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Aim We construct a framework for mapping pattern and drivers of insect diversity at the continental scale and use it to test whether and which environmental gradients drive insect beta diversity. Location Global; North and Central America; Western Europe. Time period 21st century. Major taxa studied Insects. Methods An informatics system was developed to integrate terrestrial data on insects with environmental parameters. We mined repositories of data for distribution, climatic data were retrieved (WorldClim), and vegetation parameters inferred from remote sensing analysis (MODIS Vegetation Continuous Fields). Beta diversity between sites was calculated and then modeled with two methods, Mantel test with multiple regression and generalized dissimilarity modeling. Results Geographic distance was the main driver of insect beta diversity. Independent of geographic distance, bioclimate variables explained more variance in dissimilarity than vegetation variables, although the particular variables found to be significant were more consistent in the latter, particularly, tree cover. Tree cover gradients drove compositional dissimilarity at denser coverages, in both continental case studies. For climate, gradients in temperature parameters were significant in driving beta diversity more so than gradients in precipitation parameters. Main conclusions Although environmental gradients drive insect beta diversity independently of geography, the relative contribution of different climatic and vegetational parameters is not expected to be consistent in different study systems. With further incorporation of additional temporal information and variables, this approach will enable the development of a predictive framework for conserving insect biodiversity at the global scale., An informatics system was developed to integrate terrestrial data on insects with environmental parameters and to infer biogeographic maps. Beta diversity was driven by geographic, climatic, and vegetation gradients.

Heterogeneity in forest structure, naturally occurring or induced by management, is continuous in space and time. However, measures used to quantify structure of forests are scale-variant, as they rely on bounded observations on either ecological or forest inventory observation units. The understanding of the influence of the scale of observation in mapping of forest structural heterogeneity is limited. Therefore, we researched into effects of plot size on quantifying forest structural heterogeneity, where we describe heterogeneity by three indices in stands under different management systems. In addition, we studied the performance of structural indices in separating different forest management systems across plot sizes, and created wall to wall maps of the indices using airborne LiDAR metrics describing the vertical distribution of canopy heights at different scales of observation. The studied indices are: Gini Coefficient (GC), Structural Complexity Index (SCI), and Enhanced Structural Complexity Index (ESCI). SCI and ESCI require fully mapped plots whereas GC has no information on individual tree locations. Inventory data from 95 one-hectare plots covering a range of management intensities from un-managed to age class forests were used. We quantified the three structural indices for 18 plot sizes ranging from 225 m2 to 10,000 m2. Linear fixed effects models were used to study the effects of plot sizes in different levels of structural heterogeneity and Random Forest (RF) models used to provide wall-to-wall maps at varying scales from airborne LiDAR data. The simulation showed that all indices were influenced by the scale of observation with larger effects for plots in forests with higher structural heterogeneity. For the data analyzed we found a threshold scale for enumerating stand structural heterogeneity between 900 m2 and 2500 m2. However, stable field and remote sensing predictions of stand structural heterogeneity required plots at least ⩾ 2500 m2. Compared to GC, SCI and ESCI improved separation of forest structure in the three management systems and at all observed scales. A change of plot sizes affected bivariate relationships between structural indices and airborne LiDAR metrics as well as the resultant predictive models. Smaller plot sizes yielded weaker relationships and predictive models. All structure indices were predicted from airborne LiDAR with RMSE ⩽ 22 % at scales equal or larger than the identified threshold plot size. These findings are relevant to optimize plot sizes for efficient inventory and mapping of forest structural heterogeneity, as well as for the design of natural resource inventories. Additionally, derived maps are useful for studies on forest structure and the link with forest growth, degradation, management intensity, productivity, and biodiversity in the regions.

