also confirmed that tropical forest biomes were more sensitive to a decrease in precipitation compared to woodland and savanna biomes and that Holocene vegetation changes in East Africa were driven not only by changes in annual precipitation but also by changes in its seasonality.
The El Nino-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security.
The El Nino-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security.
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.
Protected areas are arguably the most important instrument of biodiversity conservation. To keep them fit under climate change, their management needs to be adapted to address related direct and indirect changes. In our study we focus on the adaptation of conservation management planning, evaluating management plans of 60 protected areas throughout Germany with regard to their climate change-robustness. First, climate change-robust conservation management was defined using 11 principles and 44 criteria, which followed an approach similar to sustainability standards. We then evaluated the performance of individual management plans concerning the climate change-robustness framework. We found that climate change-robustness of protected areas hardly exceeded 50 percent of the potential performance, with most plans ranking in the lower quarter. Most Natura 2000 protected areas, established under conservation legislation of the European Union, belong to the sites with especially poor performance, with lower values in smaller areas. In general, the individual principles showed very different rates of accordance with our principles, but similarly low intensity. Principles with generally higher performance values included holistic knowledge management, public accountability and acceptance as well as systemic and strategic coherence. Deficiencies were connected to dealing with the future and uncertainty. Lastly, we recommended the presented principles and criteria as essential guideposts that can be used as a checklist for working towards more climate change-robust planning.
Conservation actions need to account for global climate change and adapt to it. The body of the literature on adaptation options is growing rapidly, but their feasibility and current state of implementation are rarely assessed. We discussed the practicability of adaptation options with conservation managers analysing three fields of action: reducing the vulnerability of conservation management, reducing the vulnerability of conservation targets (i.e. biodiversity) and climate change mitigation. For all options, feasibility, current state of implementation and existing obstacles to implementation were analysed, using the Federal State of Brandenburg, Germany, as a case study. Practitioners considered a large number of options useful, most of which have already been implemented at least in part. Those options considered broadly implemented resemble mainly conventional measures of conservation without direct relation to climate change. Managers are facing several obstacles for adapting to climate change, including political reluctance to change, financial and staff shortages in conservation administrations and conflictive EU funding schemes in agriculture. A certain reluctance to act, due to the high degree of uncertainty with regard to climate change scenarios and impacts, is widespread. A lack of knowledge of appropriate methods such as adaptive management often inhibits the implementation of adaptation options in the field of planning and management. Based on the findings for Brandenburg, we generally conclude that it is necessary to focus in particular on options that help to reduce vulnerability of conservation management itself, i.e. those that enhance management effectiveness. For instance, adaptive and proactive risk management can be applied as a no-regrets option, independently from specific climate change scenarios or impacts, strengthening action under uncertainty.
Scale-dependent determinants of plant species richness in a semi-arid fragmented agro-ecosystem
(2011)
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.
Agent-based complex systems are dynamic networks of many interacting agents; examples include ecosystems, financial markets, and cities. The search for general principles underlying the internal organization of such systems often uses bottom-up simulation models such as cellular automata and agent-based models. No general framework for designing, testing, and analyzing bottom-up models has yet been established, but recent advances in ecological modeling have come together in a general strategy we call pattern-oriented modeling. This strategy provides a unifying framework for decoding the internal organization of agent-based complex systems and may lead toward unifying algorithmic theories of the relation between adaptive behavior and system complexity
Give chance a chance
(2019)
A large part of biodiversity theory is driven by the basic question of what allows species to coexist in spite of a confined number of niches. A substantial theoretical background to this question is provided by modern coexistence theory (MCT), which rests on mathematical approaches of invasion analysis to categorize underlying mechanisms into factors that reduce either niche overlap (stabilizing mechanisms) or the average fitness differences of species (equalizing mechanisms). While MCT has inspired biodiversity theory in the search for these underlying mechanisms, we feel that the strong focus on coexistence causes a bias toward the most abundant species and neglects the plethora of species that are less abundant and often show high local turnover. Given the more stochastic nature of their occurrence, we advocate a complementary cross-level approach that links individuals, small populations, and communities and explicitly takes into account (1) a more complete inclusion of environmental and demographic stochasticity affecting small populations, (2) intraspecific trait variation and behavioral plasticity, and (3) local heterogeneities, interactions, and feedbacks. Focusing on mechanisms that drive the temporary coviability of species rather than infinite coexistence, we suggest a new approach that could be dubbed coviability analysis (CVA). From a modeling perspective, CVA builds on the merged approaches of individual-based modeling and population viability analysis but extends them to the community level. From an empirical viewpoint, CVA calls for a stronger integration of spatiotemporal data on variability and noise, changing drivers, and interactions at the level of individuals. The resulting large volumes of data from multiple sources could be strongly supported by novel techniques tailored to the discovery of complex patterns in high-dimensional data. By complementing MCT through a stronger focus on the coviability of less common species, this approach can help make modern biodiversity theory more comprehensive, predictive, and relevant for applications.
The small fox tapeworm (Echinococcus multilocularis) shows a heterogeneous spatial distribution in the intermediate host (Microtus arvalis). To identify the ecological processes responsible for this heterogeneity, we developed a spatially explicit simulation model. The model combines individual-based (foxes, Vulpes vulpes) and grid- based (voles) techniques to simulate the infections in both intermediate and definite host. If host populations are homogeneously mixed, the model reproduces field data for parasite prevalence only for a limited number of parameter combinations. As ecological parameters inevitably vary to a certain degree, we discarded the homogeneous mixing model as insufficient to gain insight into the ecology of the fox tapeworm cycle. We analysed five different model scenarios, each focussing on an ecological process that might be responsible for the heterogeneous spatial distribution of E multilocularis in the intermediate host. Field studies revealed that the prevalence ratio between intermediate and definite host remains stable over a wide range of ecological conditions. Thus, by varying the parameters in simulation experiments, we used the robustness of the agreement between field data and model output as quality criterion for the five scenarios. Only one of the five scenarios was found to reproduce the prevalence ratio over a sufficient range of parameter combinations. In the accentuated scenario most tapeworm eggs die due to bad environmental conditions before they cause infections in the intermediate host. This scenario is supported by the known sensitivity of tapeworm eggs to high temperatures and dry conditions. The identified process is likely to lead to a heterogeneous availability of infective eggs and thus to a clumped distribution of infected intermediate hosts. In conclusion, areas with humid conditions and low temperatures must be pointed out as high risk areas for human exposure to E. multilocularis eggs as well. (C) 2004 on behalf of Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved