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Disturbances are characteristic for many ecosystems. However, we still lack generalizations concerning their role in shaping communities, particularly when disturbances co-occur. To study such effects, we used a novel modeling approach that is unrestricted by a priori tradeoffs among specific plant traits, except for those generated by allocation principles. Thus, trait combinations were emergent properties associated with biotic and abiotic constraints. Specifically, we asked which traits dominate under specific disturbance regimes, whether single and combined disturbance regimes promote similar trait tradeoffs and how complex disturbance regimes affect species richness and functional diversity. Overall, disturbances' temporal properties governed the outcome of combined disturbances and were a stronger assortative force than spatial disturbance properties: low temporal predictability decreased seed-dispersability and dormancy, but increased competitive ability and disturbance tolerance. Evidence for tradeoffs between different colonization modes and between dormancy and disturbance tolerance were found, while surprisingly, the widely accepted colonization-competition tradeoff was not generated. Diversity was highest at intermediate disturbance intensity, but decreased monotonically with increasing unpredictability. In accordance with our results, future models should avoid restrictive assumptions about tradeoffs to generate robust and more general predictions about the role of disturbances for community dynamics.
Encroachment of shrubs into the unique pastoral grassland ecosystems of the Tibetan Plateau has significant impact on ecosystem services, especially forage production. We developed a process-based ecohydrological model to identify the relative importance of the main drivers of shrub encroachment for the alpine meadows within the Qinghai province. Specifically, we explored the effects of summer livestock grazing (intensity and type of livestock) together with the effects of climate warming, including interactions between herbaceous and woody vegetation and feedback loops between soil, water and vegetation. Under current climatic conditions and a traditional herd composition, an increasing grazing intensity above a threshold value of 0.32 +/- 0.10 large stock units (LSU) ha(-1) day(-1) changes the vegetation composition from herbaceous towards a woody and bare soil dominated system. Very high grazing intensity (above 0.8 LSU ha(-1) day(-1)) leads to a complete loss of any vegetation. Under warmer conditions, the vegetation showed a higher resilience against livestock farming. This resilience is enhanced when the herd has a higher browser : grazer ratio. A cooler climate has a shrub encroaching effect, whereas warmer conditions increase the cover of the herbaceous vegetation. This effect was primarily due to season length and an accompanied competitive loss of slower growing shrubs, rather than evaporative water loss leading to less soil water in deeper soil layers for deeper rooting shrubs. If climate warming is driving current shrub encroachment, we conclude it is only indirectly so. It would be manifest by an advancing shrubline and could be regarded as a climatic escape of specific shrub species such as Potentilla fruticosa. Under the recent high intensity of grazing, only herding by more browsing animals can potentially prevent both shrub encroachment and the complete loss of herbaceous vegetation.
Non-consumptive effects of predators within ecosystems can alter the behavior of individual prey species, and have cascading effects on other trophic levels. In this context, an understanding of non-consumptive predator effects on the whole prey community is crucial for predicting community structure and composition, hence biodiversity patterns. We used an individual-based, spatially-explicit modelling approach to investigate the consequences of landscapes of fear on prey community metrics. The model spans multiple hierarchical levels from individual home range formation based on food availability and perceived predation risk to consequences on prey community structure and composition. This mechanistic approach allowed us to explore how important factors such as refuge availability and foraging strategy under fear affect prey community metrics. Fear of predators affected prey space use, such as home range formation. These adaptations had broader consequences for the community leading to changes in community structure and composition. The strength of community responses to perceived predation risk was driven by refuge availability in the landscape and the foraging strategy of prey animals. Low refuge availability in the landscape strongly decreased diversity and total biomass of prey communities. Additionally, body mass distributions in prey communities facing high predation risk were shifted towards small prey animals. With increasing refuge availability the consequences of non-consumptive predator effects were reduced, diversity and total biomass of the prey community increased. Prey foraging strategies affected community composition. Under medium refuge availability, risk-averse prey communities consisted of many small animals while risk-taking prey communities showed a more even body mass distribution. Our findings reveal that non-consumptive predator effects can have important implications for prey community diversity and should therefore be considered in the context of conservation and nature management.
Semi-natural grasslands, biodiversity hotspots in Central-Europe, suffer from the cessation of traditional land-use. Amount and intensity of these changes challenge current monitoring frameworks typically based on classic indicators such as selected target species or diversity indices. Indicators based on plant functional traits provide an interesting extension since they reflect ecological strategies at individual and ecological processes at community levels. They typically show convergent responses to gradients of land-use intensity over scales and regions, are more directly related to environmental drivers than diversity components themselves and enable detecting directional changes in whole community dynamics. However, probably due to their labor- and cost intensive assessment in the field, they have been rarely applied as indicators so far.