In various regions in Southeast Asia, over the past decades, natural tropical forests have rapidly been converted into monoculture plantations of rubber (Hevea brasiliensis), a consequence of the rubber boom. With the goal of slowing the ecologically and environmentally detrimental conversion of forests to rubber plantations and to encourage the reconversion of rubber plantations back to close-to-nature rainforests, we developed a theoretical combined market and government payment system. To evaluate the potential impacts of such system, we carried out a simulation study plus sensitivity analyses, using the latest land-use data from Xishuangbanna, Southwest China. The results of this simulation suggest that the payment system may make the annual reconversion rate develop from 9,009 ha to 4,610 ha over the modeled period from 2021 to 2050, so that the total reconversion area by 2050 would sum up to 197,902 ha. The total net present value (NPV) of compensatory payments for the whole period, in this case, would sum up to US$3.19 billion. The total carbon sequestration benefit resulting from the replacement of rubber plantations would be 11.37 million tons of carbon (tC) over the modelled period, translating into a cost of US$280.44 per tC. Sensitivity analyses revealed that higher variations in rubber prices cause more difficulty in determining compensatory payment. Of course, changes in a number of factors may lead to a reduction of the total NPV of compensatory payments, including increases in the carbon price or traditional medicine price, increases in the discount rate, and decreases to the rubber price and the targeted final reconversion rate. The area-specific compensatory payments ($11,154–$16,106/ha) and area-specific carbon sequestration (46.39–57.45 tC/ha) would then increase linearly as the targeted final reconversion rate increases. This new integrated payment system has the potential to contribute to restoring rainforest in rubber monoculture-dominated landscape.

Background: Until 50 years ago, Xishuangbanna was a heavy forest-covered region with high biodiversity. Attributed to the rubber boom that took place in the region during the last decades, natural forest area decreased quickly and was replaced by monoculture rubber plantations (Hevea brasiliensis). To slow down the deforestation rate and encourage rubber plantation retiring, a market and government-combined compensatory payment system was developed with consideration of market-priced ecosystem services. Results: In the baseline scenario, the annual retiring rate reduced from 9,353±17.8 ha to 4,669±18.5 ha in the projection period, and the final total retiring area in 2050 was 202.477±0.063 thousand ha. The compensatory payment increased along with the growth of rubber plantations. In the projected period (2021-2050), the total NPV (net present value) of compensatory payment was $3,364.820±1.669 million. The total carbon sequestration benefit resulting from replacement of artificial rainforests was 11.718±0.005 million tC. In sensitivity analyses, more uncertainties of compensatory payment were expected with a higher variation of rubber price. The rise of carbon price, discount rate and traditional medicine price, and the decrease of rubber price and final retiring rate could reduce the total NPV of payment. Conclusions: The market and government-combined payment system has high possibility to effectively encourage rubber retiring and reduce government payment. By the projection of the market and government-combined payment system, most of the small patches of rubber plantation were disappeared in 2050. The annual retiring area decreased gradually along the projection period. The projected compensatory payment and the area-specific payment increased, while the increment of compensatory payment decreased. The carbon sequestration benefit by rubber plantation retiring was negative in the first decade. All the tested factors (i.e., rubber price, rubber price variation, carbon price, final retiring rate, discount rate, and traditional medicine price) could affect the compensatory payment. Currently, the payment system may not so attractive; however, the situation could change when more market-priced ecosystem services are involved in the system.

Expansion of rubber plantations into sub-optimal environments has been a dominating land conversion in continental South-East Asia in the last decade. Regional evaluation of the carbon sequestration potential of rubber trees depends largely on the selection of suitable allometric equations and the biomass-to-carbon conversion factor. Most equations are age-, elevation-, or clone-specific, and their application therefore gives uncertain results at the landscape level with varying age groups, elevation ranges, and clone types. Currently, for rubber-based systems, none of the allometric equations takes environmental factors (e.g. climate, topographic condition, soil properties, and management scheme) into consideration to allow pan-tropical usage. Against this background, 30 rubber trees with a root profile of up to 2 m were destructively harvested and 882 rubber trees were measured non-destructively in 27 plots, covering rotation lengths of 4–35 years, elevation gradients of 621–1127 m, and locally used clone types (GT1, PRIM600, Yunyan77-4) in mountainous South Western China. Allometric equations for aboveground biomass ( AGB ) estimations considering diameter at breast height ( DBH ), tree height ( H ), and wood density were superior to other equations. A simpler model with similar performance ( AGB = 0.0419 DBH 2.316 H 0.478 ) can be used if tree-specific wood density is not available. For belowground biomass ( BGB ) a model using only DBH can provide a robust prediction ( BGB = 0.207 DBH 1.668 ). We also tested goodness of fit for the recently proposed pan-tropical forest model, which includes a bioclimatic factor E , combining indices of temperature and precipitation variability and drought intensity. Prediction of AGB by the model calibrated with the harvested rubber tree biomass and wood density was more accurate than the results produced by the pan-tropical forest model adjusted to local conditions. The relationships between DBH and height and between DBH and biomass were influenced by tapping, therefore biomass and C stock calculations for rubber have to be done using species-specific allometric equations. Based on the analysis of environmental factors acting at the landscape level, we found that above- and belowground carbon stocks were mostly affected by stand age, soil clay content, aspect, and planting density. Increasing planting density to >570 trees per ha according to the regional plantation management strategy had a negative impact on aboveground carbon stock of old rubber plantations. The integration of bioclimatic and regional management factors is a further approach to build widely applicable biomass models for pan-tropical rubber-based systems. The results of this study provide reference for reliable carbon accounting in other rubber-cultivated regions.

