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Secondary forests are gaining increased importance in tropical landscapes and have recently been reported to act as potential belowground carbon sinks. While economic interest in the management of secondary forests to mitigate carbon emissions is rising, the dynamics of soil carbon stocks under these ecosystems remain poorly understood. Recent studies report conflicting results concerning soil carbon trends as well as multiple confounding factors (e.g. soil type, topography and land-use history) affecting these trends. In this study, organic carbon stocks were measured in the mineral soil up to 20 cm depth of at 24 active pastures, 5-8-year-old, and 12-15-year-old secondary forest sites on former pastures. Additionally, we estimated carbon stocks under a 100-year-old secondary forest and compared them to those of nearby mature forests. Abiotic conditions in the study area were homogenous, enabling us to isolate the effect of land-use change on soil organic carbon stocks. Contrary to our expectations, soil carbon stocks in the top 10 cm did not change with young secondary forest development. Pasture soils stored 24.8 +/- 2.9 Mg ha(-1) carbon (mean +/- standard error) in the top 10 cm, and no accumulation of soil carbon was apparent during the first 15 years of secondary succession. Soil carbon stocks under 100-year-old secondary forests, averaging 43.0 +/- 7.9 Mg ha(-1) (mean +/- standard error), were clearly higher than those recorded at younger sites and approached levels of soil carbon stocks under mature forests. These data indicate that soil carbon stocks in this region of Panama are not affected by the land-use transition from pasture to young secondary regrowth. However, an increase of soil carbon storage might be possible over a longer period of time. Our results support trends observed in other tropical areas and highlight the importance of environmental conditions such as soil properties rather than land-use transitions on soil carbon dynamics. While our understanding of organic carbon dynamics in tropical soils remains limited, these results underscore the challenges of undertaking short-term reforestation projects with the expectation of increasing soil carbon sequestration.
Landscapes in the humid tropics are undergoing a continuous change in land use. Deforestation is still taking its toll on forested areas, but at the same time more and more secondary forests emerge where formerly agricultural lands and pastures are being abandoned. Regarding soil hydrology, the extent to which secondary succession can recover soil hydrological properties disturbed by antecedent deforestation and pasture use is yet poorly understood. We investigated the effect of secondary succession on saturated hydraulic conductivity (Ks) at two soil depths (0-6 and 6-12 cm) using a space-for-time approach in a landscape mosaic in central Panama. The following four land-use classes were studied: pasture (P), secondary forest of 5-8 years of age (SF5), secondary forest of 12-15 years of age (SF12) and secondary forest of more than 100 years of age (SF100), each replicated altogether four times in different micro-catchments across the study region. The hydrological implications of differences in Ks in response to land-use change with land use, especially regarding overland flow generation, were assessed via comparisons with rainfall intensities.
Recovery of Ks could be detected in the 0-6 cm depth after 12 years of secondary succession: P and SF5 held similar Ks values, but differed significantly (alpha = 0.05) from SF12 and SF100 which in turn were indistinguishable. Variability within the land cover classes was large but, due to sufficient replication in the study, Ks recovery could be detected nonetheless. Ks in the 6-12 cm depth did not show any differences between the land cover classes; only Ks of the uppermost soil layer was affected by land-use changes. Overland flow - as inferred from comparisons of Ks with rainfall intensities - is more likely on P and SF5 sites compared to SF12 and 5E100 for the upper sample depth; however, generally low values at the 6-12 cm depth are likely to impede vertical percolation during high rainfall intensities regardless of land use.
We conclude that Ks can recover from pasture use under secondary succession up to pre-pasture levels, but the process may take more than 8 years. In order to gain comprehensive understanding of Ks change with land use and its hydrological implications, more studies with detailed land-use histories and combined measurements of Ks, overland flow, precipitation and throughfall are essential.
