Urbanization is a major driver of land use change and biodiversity decline. While most of the ongoing and future urbanization hotspots are located in the Global South, the impact of urban expansion on agricultural biodiversity and associated functions and services in these regions has widely been neglected. Additionally, most studies assess biodiversity responses at local scale (α‐diversity), however, ecosystem functioning is strongly determined by compositional and functional turnover of communities (β‐diversity) at regional scales. We investigated taxonomic and functional β‐diversity of farmland birds across three seasons on 36 vegetable farms spread along a continuous urbanization gradient in Bangalore, a South Indian megacity. Increasing amount of grey area in the farm surroundings was the dominant driver affecting β‐diversity and resulting in taxonomic and functional homogenization of farmland bird communities. Functional diversity losses were higher than expected from species declines (i.e., urbanization acts as an environmental filter), with particular losses of functionally important groups such as insectivores of crop pests. Moreover, urbanization reduced functional redundancy of bird communities, which may further weaken ecosystems resilience to future perturbations. Our study underscores urbanization as a major driver of taxonomic and functional homogenization of species communities in agricultural systems, potentially threatening crucial ecosystem services for food production.

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.

Many Indonesian forests have been cleared and replaced by fast-growing cash crops (e.g., oil palm and rubber plantations), altering the vegetation structure of entire regions. Complex vegetation structure provides habitat niches to a large number of native species. Airborne laser scanning (ALS) can provide detailed three-dimensional information on vegetation structure. Here, we investigate the potential of ALS metrics to highlight differences across a gradient of land-use management intensities in Sumatra, Indonesia. We focused on tropical rainforests, jungle rubber, rubber plantations, oil palm plantations and transitional lands. Twenty-two ALS metrics were extracted from 183 plots. Analysis included a principal component analysis (PCA), analysis of variance (ANOVAs) and random forest (RF) characterization of the land use/land cover (LULC). Results from the PCA indicated that a greater number of canopy gaps are associated with oil palm plantations, while a taller stand height and higher vegetation structural metrics were linked with rainforest and jungle rubber. A clear separation in metrics performance between forest (including rainforest and jungle rubber) and oil palm was evident from the metrics pairwise comparison, with rubber plantations and transitional land behaving similar to forests (rainforest and jungle rubber) and oil palm plantations, according to different metrics. Lastly, two RF models were carried out: one using all five land uses (5LU), and one using four, merging jungle rubber with rainforest (4LU). The 5LU model resulted in a lower overall accuracy (51.1%) due to mismatches between jungle rubber and forest, while the 4LU model resulted in a higher accuracy (72.2%). Our results show the potential of ALS metrics to characterize different LULCs, which can be used to track changes in land use and their effect on ecosystem functioning, biodiversity and climate.

Context: The agricultural landscape in many low- and middle-income countries is characterized by smallholder management systems, often dependent on ecosystem services, such as pollination by wild pollinator populations. Increased adoption of modern inputs (e.g., agrochemicals) may threaten pollinators and smallholder crop production. Objective: We aimed to identify the link between the use of agrochemicals and wild bee populations in Southern India, while explicitly considering the effects of temporal and spatial scaling. Methods: For our empirical analysis, we combined data from pan trap samples and a farm management survey of 127 agricultural plots around Bangalore, India. We implemented a Poisson generalized linear model to analyze factors that influence bee abundance and richness with a particular focus on the present, past, and neighboring management decisions of farmers with respect to chemical fertilizers, pesticides, and irrigation. Results: Our results suggest that agricultural intensification is associated with a decrease in the abundance and richness of wild bees in our study areas. Both time and space play an important role in explaining farm-bee interactions. We find statistically significant negative spillovers from pesticide use. Smallholders’ use of chemical fertilizers and irrigation on their own plots significantly decreases the abundance of bees. Intensive past management reduces both bee abundance and richness. Conclusions: Our results suggest that cooperative behavior among farmers and/or the regulation of agrochemical use is crucial to moderate spatial spillovers of farm management decisions. Furthermore, a rotation of extensive and intensive management could mitigate negative effects.