Determining the age of rubber tree plantations (Hevea brasiliensis) is of great interest to plantation managers and land-use decision makers as it enables, among others, reliable forecasts of resource availability. The acquisition of age information with field campaigns, however, is time consuming, laborious and expensive. We present an approach that facilitates rapid assessment of rubber plantation age at regional scales applying very dense Landsat times series (LTS) satellite data over China's second largest rubber planting area – Xishuangbanna. We aggregated 270 Landsat TM and ETM + surface reflectance images into annual best-available-pixel composites of minimum Normalized Difference Moisture Index ( NDMI ). The annual composites were classified into vegetated and non-vegetated pixels applying a global NDMI threshold of 0. As it is common practice in Xishuangbanna to clear the land before a new plantation is established, the last year in which a pixel located in a rubber plantation, was classified as non-vegetated, was recorded as the year of plantation establishment. The resultant plantation age map was validated using a stratified random sample of 184 data points, collected by visual interpretation of historical Landsat data. A Root Mean Square Error (RMSE) of 2.5 years was achieved. We estimate that in 2015 50% of Xishuangbanna's rubber plantations had an age suitable for latex tapping (8–25 years), 27% were too young to be tapped ( 25 years) and will be presumably harvested for wood in the near future. The proposed technique enables acquisitions of accurate rubber plantation age information from Landsat time series and NDMI over large areas with the potential of providing insights into land cover dynamics and allowing for the development of improved management strategies and local decision support activities.

Hemispherical canopy photography is a widely used technique to observe crown-related forest variables. However, standardization of this technique remains challenging, as exposure and threshold settings continue to constitute the main sources of variation of such photographs. This paper, therefore, presents a new method to overcome standardization issues by using thermal canopy photography. With a thermal camera, images are produced which are not critically limited in their dynamic range so that photographic exposure becomes irrelevant. Moreover, the high temperature contrast between “sky” and “non-sky”, resulting from extreme low sky temperatures, facilitates the unambiguous selection of a threshold which separates “sky” from “non-sky” pixels. For our comparison, we have taken canopy images with a high-resolution thermal camera (VarioCam hr head [Infratec, Dresden, Germany]) and an optical camera (Nikon D70s). The correlation of canopy closure values derived from the image pairs was r = 0.98. Our findings thus show that thermal canopy photography is a promising and simple to use alternative to optical canopy photography, because it limits possible sources of variability, since exposure settings and threshold definition cease to be an issue.

Understanding and managing pollination service is hindered by taxonomic impediments and paucity of data, particularly in the tropics. Herein we apply integrative species delineation and taxonomy to test impacts of land use on the diversity of bee communities within Xishuangbanna (Yunnan, south China), a highly biodiverse tropical region which has undergone extensive land conversion to rubber plantation. 128 Operational Taxonomic Units (OTU) were inferred by an iterative and integrative approach. Bee activity differed significantly across land use samples, although community composition corresponded more to level of vegetation density, when accounting for spatial structure. Species diversity was high in young rubber plantations, although composition overlapped with other species-rich habitats (natural forest edge and river banks), and older plantations (>8 years) showed very low diversity under all measures. Community structures were similar between the natural forest interior and edge, although analysis indicated contrasting drivers of diversity, with clustering in the interior and overdispersion in the forest edge. Further, phylogenetic diversity and derived indices were underestimated when reference data were omitted from analysis. The description of bee communities herein permits more informed choices in land management with respect to ensuring continuation of essential services by bees.