Sediment-discharge hysteresis loops are frequently analyzed to facilitate the understanding of sediment transport processes. Hysteresis patterns, however, are often complex and their interpretation can be complicated. Particularly, quantifying hysteresis patterns remains a problematic issue. Moreover, it is currently unknown how much data is required for analyzing sediment-discharge hysteresis loops in a given area. These open questions and challenges motivated us to develop a new method for quantifying suspended-sediment hysteresis. Subsequently, we applied the new hysteresis index to three suspended-sediment and discharge datasets from a small tropical rainforest catchment. The datasets comprised a different number of events and sampling sites. Our analyses show three main findings: (1) datasets restricted to only few events, which is typical for rapid assessment surveys, were always sufficient to identify the dominating hysteresis pattern in our research area. Furthermore, some of these small datasets contained multiple-peak events that allowed identifying intra-event exhaustion effects and hence, limitations in sediment supply. (2) Datasets comprising complete hydrological years were particularly useful for analyzing seasonal dynamics of hysteresis. These analyses revealed an exhaustion of hysteresis on the inter-event scale which also points to a limited sediment supply. (3) Datasets comprising measurements from two consecutive gauges installed at the catchment outlet and on a slope within that catchment allowed analyzing the change of hysteresis patterns along the flowpath. On the slope, multiple-peak events showed a stronger intra-event exhaustion of hysteresis than at the catchment outlet. Furthermore, exhaustion of hysteresis on the inter-event scale was not evident on the slope but occurred at the catchment outlet. Our results indicate that even small sediment datasets can provide valuable insights into sediment transport processes of small catchments. Furthermore, our results may serve as a first guideline on what to expect from an analysis of hysteresis patterns for datasets of varying quality and quantity. (c) 2014 Elsevier B.V. All rights reserved.
Soil in a changing world is subject to both anthropogenic and environmental stresses. Soil monitoring is essential to assess the magnitude of changes in soil variables and how they affect ecosystem processes and human livelihoods. However, we cannot always be sure which sampling design is best for a given monitoring task. We employed a rotational stratified simple random sampling (rotStRS) for the estimation of temporal changes in the spatial mean of saturated hydraulic conductivity (K-s) at three sites in central Panama in 2009, 2010 and 2011. To assess this design's efficiency we compared the resulting estimates of the spatial mean and variance for 2009 with those gained from stratified simple random sampling (StRS), which was effectively the data obtained on the first sampling time, and with an equivalent unexecuted simple random sampling (SRS). The poor performance of geometrical stratification and the weak predictive relationship between measurements of successive years yielded no advantage of sampling designs more complex than SRS. The failure of stratification may be attributed to the small large-scale variability of K-s. Revisiting previously sampled locations was not beneficial because of the large small-scale variability in combination with destructive sampling, resulting in poor consistency between revisited samples. We conclude that for our K-s monitoring scheme, repeated SRS is equally effective as rotStRS. Some problems of small-scale variability might be overcome by collecting several samples at close range to reduce the effect of small-scale variation. Finally, we give recommendations on the key factors to consider when deciding whether to use stratification and rotation in a soil monitoring scheme.
Saturated hydraulic conductivity (Ks) of the soil is a key variable in the water cycle. For the humid tropics, information about spatial scales of Ks and their relation to soil types deduced from soil map units is of interest, as soil maps are often the only available data source for modelling. We examined the influence of soil map units on the mean and variation in Ks along a transect in a tropical rainforest using undisturbed soil cores at 06 and 612 cm depth. The Ks means were estimated with a linear mixed model fitted by residual maximum likelihood (REML), and the spatial variation in Ks was investigated with the maximum overlap discrete wavelet packet transform (MODWPT). The mean values of Ks did not differ between soil map units. The best wavelet packet basis for Ks at 06 cm showed stationarity at high frequencies, suggesting uniform small-scale influences such as bioturbation. There were substantial contributions to wavelet packet variance over the range of spatial frequencies and a pronounced low frequency peak corresponding approximately to the scale of soil map units. However, in the relevant frequency intervals no significant changes in wavelet packet variance were detected. We conclude that near-surface Ks is not dominated by static, soil-inherent properties for the examined range of soils. Several indicators from the wavelet packet analysis hint at the more dominant dynamic influence of biotic processes, which should be kept in mind when modelling soil hydraulic properties on the basis of soil maps.
