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Investigations of spatial patterns in forest tree species composition are essential in the understanding of landscape dynamics, especially in areas of land-use change. The specific environmental factors controlling the present patterns, however, vary with the scale of observation. In this study we estimated abundance of adult trees and tree regeneration in a Southern Alpine valley in Ticino, Switzerland. We hypothesized that, at the present scale, spatial pattern of post-cultural tree species does not primarily depend on topographic features but responds instead to small- scale variation in historical land use. We used multivariate regression trees to relate species abundances to environmental variables. Species matrices were comprised of single tree species abundance as well as species groups. Groups were formed according to common ecological species requirements with respect to shade tolerance, soil moisture and soil nutrients. Though species variance could only be partially explained, a clear ranking in the relative importance of environmental variables emerged. Tree basal area of formerly cultivated Castanea sativa (Mill.) was the most important factor accounting for up to 50% of species' variation. Influence of topographic attributes was minor, restricted to profile curvature, and partly contradictory in response. Our results suggest the importance of biotic factors and soil properties for small-scale variation in tree species composition and need for further investigations in the study area on the ecological requirements of tree species in the early growing stage.
Prolonged dry periods, and increasingly the generation of smoke and dust in partially-deforested regions, can influence the chemistry of rainfall and throughfall in moist tropical forests. We investigated rainfall and throughfall chemistry in a palm-rich open tropical rainforest in the southwestern Brazilian Amazon state of Rondonia, where precipitation averages 2300 mm year(-1) with a marked seasonal pattern, and where the fragmentation of remaining forest is severe. Covering the transition from dry to wet season (TDWS) and the wet season (WS) of 2004-2005, we sampled 42 rainfall events on event basis as well as 35 events on a within-event basis, and measured concentrations of DOC, Na+, K+, Ca2+, Mg2+, NH4+ , Cl-, SO42- , NO3- and pH in rainfall and throughfall. We found strong evidence of both seasonal and within-event solute rainfall concentration dynamics. Seasonal volume-weighted mean (VWMS) concentrations in rainfall of DOC, K+, Ca2+, Mg2+, NH4+ , SO42- and NO3- were significantly higher in the TDWS than the WS, while VWMS concentrations in throughfall were significantly higher for all solutes except DOC. Patterns were generally similar within rain events, with solute concentrations declining sharply during the first few millimeters of rainfall. Rainfall and throughfall chemistry dynamics appeared to be strongly influenced by forest and pasture burning and a regional atmosphere rich in aerosols at the end of the dry season. These seasonal and within-event patterns of rainfall and throughfall chemistry were stronger than those recorded in central Amazonia, where the dry season is less pronounced and where regional deforestation is less severe. Fragmentation and fire in Rondonia now appear to be altering the patterns in which solutes are delivered to remaining moist tropical forests.
[1] Observations of hydrological response often exhibit considerable scatter that is difficult to interpret. In this paper, we examine runoff production of 53 sprinkling experiments on the water-repellent soils in the southern Alps of Switzerland; simulated plot scale tracer transport in the macroporous soils at the Weiherbach site, Germany; and runoff generation data from the 2.3-km(2) Tannhausen catchment, Germany, that has cracking soils. The response at the three sites is highly dependent on the initial soil moisture state as a result of the threshold dynamics of the systems. A simple statistical model of threshold behavior is proposed to help interpret the scatter in the observations. Specifically, the model portrays how the inherent macrostate uncertainty of initial soil moisture translates into the scatter of the observed system response. The statistical model is then used to explore the asymptotic pattern of predictability when increasing the number of observations, which is normally not possible in a field study. Although the physical and chemical mechanisms of the processes at the three sites are different, the predictability patterns are remarkably similar. Predictability is smallest when the system state is close to the threshold and increases as the system state moves away from it. There is inherent uncertainty in the response data that is not measurement error but is related to the observability of the initial conditions.