All rubber tree clones (Hevea brasiliensis) exhibit regular annual wintering characterized by senescence and abscission of leaves. After 3–4 weeks, this is followed by the onset of new leaves. It is likely that the timing of leaf onset affects the susceptibility of rubber trees to rubber powdery mildew disease, as this predominantly infests young leaves. However, little information is available on the phenological behavior of different rubber clones, or how meteorological factors affect such behavior. We assessed the wintering and flowering patterns of five rubber clones in Xishuangbanna, southwest China, based on observations made from 1978 to 2011, and evaluated how these patterns responded to different meteorological factors. Partial least squares regression was used to analyze the timing of defoliation, refoliation, and flowering. Our results showed that the two clones RRIM 600 and GT1 defoliated during the last week of December and refoliated in the last week of January, and clones Yunyan 277-5, Yunyan 34-4, and PR 107 defoliated during the first week of January and refoliated in the second week of February. The number of hours of sunshine during both the rainy season and the cold dry period in the dry season were important determinants of phenological changes in the rubber trees. Similarly, higher temperatures tended to delay the onset of defoliation and refoliation, and were a triggering factor for the onset of flowering. These results may help rubber cultivators to schedule appropriate disease control measures, as well as to design hybridization programs aiming at the production of clones which are resistant to foliar disease.

In the context of the international conventions on climate change (United Nations Framework Convention on Climate Change, UN-FCCC) and biological diversity (United Nations Convention on Biological Diversity, UN-CBD), the demand for up-to-date information on tree resources within and outside forests is higher than ever before, urging for approaches to reliably monitor tree resources across large areas. While for the assessment of tree resources within forests a variety of sophisticated forest inventory methods has been developed and tested, fewer efforts have been undertaken that focus on the assessment of trees outside forests (TOF). While the variables of interest are essentially the same, main differences in the assessment of trees within and outside forests arise from the distinctive characteristics of TOF, including uneven spatial distribution, specific geometric arrangements, specific functions, and the presence of other land uses. In this chapter, we give an overview of inventory approaches suitable for the science-based assessment of TOF, with a focus on agricultural lands, and highlight how inventory designs developed for forest inventories may be adapted to the assessment of trees on non-forest lands. The chapter covers considerations about operational definitions of TOF, describes implications resulting from modeling tree attributes using allometric models, and reviews the application of different response (plot) designs used in ground-based or remote sensing-based TOF assessments. Further, current approaches to monitor TOF resources with active and passive remote sensing sensors, such as LiDAR, RADAR, SPOT, RapidEye, Landsat, MODIS, etc., are presented, and besides, it is outlined how field inventory data and remote sensing data can potentially be integrated to increase the precision of parameter estimates.

Previous 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.

Xishuangbanna has been largely transformed from biodiverse natural forests and mixed-use farms into monoculture rubber plantations in just twenty years. This conversion has expanded into forests previously protected by the community and onto marginal sites at high-elevation. Market-based ecosystem payments, especially carbon financing, are potential tools to prevent further forest loss in China. Here, we compare rubber net present value (NPV), carbon sequestration, and seed-plant species diversity for Xishuangbanna given three land-use scenarios: Business-As-Usual (BAU), Economic Oriented Scenario (EOS) and Conservation Oriented Scenario (COS) using a previously published spatial map of rubber profitability. The EOS achieved the greatest rubber profit but caused substantial reductions in natural forest area, biodiversity and carbon stocks. The EOS also requires substantial immigration of workers into a remote and ecologically important region with little social infrastructure for basic security, food security, health-care and education, causing frequently ignored costs. As expected, the COS will maintain the highest levels of natural forest area, sequester 57% more carbon, and 71% more biodiversity than EOS. Given the conservation value of the carbon stores and rich biodiversity residing in Xishuangbanna's natural forests, reducing rubber NPV only marginally would probably cost less than attempting to recover these resources. We recommend that rubber plantations be limited to established, productive lowland areas whilst protecting intact high-elevation forest and reforesting low-productivity plantations. These actions will enhance carbon sequestration and biodiversity conservation. Management policies focused solely on profits, like the EOS scenario, will fail to sustain the entire range of natural resources and ecosystem services. The prices in the carbon market would have to be considerably larger than they are currently to compete with the profitability of rubber.

