1,721,084 research outputs found
Fig. 3 in Stingless Bee (Hymenoptera: Apidae: Meliponini) Diversity In Dipterocarp Forest Reserves In Peninsular Malaysia
No full textFig. 3. Stingless bee species accumulation at traps in the six Virgin Jungle Reserves.Published as part of Salim, Hannah M. W., Dzulkiply, Ahmad Dzamir, Harrison, Rhett D., Fletcher, Christine & Kassim, Abd Rahman, 2012, Stingless Bee (Hymenoptera: Apidae: Meliponini) Diversity In Dipterocarp Forest Reserves In Peninsular Malaysia, pp. 213-219 in Raffles Bulletin of Zoology 60 (1) on page 216, DOI: 10.5281/zenodo.534723
Environmental and geographic factors driving dung beetle (Coleoptera: Scarabaeidae: Scarabaeinae) diversity in the dipterocarp forests of Peninsular Malaysia
No full textDoll, Hannah M., Butod, Elizabeth, Harrison, Rhett D., Fletcher, Christine, Kassim, Abd Rahman, Ibrahim, Shamsudin, Potts, Matthew D. (2014): Environmental and geographic factors driving dung beetle (Coleoptera: Scarabaeidae: Scarabaeinae) diversity in the dipterocarp forests of Peninsular Malaysia. Raffles Bulletin of Zoology 62: 549-560, DOI: http://doi.org/10.5281/zenodo.535447
Fig. 2 in Stingless Bee (Hymenoptera: Apidae: Meliponini) Diversity In Dipterocarp Forest Reserves In Peninsular Malaysia
No full textFig. 2. Sampling design for one set of three transects. Three sets of three 300-m sampling transects were established at each Virgin Jungle Reserve. Transects ran parallel to each other with approximately 500 m between them. Nine baiting points were established along each transect.Published as part of Salim, Hannah M. W., Dzulkiply, Ahmad Dzamir, Harrison, Rhett D., Fletcher, Christine & Kassim, Abd Rahman, 2012, Stingless Bee (Hymenoptera: Apidae: Meliponini) Diversity In Dipterocarp Forest Reserves In Peninsular Malaysia, pp. 213-219 in Raffles Bulletin of Zoology 60 (1) on page 216, DOI: 10.5281/zenodo.534723
Mapping Leaf Area Index in subtropical upland ecosystems using RapidEye imagery and the randomForest algorithm
No full textCanopy leaf area, frequently quantified by the Leaf Area Index (LAI), serves as the dominant control over primary production, energy exchange, transpiration, and other physiological attributes related to ecosystem processes. Maps depicting the spatial distribution of LAI across the landscape are of particularly high value for a better understanding of ecosystem dynamics and processes, especially over large and remote areas. Moreover, LAI maps have the potential to be used by process models describing energy and mass exchanges in the biosphere/atmosphere system. In this article we assess the applicability of the RapidEye satellite system, whose sensor is optimized towards vegetation analyses, for mapping LAI along a disturbance gradient, ranging from heavily disturbed shrub land to mature mountain rainforest. By incorporating image texture features into the analysis, we aim at assessing the potential quality improvement of LAI maps and the reduction of uncertainties associated with LAI maps compared to maps based on Vegetation Indexes (VI) solely. We identified 22 out of the 59 image features as being relevant for predicting LAI. Among these, especially VIs were ranked high. In particular, the two VIs using RapidEye’s RED-EDGE band stand out as the top two predictor variables. Nevertheless, map accuracy as quantified by the mean absolute error obtained from a 10-fold cross validation (MAE_CV) increased significantly if VIs and texture features are combined (MAE_CV = 0.56), compared to maps based on VIs only (MAE_CV = 0.62). We placed special emphasis on the uncertainties associated with the resulting map addressing that map users often treat uncertainty statements only in a pro-forma manner. Therefore, the LAI map was complemented with a map depicting the spatial distribution of the goodness-of-fit of the model, quantified by the mean absolute error (MAE), used for predictive mapping. From this an area weighted MAE (= 0.35) was calculated and compared to the unweighted MAE of 0.29. Mapping was done using randomForest, a widely used statistical modeling technique for predictive biological mapping
Enhanced structural complexity index: An improved index for describing forest structural complexity
No full textThe horizontal distribution of stems, stand density and the differentiation of tree dimensions are among the most important aspects of stand structure. An increasing complexity of stand structure is often linked to a higher number of species and to greater ecological stability. For quantification, the Structural Complexity Index (SCI) describes structural complexity by means of an area ratio of the surface that is generated by connecting the tree tops of neighbouring trees to form triangles to the surface that is covered by all triangles if projected on a flat plane. Here, we propose two ecologically relevant modifications of the SCI: The degree of mingling of tree attributes, quantified by a vector ruggedness measure, and a stem density term. We investigate how these two modifications influence index values. Data come from forest inventory field plots sampled along a disturbance gradient from heavily disturbed shrub land, through secondary regrowth to mature montane rainforest stands in Mengsong, Xishuangbanna,Yunnan,China. An application is described linking structural complexity, as described by the SCI and its modified versions, to changes in species composition of insect communities. The results of this study show that the Enhanced Structural Complexity Index (ESCI) can serve as a valuable tool for forest managers and ecologists for describing the structural complexity of forest stands and is particularly valuable for natural forests with a high degree of structural complexity
Scale-dependent relationships between soil organic carbon stocks, land-use types and biophysical characteristics in a tropical montane landscape
