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Soil seed banks near rubbing trees indicate dispersal of plant species into forests by wild boar
(2006)
Current knowledge about processes that generate long-distance dispersal of plants is still limited despite its importance for persistence of populations and colonization of new potential habitats. Today wild large mammals are presumed to be important vectors for long-distance transport of diaspores within and between European temperate forest patches, and in particular wild boars recently came into focus. Here we use a specific habit of wild boar, i.e. wallowing in mud and subsequent rubbing against trees, to evaluate epizoic dispersal of vascular plant diaspores. We present soil seed bank data from 27 rubbing trees versus 27 control trees from seven forest areas in Germany. The mean number of viable seeds and the plant species number were higher in soil samples near rubbing trees compared with control trees. Ten of the 20 most frequent species were more frequent, and many species exclusively appeared in the soil samples near rubbing trees. The large number of plant species and seeds – approximated > 1000 per tree – in the soils near rubbing trees is difficult to explain unless the majority were dispersed by wild boar. Hooked and bristly diaspores, i.e. those adapted to epizoochory, were more frequent, above that many species with unspecialised diaspores occurred exclusively near rubbing trees. Different to plant species closely tied to forest species which occur both in forest and open vegetation, and non-forest species were more frequent near rubbing trees compared with controls. These findings are consistent with previous studies on diaspore loads in the coats and hooves of shot wild boars. However, our method allows to identify the transport of diaspores from the open landscape into forest stands where they might especially emerge after disturbance, and a clustered distribution of epizoochorically dispersed seeds. Moreover, accumulation of seeds of wetness indicators near rubbing trees demonstrates directed dispersal of plant species inhabiting wet places between remote wallows.
Global Circulation Models of climate predict not only a change of annual precipitation amounts but also a shift in the daily distribution. To improve the understanding of the importance of daily rain pattern for annual plant communities, which represent a large portion of semi-natural vegetation in the Middle East, I used a detailed, spatially explicit model. The model explicitly considers water storage in the soil and has been parameterized and validated with data collected in field experiments in Israel and data from the literature. I manipulated daily rainfall variability by increasing the mean daily rain intensity on rainy days (MDI, rain volume/day) and decreasing intervals between rainy days while keeping the mean annual amount constant. In factorial combination, I also increased mean annual precipitation (MAP). I considered five climatic regions characterized by 100, 300, 450, 600, and 800 mm MAP. Increasing MDI decreased establishment when MAP was >250 mm but increased establishment at more arid sites. The negative effect of increasing MDI was compensated by increasing mortality with increasing MDI in dry and typical Mediterranean regions (c. 360–720 mm MAP). These effects were strongly tied to water availability in upper and lower soil layers and modified by competition among seedlings and adults. Increasing MAP generally increased water availability, establishment, and density. The order of magnitudes of MDI and MAP effects overlapped partially so that their combined effect is important for projections of climate change effects on annual vegetation. The effect size of MAP and MDI followed a sigmoid curve along the MAP gradient indicating that the semi-arid region (≈300 mm MAP) is the most sensitive to precipitation change with regard to annual communitie
This contribution describes a generator of stochastic time series of daily precipitation for the interior of Israel from c. 90 to 900 mm mean annual precipitation (MAP) as a tool for studies of daily rain variability. The probability of rainfall on a given day of the year is described by a regular Gaussian peak curve function. The amount of rain is drawn randomly from an exponential distribution whose mean is the daily mean rain amount (averaged across years for each day of the year) described by a flattened Gaussian peak curve. Parameters for the curves have been calculated from monthly aggregated, long-term rain records from seven meteorological stations. Parameters for arbitrary points on the MAP gradient are calculated from a regression equation with MAP as the only independent variable. The simple structure of the generator allows it to produce time series with daily rain patterns that are projected under climate change scenarios and simultaneously control MAP. Increasing within-year variability of daily precipitation amounts also increases among-year variability of MAP as predicted by global circulation models. Thus, the time series incorporate important characteristics for climate change research and represent a flexible tool for simulations of daily vegetation or surface hydrology dynamics.
Germination rates and germination fractions of seeds can be predicted well by the hydrothermal time (HTT) model. Its four parameters hydrothermal time, minimum soil temperature, minimum soil moisture, and variation of minimum soil moisture, however, must be determined by lengthy germination experiments at combinations of several levels of soil temperature and moisture. For some applications of the HTT model it is more important to have approximate estimates for many species rather than exact values for only a few species. We suggest that minimum temperature and variation of minimum moisture can be estimated from literature data and expert knowledge. This allows to derive hydrothermal time and minimum moisture from existing data from germination experiments with one level of temperature and moisture. We applied our approach to a germination experiment comparing germination fractions of wild annual species along an aridity gradient in Israel. Using this simplified approach we estimated hydrothermal time and minimum moisture of 36 species. Comparison with exact data for three species shows that our method is a simple but effective method for obtaining parameters for the HTT model. Hydrothermal time and minimum moisture supposedly indicate climate related germination strategies. We tested whether these two parameters varied with the climate at the site where the seeds had been collected. We found no consistent variation with climate across species, suggesting that variation is more strongly controlled by site-specific factors.
In a recent contribution in Nature (vol. 442, pp. 555-558) Austin & Vivanco showed that sunlight is the dominant factor for decomposition of grass litter in a semi-arid grassland in Argentine. The quantification of this effect was portrayed as a novel finding. I put this result in the context of three other publications from as early as 1980 that quantified photodegradation. My synopsis shows that photodegradation is an important process in semi-arid grasslands in South America, North America and eastern Europe.
In semi-arid savannas, unsustainable land use can lead to degradation of entire landscapes, e.g. in the form of shrub encroachment. This leads to habitat loss and is assumed to reduce species diversity. In BIOTA phase 1, we investigated the effects of land use on population dynamics on farm scale. In phase 2 we scale up to consider the whole regional landscape consisting of a diverse mosaic of farms with different historic and present land use intensities. This mosaic creates a heterogeneous, dynamic pattern of structural diversity at a large spatial scale. Understanding how the region-wide dynamic land use pattern affects the abundance of animal and plant species requires the integration of processes on large as well as on small spatial scales. In our multidisciplinary approach, we integrate information from remote sensing, genetic and ecological field studies as well as small scale process models in a dynamic region-wide simulation tool. <hr> Interdisziplinäres Zentrum für Musterdynamik und Angewandte Fernerkundung Workshop vom 9. - 10. Februar 2006.
Decisions for the conservation of biodiversity and sustainable management of natural resources are typically related to large scales, i.e. the landscape level. However, understanding and predicting the effects of land use and climate change on scales relevant for decision-making requires to include both, large scale vegetation dynamics and small scale processes, such as soil-plant interactions. Integrating the results of multiple BIOTA subprojects enabled us to include necessary data of soil science, botany, socio-economics and remote sensing into a high resolution, process-based and spatially-explicit model. Using an example from a sustainably-used research farm and a communally used and degraded farming area in semiarid southern Namibia we show the power of simulation models as a tool to integrate processes across disciplines and scales.