Landslides are a hazard for humans and artificial structures. From an ecological point of view, they represent an important ecosystem disturbance, especially in tropical montane forests. Here, shallow translational landslides are a frequent natural phenomenon and one local determinant of high levels of biodiversity. In this paper, we apply weighted ensembles of advanced phenomenological models from statistics and machine learning to analyze the driving factors of natural landslides in a tropical montane forest in South Ecuador. We exclusively interpret terrain attributes, derived from a digital elevation model, as proxies to several driving factors of landslides and use them as predictors in our models which are trained on a set of five historical landslide inventories. We check the model generality by transferring them in time and use three common performance criteria (i.e. AUC, explained deviance and slope of model calibration curve) to, on the one hand, compare several state-of-the-art model approaches and on the other hand, to create weighted model ensembles. Our results suggest that it is important to consider more than one single performance criterion.
Approaching our main question, we compare responses of weighted model ensembles that were trained on distinct functional units of landslides (i.e. initiation, transport and deposition zones). This way, we are able to show that it is quite possible to deduce driving factors of landslides, if the consistency between the training data and the processes is maintained. Opening the 'black box' of statistical models by interpreting univariate model response curves and relative importance of single predictors regarding their plausibility, we provide a means to verify this consistency.
With the exception of classification tree analysis, all techniques performed comparably well in our case study while being outperformed by weighted model ensembles. Univariate response curves of models trained on distinct functional units of landslides exposed different shapes following our expectations. Our results indicate the occurrence of landslides to be mainly controlled by factors related to the general position along a slope (i.e. ridge, open slope or valley) while landslide initiation seems to be favored by small scale convexities on otherwise plain open slopes.
Large-scale soy agriculture in the southern Brazilian Amazon now rivals deforestation for pasture as the region's predominant form of land use change. Such landscape-level change can have substantial consequences for local and regional hydrology, but these effects remain relatively unstudied in this ecologically and economically important region. We examined how the conversion to soy agriculture influences water balances and stormflows using stream discharge (water yields) and the timing of discharge (stream hydrographs) in small (2.5-13.5 km2) forested and soy headwater watersheds in the Upper Xingu Watershed in the state of Mato Grosso, Brazil. We monitored water yield for 1 year in three forested and four soy watersheds. Mean daily water yields were approximately four times higher in soy than forested watersheds, and soy watersheds showed greater seasonal variability in discharge. The contribution of stormflows to annual streamflow in all streams was low (< 13% of annual streamflow), and the contribution of stormflow to streamflow did not differ between land uses. If the increases in water yield observed in this study are typical, landscape-scale conversion to soy substantially alters water-balance, potentially altering the regional hydrology over large areas of the southern Amazon.
The flowpaths by which water moves from watersheds to streams has important consequences for the runoff dynamics and biogeochemistry of surface waters in the Amazon Basin. The clearing of Amazon forest to cattle pasture has the potential to change runoff sources to streams by shifting runoff to more surficial flow pathways. We applied end-member mixing analysis (EMMA) to 10 small watersheds throughout the Amazon in which solute composition of streamwater and groundwater, overland flow, soil solution, throughfall and rainwater were measured, largely as part of the Large-Scale Biosphere-Atmosphere Experiment in Amazonia. We found a range in the extent to which streamwater samples fell within the mixing space determined by potential flowpath end-members, suggesting that some water sources to streams were not sampled. The contribution of overland flow as a source of stream flow was greater in pasture watersheds than in forest watersheds of comparable size. Increases in overland flow contribution to pasture streams ranged in some cases from 0% in forest to 27-28% in pasture and were broadly consistent with results from hydrometric sampling of Amazon forest and pasture watersheds that indicate 17- to 18-fold increase in the overland flow contribution to stream flow in pastures. In forest, overland flow was an important contribution to stream flow (45-57%) in ephemeral streams where flows were dominated by stormflow. Overland flow contribution to stream flow decreased in importance with increasing watershed area, from 21 to 57% in forest and 60-89% in pasture watersheds of less than 10 ha to 0% in forest and 27-28% in pastures in watersheds greater than 100 ha. Soil solution contributions to stream flow were similar across watershed area and groundwater inputs generally increased in proportion to decreases in overland flow. Application of EMMA across multiple watersheds indicated patterns across gradients of stream size and land cover that were consistent with patterns determined by detailed hydrometric sampling.
