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Tree size and herbivory determine below-canopy grass quality and species composition in savannahs
(2009)
Large single-standing trees are rapidly declining in savannahs, ecosystems supporting a high diversity of large herbivorous mammals. Savannah trees are important as they support both a unique flora and fauna. The herbaceous layer in particular responds to the structural and functional properties of a tree. As shrubland expands stem thickening occurs and large trees are replaced by smaller trees. Here we examine whether small trees are as effective in providing advantages for grasses growing beneath their crowns as large trees are. The role of herbivory in this positive tree- grass interaction is also investigated. We assessed soil and grass nutrient content, structural properties, and herbaceous species composition beneath trees of three size classes and under two grazing regimes in a South African savannah. We found that grass leaf content (N and P) beneath the crowns of particularly large (ca. 3.5 m) and very large trees (ca. 9 m) was as much as 40% greater than the same grass species not growing under a tree canopy, whereas nutrient contents of grasses did not differ beneath small trees (< 2.3 m). Moderate herbivory enhanced these effects slightly. Grass species composition differed beneath and beyond the tree canopy but not between tree size classes. As large trees significantly improve the grass nutrient quality for grazers in contrast to smaller trees, the decline of the former should be halted. The presence of trees further increases grass species diversity and patchiness by favouring shade- tolerant species. Both grazing wildlife and livestock will benefit from the presence of large trees because of their structural and functional importance for savannahs.
Movement ecology aims to provide common terminology and an integrative framework of movement research across all groups of organisms. Yet such work has focused on unitary organisms so far, and thus the important group of filamentous fungi has not been considered in this context. With the exception of spore dispersal, movement in filamentous fungi has not been integrated into the movement ecology field. At the same time, the field of fungal ecology has been advancing research on topics like informed growth, mycelial translocations, or fungal highways using its own terminology and frameworks, overlooking the theoretical developments within movement ecology. We provide a conceptual and terminological framework for interdisciplinary collaboration between these two disciplines, and show how both can benefit from closer links: We show how placing the knowledge from fungal biology and ecology into the framework of movement ecology can inspire both theoretical and empirical developments, eventually leading towards a better understanding of fungal ecology and community assembly. Conversely, by a greater focus on movement specificities of filamentous fungi, movement ecology stands to benefit from the challenge to evolve its concepts and terminology towards even greater universality. We show how our concept can be applied for other modular organisms (such as clonal plants and slime molds), and how this can lead towards comparative studies with the relationship between organismal movement and ecosystems in the focus.
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
Moving in the Anthropocene
(2018)
Animal movement is fundamental for ecosystem functioning and species survival, yet the effects of the anthropogenic footprint on animal movements have not been estimated across species. Using a unique GPS-tracking database of 803 individuals across 57 species, we found that movements of mammals in areas with a comparatively high human footprint were on average one-half to one-third the extent of their movements in areas with a low human footprint. We attribute this reduction to behavioral changes of individual animals and to the exclusion of species with long-range movements from areas with higher human impact. Global loss of vagility alters a key ecological trait of animals that affects not only population persistence but also ecosystem processes such as predator-prey interactions, nutrient cycling, and disease transmission.
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.
GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (releves) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001;... 1,000 m(2)) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetationplot databases, such as the European Vegetation Archive (EVA) and the global database " sPlot". Its main aim is to facilitate studies on the scale-and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board.
In European dry grasslands land-use changes affect plant species performance and frequency. Potential driving forces are eutrophication and habitat fragmentation. The importance of these factors is presumably scale dependent. We used a functional trait approach to detect processes that influence species frequency and endangerment on different spatial scales. We tested for associations between functional traits and (1) frequency and (2) degree of endangerment on local, regional and national scales. We focussed on five selected traits that describe the life-history of plant species and that are related to competition, dispersal ability and habitat specificity. Trait data on plant height, SLA, plant coverage, peak of flowering and diaspore mass were measured for 28 perennials from common to rare and endangered to non-endangered on 59 dry grassland sites in north-eastern Germany. Multiple regression models revealed that species frequency is positively and species endangerment negatively related to plant height, plant coverage and SLA on more than one spatial scale. On the local scale, diaspore mass has a negative effect on species frequency. More frequent and less endangered species show a later peak of flowering on nationwide and regional scales. We concluded that competition traits are more important on larger scales, whereas dispersal traits are more important for species frequency on the smaller scale. On national and regional scales, eutrophication and habitat loss may be the main drivers of species threat, whereas on the local scale fragmentation plays a crucial role for the performance of dry grassland species.
The cover of large trees in African savannahs is rapidly declining, mainly due to human land-use practices. Trees improve grass nutrient quality and contribute to species and structural diversity of savannah vegetation. However, the response of herbivores to trees as habitat features is unknown We quantified the habitat use of wild and domestic ungulates in two eastern and southern African savannahs. We assessed grazing intensities and quantified dung depositions beneath and around canopies of different sized trees. Grasses were eaten and dung was deposited twice as frequently beneath large (ca. 5 m in height) and very large trees (7-10 m) than in open grasslands. Small trees (<2.5 m) did not show this trend. Grazing intensity and dung deposition decreased with distance away from trees at both study sites. These results suggest that large trees represent essential habitat features for domestic and wild herbivores. Increased dung depositions beneath large trees may further promote the maintenance of a patchy nutrient distribution in savannahs. Small trees cannot provide the same structural and functional advantages as large trees do. We recommend that land-use practices be promoted which conserve large single-standing trees to benefit the flora and fauna of African savannahs.
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.
Home range estimation is routine practice in ecological research. While advances in animal tracking technology have increased our capacity to collect data to support home range analysis, these same advances have also resulted in increasingly autocorrelated data. Consequently, the question of which home range estimator to use on modern, highly autocorrelated tracking data remains open. This question is particularly relevant given that most estimators assume independently sampled data. Here, we provide a comprehensive evaluation of the effects of autocorrelation on home range estimation. We base our study on an extensive data set of GPS locations from 369 individuals representing 27 species distributed across five continents. We first assemble a broad array of home range estimators, including Kernel Density Estimation (KDE) with four bandwidth optimizers (Gaussian reference function, autocorrelated‐Gaussian reference function [AKDE], Silverman's rule of thumb, and least squares cross‐validation), Minimum Convex Polygon, and Local Convex Hull methods. Notably, all of these estimators except AKDE assume independent and identically distributed (IID) data. We then employ half‐sample cross‐validation to objectively quantify estimator performance, and the recently introduced effective sample size for home range area estimation ( N̂ area
) to quantify the information content of each data set. We found that AKDE 95% area estimates were larger than conventional IID‐based estimates by a mean factor of 2. The median number of cross‐validated locations included in the hold‐out sets by AKDE 95% (or 50%) estimates was 95.3% (or 50.1%), confirming the larger AKDE ranges were appropriately selective at the specified quantile. Conversely, conventional estimates exhibited negative bias that increased with decreasing N̂ area. To contextualize our empirical results, we performed a detailed simulation study to tease apart how sampling frequency, sampling duration, and the focal animal's movement conspire to affect range estimates. Paralleling our empirical results, the simulation study demonstrated that AKDE was generally more accurate than conventional methods, particularly for small N̂ area. While 72% of the 369 empirical data sets had >1,000 total observations, only 4% had an N̂ area >1,000, where 30% had an N̂ area <30. In this frequently encountered scenario of small N̂ area, AKDE was the only estimator capable of producing an accurate home range estimate on autocorrelated data.