Here we suggest overcoming these limitations by calculating indicators with plant traits derived from online accessible databases. Aiming to provide a minimal trait set to monitor effects of land-use intensification on plant diversity we investigated relationships between 12 community mean traits, 2 diversity indices and 6 predictors of land-use intensity within grassland communities of 3 different regions in Germany (part of the German 'Biodiversity Exploratory' research network). By standardization of traits and diversity measures, use of null models and linear mixed models we confirmed (i) strong links between functional community composition and plant diversity, (ii) that traits are closely related to land-use intensity, and (iii) that functional indicators are equally, or even more sensitive to land-use intensity than traditional diversity indices. The deduced trait set consisted of 5 traits, i.e., specific leaf area (SLA), leaf dry matter content (LDMC), seed release height, leaf distribution, and onset of flowering. These database derived traits enable the early detection of changes in community structure indicative for future diversity loss. As an addition to current monitoring measures they allow to better link environmental drivers to processes controlling community dynamics.
Small scale distribution of insect root herbivores may promote plant species diversity by creating patches of different herbivore pressure. However, determinants of small scale distribution of insect root herbivores, and impact of land use intensity on their small scale distribution are largely unknown. We sampled insect root herbivores and measured vegetation parameters and soil water content along transects in grasslands of different management intensity in three regions in Germany. We calculated community-weighted mean plant traits to test whether the functional plant community composition determines the small scale distribution of insect root herbivores. To analyze spatial patterns in plant species and trait composition and insect root herbivore abundance we computed Mantel correlograms. Insect root herbivores mainly comprised click beetle (Coleoptera, Elateridae) larvae (43%) in the investigated grasslands. Total insect root herbivore numbers were positively related to community-weighted mean traits indicating high plant growth rates and biomass (specific leaf area, reproductive-and vegetative plant height), and negatively related to plant traits indicating poor tissue quality (leaf C/N ratio). Generalist Elaterid larvae, when analyzed independently, were also positively related to high plant growth rates and furthermore to root dry mass, but were not related to tissue quality. Insect root herbivore numbers were not related to plant cover, plant species richness and soil water content. Plant species composition and to a lesser extent plant trait composition displayed spatial autocorrelation, which was not influenced by land use intensity. Insect root herbivore abundance was not spatially autocorrelated. We conclude that in semi-natural grasslands with a high share of generalist insect root herbivores, insect root herbivores affiliate with large, fast growing plants, presumably because of availability of high quantities of food. Affiliation of insect root herbivores with large, fast growing plants may counteract dominance of those species, thus promoting plant diversity.
While several empirical and theoretical studies have clearly shown the negative effects of climate or landscape changes on population and species survival only few of them addressed combined and correlated consequences of these key environmental drivers. This also includes positive landscape changes such as active habitat management and restoration to buffer the negative effects of deteriorating climatic conditions. In this study, we apply a conceptual spatial modelling approach based on functional types to explore the effects of both positive and negative correlations between changes in habitat and climate conditions on the survival of spatially structured populations. We test the effect of different climate and landscape change scenarios on four different functional types that represent a broad spectrum of species characterised by their landscape level carrying capacity, the local population turnover rates at the patch level (K-strategies vs. r-strategies) and dispersal characterstics. As expected, simulation results show that correlated landscape and climatic changes can accelerate (in case of habitat loss or degradation) or slow down (in case of habitat gain or improvement) regional species extinction. However, the strength of the combined changes depends on local turnover at the patch level, the overall landscape capacity of the species, and its specific dispersal characteristics. Under all scenarios of correlated changes in habitat and climate conditions we found the highest sensitivity for functional types representing species with a low landscape capacity but a high population growth rate and a strong density regulation causing a high turnover at the local patch level.
The relative importance of habitat loss or habitat degradation, in combination with climate deterioration, differed among the functional types. However, an increase in regional capacity revealed a similar response pattern: For all types, habitat improvement led to higher survival times than habitat gain, i.e. the establishment of new habitat patches. This suggests that improving local habitat quality at a regional scale is a more promising conservation strategy under climate change than implementing new habitat patches. This conceptual modelling study provides a general framework to better understand and support the management of populations prone to complex environmental changes.
