Balancing economic and ecological functions in smallholder and industrial oil palm plantations.

The expansion of the oil palm industry in Indonesia has improved livelihoods in rural communities, but comes at the cost of biodiversity and ecosystem degradation. Here, we investigated ways to balance ecological and economic outcomes of oil palm cultivation. We compared a wide range of production systems, including smallholder plantations, industrialized company estates, estates with improved agronomic management, and estates with native tree enrichment. Across all management types, we assessed multiple indicators of biodiversity, ecosystem functions, management, and landscape structure to identify factors that facilitate economic-ecological win-wins, using palm yields as measure of economic performance. Although, we found that yields in industrialized estates were, on average, twice as high as those in smallholder plantations, ecological indicators displayed substantial variability across systems, regardless of yield variations, highlighting potential for economic-ecological win-wins. Reducing management intensity (e.g., mechanical weeding instead of herbicide application) did not lower yields but improved ecological outcomes at moderate costs, making it a potential measure for balancing economic and ecological demands. Additionally, maintaining forest cover in the landscape generally enhanced local biodiversity and ecosystem functioning within plantations. Enriching plantations with native trees is also a promising strategy to increase ecological value without reducing productivity. Overall, we recommend closing yield gaps in smallholder cultivation through careful intensification, whereas conventional plantations could reduce management intensity without sacrificing yield. Our study highlights various pathways to reconcile the economics and ecology of palm oil production and identifies management practices for a more sustainable future of oil palm cultivation.

Seasonal fluctuations of litter and soil Collembola and their drivers in rainforest and plantation systems.

Rainforest conversion and expansion of plantations in tropical regions change local microclimate and are associated with biodiversity decline. Tropical soils are a hotspot of animal biodiversity and may sensitively respond to microclimate changes, but these responses remain unexplored. To address this knowledge gap, here we investigated seasonal fluctuations in density and community composition of Collembola, a dominant group of soil invertebrates, in rainforest, and in rubber and oil palm plantations in Jambi province (Sumatra, Indonesia). Across land-use systems, the density of Collembola in the litter was at a maximum at the beginning of the wet season, whereas in soil it generally varied little. The community composition of Collembola changed with season and the differences between land-use systems were most pronounced at the beginning of the dry season. Water content, pH, fungal and bacterial biomarkers, C/N ratio and root biomass were identified as factors related to seasonal variations in species composition of Collembola across different land-use systems. We conclude that (1) conversion of rainforest into plantation systems aggravates detrimental effects of low moisture during the dry season on soil invertebrate communities; (2) Collembola communities are driven by common environmental factors across land-use systems, with water content, pH and food availability being most important; (3) Collembola in litter are more sensitive to climatic variations than those in soil. Overall, the results document the sensitivity of tropical soil invertebrate communities to seasonal climatic variations, which intensifies the effects of the conversion of rainforest into plantation systems on soil biodiversity.

Transformation scenarios towards multifunctional landscapes: A multi-criteria land-use allocation model applied to Jambi Province, Indonesia.

In tropical regions, shifting from forests and traditional agroforestry to intensive plantations generates conflicts between human welfare (farmers' demands and societal needs) and environmental protection. Achieving sustainability in this transformation will inevitably involve trade-offs between multiple ecological and socioeconomic functions. To address these trade-offs, our study used a new methodological approach allowing the identification of transformation scenarios, including theoretical landscape compositions that satisfy multiple ecological functions (i.e., structural complexity, microclimatic conditions, organic carbon in plant biomass, soil organic carbon and nutrient leaching losses), and farmers needs (i.e., labor and input requirements, total income to land, and return to land and labor) while accounting for the uncertain provision of these functions and having an actual potential for adoption by farmers. We combined a robust, multi-objective optimization approach with an iterative search algorithm allowing the identification of ecological and socioeconomic functions that best explain current land-use decisions. The model then optimized the theoretical land-use composition that satisfied multiple ecological and socioeconomic functions. Between these ends, we simulated transformation scenarios reflecting the transition from current land-use composition towards a normative multifunctional optimum. These transformation scenarios involve increasing the number of optimized socioeconomic or ecological functions, leading to higher functional richness (i.e., number of functions). We applied this method to smallholder farms in the Jambi Province, Indonesia, where traditional rubber agroforestry, rubber plantations, and oil palm plantations are the main land-use systems. Given the currently practiced land-use systems, our study revealed short-term returns to land as the principal factor in explaining current land-use decisions. Fostering an alternative composition that satisfies additional socioeconomic functions would require minor changes ("low-hanging fruits"). However, satisfying even a single ecological indicator (e.g., reduction of nutrient leaching losses) would demand substantial changes in the current land-use composition ("moonshot"). This would inevitably lead to a profit decline, underscoring the need for incentives if the societal goal is to establish multifunctional agricultural landscapes. With many oil palm plantations nearing the end of their production cycles in the Jambi province, there is a unique window of opportunity to transform agricultural landscapes.