Canopy 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.

An analysis and multi-model approach, based on a statistically derived Global Environmental Stratification (GEnS) and using a downscaled ensemble (n = 63) of CIMP5 Earth System Models applied across four representative concentration pathways (RCP), has been used to project the impact of climate change on spatial distribution of bioclimatic zones and ecosystems within the biodiverse rich Xishuangbanna Prefecture, Yunnan Province, by the year 2050. Four bioclimatic zones and 9 strata were identified, overlaid with protected areas, and associated with on-going landuse change, i.e. a rapid increase in rubber plantation from 8% to 22% of total area between 2002 and 2010. Significant changes in the areal extent and distribution of all zones and strata are projected, with an averaged mean annual temperature increase ranging from 1.6 degrees C to 2.4 degrees C By 2050, there are significant geographical shifts in all identified strata, with an average upward shift of 309 m of elevation for all strata. On average, more than 75% of Xishuangbanna is predicted to shift to a different zone, with 96% shifting to a different stratum. The area conducive to rubber plantations, currently limited by climatic conditions, expands to nearly 75% of the total area. Climatic change potentially removes the bioclimatic barriers to further expansion of rubber plantations within the area and increases pressure on remaining biodiversity both within and outside of protected areas. The analysis provides the basis for understanding potential impacts of changing bioclimatic conditions on managed and unmanaged ecosystems and landuse change trends, within the context of ongoing rapid change and agricultural expansion in the area. Current efforts to conserve forests, biodiversity and traditional landuse systems require an improved understanding of both the projected climatic changes and the responses of biodiversity and traditional agricultural systems to changing conditions. (C) 2013 Elsevier Ltd. All rights reserved.

Rapid land-use transformations are occurring throughout the Mekong Region, and especially in Xishuangbanna, Yunnan Province in southwest China. Most of this is due to the spread of monoculture rubber plantations. Using a new map derived from Landsat and RapidEye imagery tracking the spread of rubber from 1992 to 2010 in combination with a literature review and interviews with key local experts and officials, we performed a general overview of the extent, causes and consequences of landscape transformation in Xishuangbanna. We discovered that structural and functional biodiversity has been reduced, habitat fragmentation has increased,,carbon sequestration in natural forests has been reduced, and hydrological systems altered. For humans, while incomes have risen, food insecurity has also grown. The drivers of these changes are regional economic integration, government policy, and conservation vs development value systems. To improve land-use management, we surveyed the availability of ecological and socioeconomic indicators that may better track such changes. We found that combining both types of indicators within a multi-scale conservation planning framework would help to inform policy making in the region. As yet, however, there is little integrative research using indicators to track changes in ecosystems and human livelihoods in the region. (C) 2012 Elsevier Ltd. All rights reserved.

At least 10 different methods to determine exposure for hemispherical photographs were used by scientists in the last two decades, severely hampering comparability among studies. Here, an overview of the applied methods is reported. For the standardization of photographic exposure, a time-consuming reference measurement in the open land towards the unobstructed sky was required so far. The two Histogram Methods proposed here make use of the technical advances of digital cameras which enable users to assess a photograph’s histogram directly at the location of measurement. This avoids errors occurring due to variations in sky lighting happening in the time span between taking the reference measurement and reaching the sample location within the forest. The Histogram Methods speed up and simplify taking hemispherical photographs, and introduce an objectively applicable, standardized approach. We highlight the importance of correct exposure by quantifying the overestimation of gap fraction resulting from auto-exposed photographs under a wide range of canopy openness situations. In our study, gap fraction derived from auto-exposed photographs reached values up to 900% higher than those derived from non-overexposed photographs. By investigating the size of the largest gap per photograph and the number of small gaps (gaps contributing less than 0.1% to gap fraction), we concluded that the overestimation of gap fraction resulted mainly from the overexposure of vegetation surrounding large gaps.