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Data from: Quantifying the factors affecting leaf litter decomposition across a tropical forest disturbance gradient
No full textDeforestation and forest degradation are driving unprecedented declines in biodiversity across the tropics, and understanding the consequences of these changes for ecosystem functioning is essential for human well-being. Forest degradation and loss alter ecosystem functioning through changes in species composition and abiotic conditions. However, the consequences of these changes for heterospecific processes are often poorly understood. Leaf litter decomposition is a major source of atmospheric carbon and critical for carbon and nutrient cycling. Through a highly replicated litter-bag experiment (3360 bags), we quantified the effects of litter quality, decomposer functional diversity and seasonal precipitation regime on litter decomposition along a tropical disturbance gradient in SW China. In addition, using soil and litter from sites selected from across the disturbance gradient, we established replicated litter-bed treatments and exposed these to a gradient of simulated canopy cover in a shade-house. Across the landscape, mass loss from litter-bags after 12 months varied from 7% to 98%. Even after 12 months, litter-bags installed at the beginning of the dry season had much lower mass loss than those installed at the beginning of the wet season. As expected, litter quality and faunal exclusion had substantial effects on decomposition rates. Decomposition rates declined along the disturbance gradient from mature forest, through regenerating forest to open land, although the effect size was strongly dependent on installation season. The effect of excluding meso- and macro-invertebrates increased with increasing forest degradation, whereas the effect of litter quality declined. Results from the shade-house experiment strongly suggested that forest degradation effects were driven predominantly by changes in micro-climatic conditions resulting from increased canopy openness. To better model the impacts of anthropogenic global change on litter decomposition rates, it will be important to consider landscape scale processes, such as forest degradation
Using metabarcoding to ask if easily collected soil and leaf-litter samples can be used as a general biodiversity indicator
No full textThe targeted sequencing of taxonomically informative genetic markers, sometimes known as metabarcoding, allows eukaryote biodiversity to be measured rapidly, cheaply, comprehensively, repeatedly, and verifiably. Metabarcoding helps to remove the taxonomic impediment, which refers to the great logistical difficulties of describing and identifying species, and thus promises to improve our ability to detect and respond to changes in the natural environment. Now, sampling has become a rate-limiting step in biodiversity measurement, and in an effort to reduce turnaround time, we use arthropod samples from southern China and Vietnam to ask whether soil, leaf litter, and aboveground samples provide similar ecological information. A soil or leaf-litter sample can be collected in minutes, whereas an aboveground sample, such as from Malaise traps or canopy fogging, can require days to set up and run, during which time they are subject to theft, damage, and deliberate contamination. Here we show that while the taxonomic compositions of soil and leaf-litter samples are very different from aboveground samples, both types of samples provide similar ecological information, in terms of ranking sites by species richness and differentiating sites by beta diversity. In fact, leaf-litter samples appear to be as or more powerful than Malaise-trap and canopy-fogging samples at detecting habitat differences. We propose that metabarcoded leaf-litter and soil samples be widely tested as a candidate method for rapid environmental monitoring in terrestrial ecosystems
Phylogenetic clustering increases with succession for lianas in a Chinese tropical montane rain forest
No full textPrevious research found that phylogenetic clustering increased with disturbance for tropical trees, suggesting that community assembly is mainly influenced by abiotic factors during early succession. Lianas are an important additional component of tropical forests, but their phylogenetic community structure has never been investigated. Unlike tropical trees, liana abundance is often high in disturbed forests and diversity can peak in old secondary forest. Therefore, phylogenetic structure along a disturbance gradient might also differ from tropical tree communities. Here we determined phylogenetic community structure of lianas along a disturbance gradient in a tropical montane forest in China, using the net relatedness index (NRI) from 100 equivalent phylogenies with varying branch length that were constructed using DNA-barcode sequences. Three additional phylogenetic indices were also considered for comparison. When NRI was used as index phylogenetic clustering of liana communities decreased with decreasing tree basal area, suggesting that liana competitive interactions dominate during early succession, which is in contrast to the pattern reported for trees. Liana communities in mature forests, on the other hand, were phylogenetic clustered, which could be caused by dispersal limitation and/or environmental filtering. The three additional phylogenetic indices identified different, sometimes contradicting predictors of phylogenetic community structure, indicating that caution is needed when generalizing interpretations of studies based on a single phylogenetic community structure index. Our study provides a more nuanced picture of non-random assembly along disturbance gradients by focusing on a non-tree forest component
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