Detecting cocoa plantations in Côte d'Ivoire and Ghana and their implications on protected areas.

Côte d'Ivoire and Ghana are the largest producers of cocoa in the world. In recent decades the cultivation of this crop has led to the loss of vast tracts of forest areas in both countries. Efficient and accurate methods for remotely identifying cocoa plantations are essential to the implementation of sustainable cocoa practices and for the periodic and effective monitoring of forests. In this study, a method for cocoa plantation identification was developed based on a multi-temporal stack of Sentinel-1 and Sentinel-2 images and a multi-feature Random Forest (RF) algorithm. The Normalized Difference Vegetation Index (NDVI) and second-order texture features were assessed for their importance in an RF classification, and their optimal combination was used as input variables for the RF model to identify cocoa plantations in both countries. The RF model-based cocoa map achieved 82.89% producer's and 62.22% user's accuracy, detecting 3.69 million hectares (Mha) and 2.15 Mha of cocoa plantations for Côte d'Ivoire and Ghana, respectively. The results demonstrate that a combination of an RF model and multi-feature classification can distinguish cocoa plantations from other land cover/use, effectively reducing feature dimensions and improving classification efficiency. The results also highlight that cocoa farms largely encroach into protected areas (PAs), as 20% of the detected cocoa plantation area is located in PAs and almost 70% of the PAs in the study area house cocoa plantations.

Mapping the diversity of land uses following deforestation across Africa.

African forest are increasingly in decline as a result of land-use conversion due to human activities. However, a consistent and detailed characterization and mapping of land-use change that results in forest loss is not available at the spatial-temporal resolution and thematic levels suitable for decision-making at the local and regional scales; so far they have only been provided on coarser scales and restricted to humid forests. Here we present the first high-resolution (5 m) and continental-scale mapping of land use following deforestation in Africa, which covers an estimated 13.85% of the global forest area, including humid and dry forests. We use reference data for 15 different land-use types from 30 countries and implement an active learning framework to train a deep learning model for predicting land-use following deforestation with an F1-score of [Formula: see text] for the whole of Africa. Our results show that the causes of forest loss vary by region. In general, small-scale cropland is the dominant driver of forest loss in Africa, with hotspots in Madagascar and DRC. In addition, commodity crops such as cacao, oil palm, and rubber are the dominant drivers of forest loss in the humid forests of western and central Africa, forming an "arc of commodity crops" in that region. At the same time, the hotspots for cashew are found to increasingly dominate in the dry forests of both western and south-eastern Africa, while larger hotspots for large-scale croplands were found in Nigeria and Zambia. The increased expansion of cacao, cashew, oil palm, rubber, and large-scale croplands observed in humid and dry forests of western and south-eastern Africa suggests they are vulnerable to future land-use changes by commodity crops, thus creating challenges for achieving the zero deforestation supply chains, support REDD+ initiatives, and towards sustainable development goals.

Rainfall variability patterns in Nigeria during the rainy season.

To enhance the physical understanding of the circulation patterns associated with rainfall variations in Nigeria, we spatially decomposed rainfall during the rainy season and uncovered the asymmetric atmospheric circulation patterns driving wet and dry regimes in specific parts of Nigeria. Also, we examined linear trends in rainfall and the circulation patterns driving the trends. Our result shows that during the analysis period (1979-2022), northern part of Nigeria has coherent rainfall anomaly that is coupled with rainfall variations over the Sahel (Pearson correlation coefficient (r) is 0.55), and sea surface temperature anomalies (SSTa) in the global oceans (r = [Formula: see text]). The negative phases of the Pacific Decadal Oscillation, North Atlantic Oscillation, and the North Pacific Oscillation; and the positive phases of the Atlantic Multidecadal Oscillation and the Pacific warm pool are associated with rainfall increase over the northern part of Nigeria. Owing to the increasing trend in SSTa over the Mediterranean and the adjacent oceans, implying the weakening of dry northerly winds penetrating northern Nigeria, the rainfall trend is significantly positive in the northern part of Nigeria during the rainy season-with an increase of about 2-4 mm/year, especially during August. The circulation patterns associated with rainfall formation at the western and southeastern parts of Nigeria are shown to be associated with SSTa over the tropical Atlantic Ocean, south coast of Nigeria (r = [Formula: see text]). Moreover, rainfall shows a negative trend, with a decrease of about 5 mm/year, in the southeastern parts of Nigeria, which can be linked to the warming trend over the Gulf of Guinea.

Addressing indirect sourcing in zero deforestation commodity supply chains.

The trade in agricultural commodities is a backbone of the global economy but is a major cause of negative social and environmental impacts, not least deforestation. Commodity traders are key actors in efforts to eliminate deforestation-they are active in the regions where commodities are produced and represent a "pinch point" in global trade that provides a powerful lever for change. However, the procurement strategies of traders remain opaque. Here, we catalog traders' sourcing across four sectors with high rates of commodity-driven deforestation: South American soy, cocoa from Côte d'Ivoire, Indonesian palm oil, and Brazilian live cattle exports. We show that traders often source more than 40% of commodities "indirectly" via local intermediaries and that indirect sourcing is a major blind spot for sustainable sourcing initiatives. To eliminate deforestation, indirect sourcing must be included in sectoral initiatives, and landscape or jurisdictional approaches, which internalize indirect sourcing, must be scaled up.