QuestionThe empirical evidence of root herbivory effects on plant community composition and co-existence is contradictory. This originates from difficulties connected to below-ground research and confinement of experimental studies to a small range of environmental conditions. Here we suggest coupling experimental data with an individual-based model to overcome the limitations inherent in either approach. To demonstrate this, we investigated the consequences of root herbivory, as experimentally observed on individual plants, on plant competition and co-existence in a population and community context under different root herbivory intensities (RHI), fluctuating and constant root herbivore activity and grazing along a resource gradient. LocationBerlin, Germany, glasshouse; Potsdam, Germany, high performance cluster computer. MethodsThe well-established community model IBC-Grass was adapted to allow for a flexible species parameterization and to include annual species. Experimentally observed root herbivory effects on performance of eight common grassland plant species were incorporated into the model by altering plant growth rates. We then determined root herbivore effects on plant populations, competitive hierarchy and consequences for co-existence and community diversity. ResultsRoot herbivory reduced individual biomass, but temporal fluctuation allowed for compensation of herbivore effects. Reducing resource availability strongly shifted competitive hierarchies, with, however, more similar hierarchies along the gradient under root herbivory, pointing to reduced ecological species differences. Consequently, negative effects on co-existence and diversity prevailed, with the exception of a few positive effects on co-existence of selected species pairs. Temporal fluctuation alleviated but did not remove negative root herbivore effects, despite of the stronger influence of intra- compared to interspecific competition. Grazing in general augmented co-existence. Most interestingly, grazing interacted with RHI and resource availability by promoting positive effects of root herbivory. ConclusionsThrough integrating experimental data on the scale of individual plants with a simulation model we verified that root herbivory could affect plant competition with consequences for species co-existence. Our approach demonstrates the benefit that accrues when empirical and modelling approaches are brought more closely together, and that gathering data on distinct processes and under specific conditions, combined with appropriate models, can be used to answer challenging research questions in a more general way.
To assess the ecological and economic implications of the redistributive land reform in semi-arid Namibia, we investigated to what extent land reform beneficiaries adjust herd size and herd composition according to environmental (rainfall, vegetation) and economic variables (herd size, financial assets, running costs). We performed model-based role-plays with Namibian land reform beneficiaries, simulating 10 years of rangeland management.
Our study revealed that the farmers surveyed mainly manage their herds according to their economic situation (herd size and account balance) but do not take environmental variability (rainfall and vegetation) into account. Further, our results indicate that, due to financial pressure, farmers are not able to apply their desired management strategies, and that owners of small farms face a higher risk of economic failure. However, farmers apply rather conservative and constant stocking rates and will thus, given the current economic limitations, likely not contribute to semi-arid savanna degradation.
We conclude that land reform beneficiaries need support to be able to apply straightforward and efficient management strategies. This could be achieved by facilitating cooperation between small farming businesses and by supporting initial investment in productive cattle herds at the time of redistribution of the land.
The abandonment of military areas leads to succession processes affecting valuable open-land habitats and is considered to be a major threat for European butterflies. We assessed the ability of hyper spectral remote sensing data to spatially predict the occurrence of one of the most endangered butterfly species (Hipparchia statilinus) in Brandenburg (Germany) on the basis of habitat characteristics at a former military training area. Presence-absence data were sampled on a total area of 36 km(2), and N = 65 adult individuals of Hipparchia statilinus could be detected. The floristic composition within the study area was modeled in a three-dimensional ordination space. Occurrence probabilities for the target species were predicted as niches between ordinated floristic gradients by using Regression Kriging of Indicators. Habitat variance could be explained by up to 81 % with spectral variables at a spatial resolution of 2 x 2 m by transferring PLSR models to imagery. Ordinated ecological niche of Hipparchia statilinus was tested against environmental predictor variables. N = 6 variables could be detected to be significantly correlated with habitat preferences of Hipparchia statilinus. They show that Hipparchia statilinus can serve as a valuable indicator for the evaluation of the conservation status of Natura 2000 habitat type 2330 (inland dunes with open Corynephorus and Agrostis grasslands) protected by the Habitat Directive (Council Directive 92/43/EEC). The authors of this approach, conducted in August 2013 at Doberitzer Heide Germany, aim to increase the value of remote sensing as an important tool for questions of biodiversity research and conservation.
The response of species diversity to dispersal capability is inherently scale-dependent: increasing dispersal capability is expected to increase diversity at the local scale, while decreasing diversity at the metacommunity scale. However, these expectations are based on model formulations that neglect dispersal limitation and species segregation at the local scale. We developed a unifying framework of dispersaldiversity relationships and tested the generality of these expectations. For this purpose we used a spatially-explicit neutral model with various combinations of survey area (local scale) and landscape size (metacommunity scale). Simulations were conducted using landscapes of finite and of conceptually infinite size. We analyzed the scale-dependence of dispersal-diversity relationships for exponentially-bounded versus fat-tailed dispersal kernels, several levels of speciation rate and contrasting assumptions on recruitment at short dispersal distances. We found that the ratio of survey area to landscape size is a major determinant of dispersaldiversity relationships. With increasing survey-to-landscape area ratio the dispersaldiversity relationship switches from monotonically increasing through a U-shaped pattern (with a local minimum) to a monotonically decreasing pattern. Therefore, we provide a continuous set of dispersaldiversity relationships, which contains the response shapes reported previously as extreme cases. We suggest the mean dispersal distance with the minimum of species diversity (minimizing dispersal distance) for a certain scenario as a key characteristic of dispersaldiversity relationships. We show that not only increasing mean dispersal distances, but also increasing variances of dispersal can enhance diversity at the local scale, given a diverse species pool at the metacommunity scale. In conclusion, the response of diversity to variations of dispersal capability at spatial scales of interest, e.g. conservation areas, can differ more widely than expected previously. Therefore, land use and conservation activities, which manipulate dispersal capability, need to consider the landscape context and potential species pools carefully.