The soils on four lithologies (basaltic conglomerates, Bohio; Andesite; volcanoclastic sediments with basaltic agglomerates, Caimito volcanic; foraminiferal limestone, Caimito marine) on Barro Colorado Island (BCI have high exchangeable Ca concentrations and cation-exchange capacities (CEC) compared to other tropical soils on similar parent material. In the 0-10 cm layer of 24 mineral soils, pH values ranged from 5.7 (Caimito volcanic and Andesite) to 6.5 (Caimito marine), concentrations of exchangeable Ca from 134 mmol(c) kg(-1) (Caimito volcanic) to 585 mmolc kg-1 (Caimito marine), and cation exchange capacities from 317 mmol(c) kg(-1) (Caimito volcanic) to 933 mmol(c) kg(-1) (Caimito marine). X-ray diffractometry of the fraction <2 mu m revealed that smectites dominated the clay mineral assemblage in soil except on Caimito volcanic, where kaolinite was the dominant clay mineral. Exchangeable Ca concentrations decreased with increasing soil depth except on Caimito marine. The weathering indices Chemical Index of Alteration (CIA), Plagioclase Index of Alteration (PIA) and Weathering Index of Parker (WIP) determined for five soils on all geological formations, suggested that in contrast to expectation the topsoil (0-10 cm) appeared to be the least and the subsoil (50-70 cm) and saprolite (isomorphically weathered rock in the soil matrix) the most weathered. Additionally, the weathering indices indicated depletion of base cations and enrichment of Al-(hydr)oxides throughout the soil profile. Tree species did not have an effect on soil properties. Impeded leaching and the related occurrence of overland flow seem to be important in determining clay mineralogy. Our results suggest that (i) edaphic conditions favor the formation of smectites on most lithologies resulting in high CEC and thus high retention capacity for Ca and (ii) that there is an external source such as dust or sea spray deposition supplying Ca to the soils.
The expansion of soybean cultivation into the Amazon in Brazil has potential hydrological effects at local to regional scales. To determine the impacts of soybean agriculture on hydrology, a comparison of net precipitation (throughfall, stemflow) in undisturbed tropical forest and soybean fields on the southern edge of the Amazon Basin in the state of Mato Grosso is needed. This study measured throughfall with troughs and stemflow with collar collectors during two rainy seasons. The results showed that in forest 91.6% of rainfall was collected as throughfall and 0.3% as stemflow, while in soybean fields with two-month old plants, 46.2% of rainfall was collected as throughfall and 9.0% as stemflow. Hence, interception of precipitation in soybean fields was far greater than in intact forests. Differences in throughfall, stemflow and net precipitation were found to be mainly associated with differences in plant structure and stem density in transitional forest and soybean cropland. Because rainfall interception in soybean fields is higher than previously believed and because both the area of cropland and the frequency of crop cycles (double cropping) are increasing rapidly, interception needs to be reconsidered in regional water balance models when consequences of land cover changes are analyzed in the Amazon soybean frontier region. Based on the continued expansion of soybean fields across the landscape and the finding that net precipitation is lower in soy agriculture, a reduction in water availability in the long term can be assumed.