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Elektronisch veröffentlicht auf dem Publikationsserver der Universität Potsdam: http://opus.kobv. de/ubp/volltexte/2008/1640/ urn:nbn:de:kobv:517-opus-16402 [http://nbn-resolving.de/urn:nbn:de:kobv:517-opus16402] SummaryAs land-cover conversion continues to expand into ever more remote areas in the humid tropics, montane rainforests are increasingly threatened. In addition to the loss of biodiversity, land-use change potentially deteriorates regional water cycles, which may have undesirable effects for local populations such as decreased water supply during dry seasons, enhanced flooding in the rainy season, or deterioration of drinking water quality.Montane rainforests in the south Ecuadorian Andes are not only subject to man-made disturbances but also to naturally occurring landslides. I was interested in the impact of this ecosystem dynamics on a key parameter of the hydrologic cycle, the soil saturated hydraulic conductivity (synonym: permeability; Ks from here on), because it is a sensitive indicator for soil disturbances. Depending on the rainfall regime, the potential disturbance-induced decrease of Ks may become relevant for regional watersheds.My general objective was to quantify the effects of the regional natural and human disturbances on the saturated hydraulic conductivity and to describe the resulting spatialtemporal patterns. The main hypotheses were: 1) disturbances cause an apparent displacement of the less permeable soil layer towards the surface, either due to a loss of the permeable surface soil after land-sliding, or as a consequence of the surface soil compaction under cattle pastures; 2) 'recovery' from disturbance, either because of landslide re-vegetation or because of secondary succession after pasture abandonment, involves an apparent displacement of the less permeable layer back towards the original depth an 3) disturbances cause a simplification of the Ks spatial structure, i.e. the spatially dependent random variation diminishes; the subsequent recovery entails the re-establishment of the original structure.In my first study, I developed a synthesis of recent geostatistical research regarding its applicability to soil hydraulic data, including exploratory data analysis and variogram estimation techniques; I subsequently evaluated the results in terms of spatial prediction uncertainty. Concerning the exploratory data analysis, my main results were: 1) Gaussian uniand bivariate distributions of the log-transformed data; 2) the existence of significant local trends; 3) no need for robust estimation; 4) no anisotropic variation. I found partly considerable differences in covariance parameters resulting from different variogram estimation techniques, which, in the framework of spatial prediction, were mainly reflected in the spatial connectivity of the Ks-field. Ignoring the trend component and an arbitrary use of robust estimators, however, would have the most severe consequences in this respect.Regarding variogram modeling, I encouraged restricted maximum likelihood estimation becau...

[1] The investigation of throughfall patterns has received considerable interest over the last decades. And yet, the geographical bias of pertinent previous studies and their methodologies and approaches to data analysis cast a doubt on the general validity of claims regarding spatial and temporal patterns of throughfall. We employed 220 collectors in a 1-ha plot of semideciduous tropical rain forest in Panama and sampled throughfall during a period of 14 months. Our analysis of spatial patterns is based on 60 data sets, whereas the temporal analysis comprises 91 events. Both data sets show skewed frequency distributions. When skewness arises from large outliers, the classical, nonrobust variogram estimator overestimates the sill variance and, in some cases, even induces spurious autocorrelation structures. In these situations, robust variogram estimation techniques offer a solution. Throughfall in our plot typically displayed no or only weak spatial autocorrelations. In contrast, temporal correlations were strong, that is, wet and dry locations persisted over consecutive wet seasons. Interestingly, seasonality and hence deciduousness had no influence on spatial and temporal patterns. We argue that if throughfall patterns are to have any explanatory power with respect to patterns of near-surface processes, data analytical artifacts must be ruled out lest spurious correlation be confounded with causality; furthermore, temporal stability over the domain of interest is essential.