Land-use change shifts and magnifies seasonal variations of the decomposer system in lowland tropical landscapes.

Deforestation and agricultural expansion in the tropics affect local and regional climatic conditions, leading to synergistic negative impacts on land ecosystems. Climatic changes manifest in increased inter- and intraseasonal variations and frequency of extreme climatic events (i.e., droughts and floods), which have evident consequences for aboveground biodiversity. However, until today, there have been no studies on how land use affects seasonal variations below ground in tropical ecosystems, which may be more buffered against climatic variation. Here, we analyzed seasonal variations in soil parameters, basal respiration, microbial communities, and abundances of soil invertebrates along with microclimatic conditions in rainforest and monocultures of oil palm and rubber in Sumatra, Indonesia. About 75% (20 out of 26) of the measured litter and soil, microbial, and animal parameters varied with season, with seasonal changes in 50% of the parameters depending on land use. Land use affected seasonal variations in microbial indicators associated with carbon availability and cycling rate. The magnitude of seasonal variations in microbial parameters in the soil of monocultures was almost 40% higher than in the soil of rainforest. Measured parameters were associated with short-term climatic conditions (3-day period air humidity) in plantations, but not in rainforest, confirming a reduced soil buffering ability in plantations. Overall, our findings suggest that land use temporally shifts and increases the magnitude of seasonal variations of the belowground ecosystem compartment, with microbial communities responding most strongly. The increased seasonal variations in soil biota in plantations likely translate into more pronounced fluctuations in essential ecosystem functions such as nutrient cycling and carbon sequestration, and these ramifications ultimately may compromise the stability of tropical ecosystems in the long term. As the observed seasonal dynamics is likely to increase with both local and global climate change, these shifts need closer attention for the long-term sustainable management of plantation systems in the tropics.

Dataset on microclimate and drone-based thermal patterns within an oil palm agroforestry system.

Microclimate and Land Surface Temperature (LST) are important analytical variables used to understand complex oil palm agroforestry systems and their effects on biodiversity and ecosystem functions. In order to examine experimental effects of tree species richness (0, 1, 2, 3 or 6), plot size (25 m2, 100 m2, 400 m2, 1600 m2) and stand structural complexity on microclimate and Land Surface Temperature, related data were collected following a strict design. The experiment was carried out in the Jambi province, in Sumatra (Indonesia), as part of the collaborative project EFForTS [Ecological and Socioeconomic Functions of Tropical Lowland Rainforest Transformation Systems]. Microclimate data collected using miniaturized data loggers combined with drone-based thermal data were considered within an oil palm plantation enriched with six target tree species. The timeframe considered for data analysis was 20th September 2017 to 26th September 2017. The experiment data can be used for comparison with data from conventional oil palm agroforestry systems in the tropics. They can more specifically be used as reference to assess microclimate and Land Surface Temperature patterns within similar agroforestry systems.

Measured greenhouse gas budgets challenge emission savings from palm-oil biodiesel.

The potential of palm-oil biofuels to reduce greenhouse gas (GHG) emissions compared with fossil fuels is increasingly questioned. So far, no measurement-based GHG budgets were available, and plantation age was ignored in Life Cycle Analyses (LCA). Here, we conduct LCA based on measured CO2, CH4 and N2O fluxes in young and mature Indonesian oil palm plantations. CO2 dominates the on-site GHG budgets. The young plantation is a carbon source (1012 ± 51 gC m-2 yr-1), the mature plantation a sink (-754 ± 38 gC m-2 yr-1). LCA considering the measured fluxes shows higher GHG emissions for palm-oil biodiesel than traditional LCA assuming carbon neutrality. Plantation rotation-cycle extension and earlier-yielding varieties potentially decrease GHG emissions. Due to the high emissions associated with forest conversion to oil palm, our results indicate that only biodiesel from second rotation-cycle plantations or plantations established on degraded land has the potential for pronounced GHG emission savings.

Spatiotemporal variability in surface energy balance across tundra, snow and ice in Greenland.

The surface energy balance (SEB) is essential for understanding the coupled cryosphere-atmosphere system in the Arctic. In this study, we investigate the spatiotemporal variability in SEB across tundra, snow and ice. During the snow-free period, the main energy sink for ice sites is surface melt. For tundra, energy is used for sensible and latent heat flux and soil heat flux leading to permafrost thaw. Longer snow-free period increases melting of the Greenland Ice Sheet and glaciers and may promote tundra permafrost thaw. During winter, clouds have a warming effect across surface types whereas during summer clouds have a cooling effect over tundra and a warming effect over ice, reflecting the spatial variation in albedo. The complex interactions between factors affecting SEB across surface types remain a challenge for understanding current and future conditions. Extended monitoring activities coupled with modelling efforts are essential for assessing the impact of warming in the Arctic.