The ecological impact of rapid environmental change will depend on the resistance of key ecosystems processes, which may be promoted by species that exert strong control over local environmental conditions. Recent theoretical work suggests that macrodetritivores increase the resistance of African savanna ecosystems to changing climatic conditions, but experimental evidence is lacking. We examined the effect of large fungus-growing termites and other non-fungus-growing macrodetritivores on decomposition rates empirically with strong spatiotemporal variability in rainfall and temperature. Non-fungus-growing larger macrodetritivores (earthworms, woodlice, millipedes) promoted decomposition rates relative to microbes and small soil fauna (+34%) but both groups reduced their activities with decreasing rainfall. However, fungus-growing termites increased decomposition rates strongest (+123%) under the most water-limited conditions, making overall decomposition rates mostly independent from rainfall. We conclude that fungus-growing termites are of special importance in decoupling decomposition rates from spatiotemporal variability in rainfall due to the buffered environment they create within their extended phenotype (mounds), that allows decomposition to continue when abiotic conditions outside are less favorable. This points at a wider class of possibly important ecological processes, where soil-plant-animal interactions decouple ecosystem processes from large-scale climatic gradients. This may strongly alter predictions from current climate change models.

The humid highlands of the Galapagos are the islands’ most biologically productive regions and a key habitat for endemic animal and plant species. These areas are crucial for the region’s food security and for the control of invasive plants, but little is known about the spatial distribution of its land cover. We generated a baseline high-resolution land cover map of the agricultural zones and their surrounding protected areas. We combined the high spatial resolution of PlanetScope images with the high spectral resolution of Sentinel-2 images in an object-based classification using a RandomForest algorithm. We used images collected with an unmanned aerial vehicle (UAV) to verify and validate our classified map. Despite the astounding diversity and heterogeneity of the highland landscape, our classification yielded useful results (overall Kappa: 0.7, R2: 0.69) and revealed that across all four inhabited islands, invasive plants cover the largest fraction (28.5%) of the agricultural area, followed by pastures (22.3%), native vegetation (18.6%), food crops (18.3%), and mixed forest and pioneer plants (11.6%). Our results are consistent with historical trajectories of colonization and abandonment of the highlands. The produced dataset is designed to suit the needs of practitioners of both conservation and agriculture and aims to foster collaboration between the two areas.

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Agriculture is cultural heritage, and studies of agricultural spaces and practices help this heritage to be valued and protected. In the Galapagos Islands, little focus has been placed on local agricultural practices and agroforestry, despite their increasing importance for food security and invasive species management. This article discusses the possibilities for unoccupied aerial vehicle (UAV) high-resolution imagery in examining agricultural and agroforestry spaces, techniques, and practices. It describes and assesses an UAV-assisted participatory methodology for on-farm qualitative research that aims to investigate the visible and invisible features of farming practices. An analysis of the types of responses elicited by different methods of interviews with Galapagos farmers demonstrates how incorporating UAV data affects what we took away from the interview, and how the perceived relationship between farmer and land is reflected. Specifically, we find that when interacting with orthomosaics created from UAV images of their farms, farmers’ responses reveal a greater focus on management strategies at larger spatial and temporal scales. UAV imagery thus supports studies of agricultural heritage not only by recording agricultural spaces but also by revealing agrarian knowledge and practices.

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