Arctic and alpine treelines worldwide differ in their reactions to climate change. A northward advance of or densification within the treeline ecotone will likely influence climate-vegetation feedback mechanisms. In our study, which was conducted in the Taimyr Depression in the North Siberian Lowlands, w present a combined field-and model-based approach helping us to better understand the population processes involved in the responses of the whole treeline ecotone, spanning from closed forest to single-tree tundra, to climate warming. Using information on stand structure, tree age, and seed quality and quantity from seven sites, we investigate effects of intra-specific competition and seed availability on the specific impact of recent climate warming on larch stands. Field data show that tree density is highest in the forest-tundra, and average tree size decreases from closed forest to single-tree tundra. Age-structure analyses indicate that the trees in the closed forest and forest-tundra have been present for at least similar to 240 yr. At all sites except the most southerly ones, past establishment is positively correlated with regional temperature increase. In the single-tree tundra, however, a change in growth form from krummholz to erect trees, beginning similar to 130 yr ago, rather than establishment date has been recorded. Seed mass decreases from south to north, while seed quantity increases. Simulations with LAVESI (Larix Vegetation Simulator) further suggest that relative density changes strongly in response to a warming signal in the forest-tundra while intra-specific competition limits densification in the closed forest and seed limitation hinders densification in the single-tree tundra. We find striking differences in strength and timing of responses to recent climate warming. While forest-tundra stands recently densified, recruitment is almost non-existent at the southern and northern end of the ecotone due to autecological processes. Palaeo-treelines may therefore be inappropriate to infer past temperature changes at a fine scale. Moreover, a lagged treeline response to past warming will, via feedback mechanisms, influence climate change in the future.
Recent theoretical studies have shown contrasting effects of temporal correlation of environmental fluctuations ( red noise) on the risk of population extinction. It is still debated whether and under which conditions red noise increases or decreases extinction risk compared with uncorrelated ( white) noise. Here, we explain the opposing effects by introducing two features of red noise time series. On the one hand, positive autocorrelation increases the probability of series of poor environmental conditions, implying increasing extinction risk. On the other hand, for a given time period, the probability of at least one extremely bad year ("catastrophe") is reduced compared with white noise, implying decreasing extinction risk. Which of these two features determines extinction risk depends on the strength of environmental fluctuations and the sensitivity of population dynamics to these fluctuations. If extreme ( catastrophic) events can occur ( strong noise) or sensitivity is high ( overcompensatory density dependence), then temporal correlation decreases extinction risk; otherwise, it increases it. Thus, our results provide a simple explanation for the contrasting previous findings and are a crucial step toward a general understanding of the effect of noise color on extinction risk
The interaction between ecological and hydrological processes is particularly important in arid and semi-arid regions. Often the interaction between these processes is not completely understood and they are studied separately. We developed a grid-based computer model simulating the dynamics of the four most common vegetation types (perennial grass, annuals, dwarf shrubs and shrubs) and related hydrological processes in the region studied. Eco-hydrological interactions gain importance in rangelands with increasing slope, where vegetation cover obstructs run-off and decreases evaporation from the soil. Overgrazing can influence these positive feedback mechanisms. In this study, we first show that model predictions of cover and productivity of the vegetation types are realistic by comparing them with estimates obtained from field surveys. Then, we apply a realistic range in slope angle combined with two land use regimes (light versus heavy grazing intensity). Our simulation results reveal that hydrological processes and associated productivity are strongly affected by slope, whereas the magnitude of this impact depends on overgrazing. Under low stocking rates, undisturbed vegetation is maintained and run-off and evaporation remain low on flat plains and gentle slope. On steep slopes, run-off and evaporation become larger, while water retention potential decreases, which leads to reduced productivity. Overgrazing, however, reduces vegetation cover and biomass production and the landscape"s ability to conserve water decreases even on flat plains and gentle slopes. Generally, the abundance of perennial grasses and shrubs decreases with increasing slope and grazing. Dominance is shifted towards shrubs and annuals. As a management recommendation we suggest that different vegetation growth forms should not only be regarded as forage producers but also as regulators of ecosystem functioning. Particularly on sloping range lands, a high percentage of cover by perennial vegetation insures that water is retained in the system.