The use of biostimulants with plant growth-promoting properties, but without significant input of nutrients, is discussed as a strategy to increase stress resistance and nutrient use efficiency of crops. However, limited reproducibility under real production conditions remains a major challenge. The use of combination products based on microbial and non-microbial biostimulants or microbial consortia, with the aim to exploit complementary or synergistic interactions and increase the flexibility of responses under different environmental conditions, is discussed as a potential strategy to overcome this problem. This study aimed at comparing the efficiency of selected microbial single-strain inoculants with proven plant-growth promoting potential versus consortium products under real production conditions in large-scale tomato cultivation systems, exposed to different environmental challenges. In a protected greenhouse production system at Timisoara, Romania, with composted cow manure, guano, hair-, and feather-meals as major fertilizers, different fungal and bacterial single-strain inoculants, as well as microbial consortium products, showed very similar beneficial responses. Nursery performance, fruit setting, fruit size distribution, seasonal yield share, and cumulative yield (39–84% as compared to the control) were significantly improved over two growing periods. By contrast, superior performance of the microbial consortia products (MCPs) was recorded under more challenging environmental conditions in an open-field drip-fertigated tomato production system in the Negev desert, Israel with mineral fertilization on a high pH (7.9), low fertility, and sandy soil. This was reflected by improved phosphate (P) acquisition, a stimulation of vegetative shoot biomass production and increased final fruit yield under conditions of limited P supply. Moreover, MCP inoculation was associated with selective changes of the rhizosphere-bacterial community structure particularly with respect to Sphingobacteriia and Flavobacteria, reported as salinity indicators and drought stress protectants. Phosphate limitation reduced the diversity of bacterial populations at the root surface (rhizoplane) and this effect was reverted by MCP inoculation, reflecting the improved P status of the plants. The results support the hypothesis that the use of microbial consortia can increase the efficiency and reproducibility of BS-assisted strategies for crop production, particularly under challenging environmental conditions.

Soils in various places of the Panama Canal Watershed feature a low saturated hydraulic conductivity (K s ) at shallow depth, which promotes overland-flow generation and associated flashy catchment responses. In undisturbed forests of these areas, overland flow is concentrated in flow lines that extend the channel network and provide hydrological connectivity between hillslopes and streams. To understand the dynamics of overland-flow connectivity, as well as the impact of connectivity on catchment response, we studied an undisturbed headwater catchment by monitoring overland-flow occurrence in all flow lines and discharge, suspended sediment, and total phosphorus at the catchment outlet. We find that connectivity is strongly influenced by seasonal variation in antecedent wetness and can develop even under light rainfall conditions. Connectivity increased rapidly as rainfall frequency increased, eventually leading to full connectivity and surficial drainage of entire hillslopes. Connectivity was nonlinearly related to catchment response. However, additional information on factors such as overland-flow volume would be required to constrain relationships between connectivity, stormflow, and the export of suspended sediment and phosphorus. The effort to monitor those factors would be substantial, so we advocate applying the established links between rain event characteristics, drainage network expansion by flow lines, and catchment response for predictive modeling and catchment classification in forests of the Panama Canal Watershed and in similar regions elsewhere.

[1] What is the most appropriate sampling scheme to estimate event-based average throughfall? A satisfactory answer to this seemingly simple question has yet to be found, a failure which we attribute to previous efforts' dependence on empirical studies. Here we try to answer this question by simulating stochastic throughfall fields based on parameters for statistical models of large monitoring data sets. We subsequently sampled these fields with different sampling designs and variable sample supports. We evaluated the performance of a particular sampling scheme with respect to the uncertainty of possible estimated means of throughfall volumes. Even for a relative error limit of 20%, an impractically large number of small, funnel-type collectors would be required to estimate mean throughfall, particularly for small events. While stratification of the target area is not superior to simple random sampling, cluster random sampling involves the risk of being less efficient. A larger sample support, e.g., the use of trough-type collectors, considerably reduces the necessary sample sizes and eliminates the sensitivity of the mean to outliers. Since the gain in time associated with the manual handling of troughs versus funnels depends on the local precipitation regime, the employment of automatically recording clusters of long troughs emerges as the most promising sampling scheme. Even so, a relative error of less than 5% appears out of reach for throughfall under heterogeneous canopies. We therefore suspect a considerable uncertainty of input parameters for interception models derived from measured throughfall, in particular, for those requiring data of small throughfall events.

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