Rangelands across the globe increasingly face anthropogenic disturbances, including improper grazing practices, maladaptive fire regimes, and climate change, leading to the emergence of novel ecosystems. These systems are stable ecological states that cannot feasibly be reverted to previous preferred conditions. We focus on a specific type of novel ecosystem characterized by monocultures of competitive introduced forage species. While not always regarded as “degraded landscapes,” these ecosystems can have dramatically altered spatiotemporal distributions of resources, leading to resource deficits that severely diminish the ability of rangelands to support livestock and wildlife and to provide other critical ecosystem services. For instance, seasonal protein deficiencies in large herbivores, insufficient vegetation structure for wildlife cover, and diminished soil function are all manifestations of these resource deficits. In this paper, we explore the use of strategic islands of functional and diverse perennial plants as a landscape intervention for both long-term ecosystem restoration and near-term mitigation of resource deficits to optimize livestock or wildlife production. Current agricultural approaches, such as protein supplementation, tend to address resource deficits symptomatically rather than holistically, while diversity-oriented ecological restoration approaches do not always prioritize continued production or plant–animal interactions within working landscapes. We introduce the islands of diversity (IOD) approach which aims to restore spatial and/or temporal distribution of critical resources, including nutrients and medicinal secondary compounds, plant structure, adaptive soil conditions, and vegetative propagules, while potentially improving the health of grazers and nutrient density of resulting animal products. We explore the current challenges and opportunities associated with a case study in which IODs are used to improve rangeland condition, livestock production, and wildlife habitat. Within this case study we explore the use of emerging technologies such as remote sensing and drone imaging for IOD site selection, virtual fencing for the management of grazing within IOD, and the influence of IOD on animal movement and distribution. Ultimately, IODs are a promising landscape intervention for addressing resource deficits affecting livestock, wildlife, and ecosystem processes in rangeland monocultures.

Abstract. Rainfall gauge networks in Sub-Saharan Africa are inadequate for assessing Sahelian agricultural drought, hence satellite-based estimates of precipitation and vegetation indices such as the Normalized Difference Vegetation Index (NDVI) provide the main source of information for early warning systems. While it is common practice to translate precipitation into estimates of soil moisture, it is difficult to quantitatively compare precipitation and soil moisture estimates with variations in NDVI. In the context of agricultural drought early warning, this study quantitatively compares rainfall, soil moisture and NDVI using a simple statistical model to translate NDVI values into estimates of soil moisture. The model was calibrated using in-situ soil moisture observations from southwest Niger, and then used to estimate root zone soil moisture across the African Sahel from 2001–2012. We then used these NDVI-soil moisture estimates (NSM) to quantify agricultural drought, and compared our results with a precipitation-based estimate of soil moisture (the Antecedent Precipitation Index, API), calibrated to the same in-situ soil moisture observations. We also used in-situ soil moisture observations in Mali and Kenya to assess performance in other water-limited locations in sub Saharan Africa. The separate estimates of soil moisture were highly correlated across the semi-arid, West and Central African Sahel, where annual rainfall exhibits a uni-modal regime. We also found that seasonal API and NDVI-soil moisture showed high rank correlation with a crop water balance model, capturing known agricultural drought years in Niger, indicating that this new estimate of soil moisture can contribute to operational drought monitoring. In-situ soil moisture observations from Kenya highlighted how the rainfall-driven API needs to be recalibrated in locations with multiple rainy seasons (e.g., Ethiopia, Kenya, and Somalia). Our soil moisture estimates from NDVI, on the other hand, performed well in Niger, Mali and Kenya. This suggests that the NDVI-soil moisture relationship may be more robust across rainfall regimes than the API because the relationship between NDVI and plant available water is less reliant on local characteristics (e.g., infiltration, runoff, evaporation) than the relationship between rainfall and soil moisture.