China is investing immense resources for planting trees, totalling more than US$ 100 billion in the past decade alone. Every year, China reports more afforestation than the rest of the world combined. Here, we show that China's forest cover gains are highly definition-dependent. If the definition of ‘forest’ follows FAO criteria (including immature and temporarily unstocked areas), China has gained 434 000 km 2 between 2000 and 2010. However, remotely detectable gains of vegetation that non-specialists would view as forest (tree cover higher than 5 m and minimum 50% crown cover) are an order of magnitude less (33 000 km 2 ). Using high-resolution maps and environmental modelling, we estimate that approximately 50% of the world's forest with minimum 50% crown cover has been lost in the past approximately 10 000 years. China historically lost 1.9–2.7 million km 2 (59–67%), and substantial losses continue. At the same time, most of China's afforestation investment targets environments that our model classes as unsuitable for trees. Here, gains detectable via satellite imagery are limited. Conversely, the regions where modest gains are detected are environmentally suitable but have received little afforestation investment due to conflicting land-use demands for agriculture and urbanization. This highlights the need for refined forest monitoring, and greater consideration of environmental suitability in afforestation programmes.

Tropical lowland rainforests are increasingly threatened by the expansion of agriculture and the extraction of natural resources. In Jambi Province, Indonesia, the interdisciplinary EFForTS project focuses on the ecological and socio-economic dimensions of rainforest conversion to jungle rubber agroforests and monoculture plantations of rubber and oil palm. Our data confirm that rainforest transformation and land use intensification lead to substantial losses in biodiversity and related ecosystem functions, such as decreased above- and below-ground carbon stocks. Owing to rapid step-wise transformation from forests to agroforests to monoculture plantations and renewal of each plantation type every few decades, the converted land use systems are continuously dynamic, thus hampering the adaptation of animal and plant communities. On the other hand, agricultural rainforest transformation systems provide increased income and access to education, especially for migrant smallholders. Jungle rubber and rubber monocultures are associated with higher financial land productivity but lower financial labour productivity compared to oil palm, which influences crop choice: smallholders that are labour-scarce would prefer oil palm while land-scarce smallholders would prefer rubber. Collecting long-term data in an interdisciplinary context enables us to provide decision-makers and stakeholders with scientific insights to facilitate the reconciliation between economic interests and ecological sustainability in tropical agricultural landscapes.

The rapidly growing car industry in China has led to an equally rapid expansion of monoculture rubber in many regions of South East Asia. Xishuangbanna, the second largest rubber planting area in China, located in the Indo-Burma biodiversity hotspot, supplies about 37% of the domestic natural rubber production. There, high income possibilities from rubber drive a dramatic expansion of monoculture plantations which poses a threat to natural forests. For the first time we mapped rubber plantations in and outside protected areas and their net present value for the years 1988, 2002 (Landsat, 30 m resolution) and 2010 (RapidEye, 5 m resolution). The purpose of our study was to better understand the pattern and dynamics of the expansion of rubber plantations in Xishuangbanna, as well as its economic prospects and conservation impacts. We found that 1) the area of rubber plantations was 4.5% of the total area of Xishuangbanna in 1988, 9.9% in 2002, and 22.2% in 2010; 2) rubber monoculture expanded to higher elevations and onto steeper slopes between 1988 and 2010; 3) the proportion of rubber plantations with medium economic potential dropped from 57% between 1988 and 2002 to 47% in 2010, while the proportion of plantations with lower economic potential had increased from 30% to 40%; and 4) nearly 10% of the total area of nature reserves within Xishuangbanna has been converted to rubber monoculture by 2010. On the basis of our findings, we conclude that the rapid expansion of rubber plantations into higher elevations, steeper terrain, and into nature reserves (where most of the remaining forests of Xishuangbanna are located) poses a serious threat to biodiversity and environmental services while not producing the expected economic returns. Therefore, it is essential that local governments develop long-term land use strategies for balancing economic benefits with environmental sustainability, as well as for assisting farmers with the selection of land suitable for rubber production. peerReviewed

The 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. peerReviewed

Deforestation 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 shadehouse. 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. peerReviewed