Complex relationships between soybean trade destination and tropical deforestation.

Over the last few years, understanding of the effects of increasingly interconnected global flows of agricultural commodities on coupled human and natural systems has significantly improved. However, many important factors in environmental change that are influenced by these commodity flows are still not well understood. Here, we present an empirical spatial modelling approach to assess how changes in forest cover are influenced by trade destination. Using data for soybean-producing municipalities in the state of Mato Grosso, Brazil, between 2004 and 2017, we evaluated the relationships between forest cover change and the annual soybean trade destination. Results show that although most of the soybean produced in Mato Grosso during the study period (60%) was destined for international markets, municipalities with greater and more consistent soybean production not destined for international markets during the study period were more strongly associated with deforestation. In these municipalities, soybean production was also significantly correlated with cattle and pasture expansion. These results have important implications for the sustainable management of natural resources in the face of an increasingly interconnected world, while also helping to identify the most suitable locations for implementing policies to reduce deforestation risks.

Balancing food production with climate change mitigation and biodiversity conservation in the Brazilian Amazon.

Climate change mitigation and biodiversity conservation are two major environmental actions that need to be effectively performed this century, alongside ensuring food supply for a growing global human population. These three issues are highly interlinked through land management systems. Thus, major global food production regions located in biodiversity hotpots and with potential for carbon sequestration face trade-offs between these valuable land-based ecosystem services. The state of Mato Grosso in Brazil is one such region, where private lands that have been illegally used for agriculture could be restored to natural vegetation - with potential benefits for climate change mitigation and biodiversity conservation, although with potentially negative effects on food production. To address this challenge, in this study we used a multicriteria nexus modeling approach that considers carbon stocks, priority areas for biodiversity conservation, and the opportunity for food production, to develop scenarios of land allocation that aim to balance the benefits and drawbacks of ecosystem restoration. Results show that forcing landowners to restore their individual lands compromises the potential for a "green land market" throughout the Amazon biome in which private landowners with lower food production capacities (e.g., less connected to markets and infrastructure) would benefit from restoration programs that compensate them for the inclusion of environmental restoration among their economic activities, instead of taking large economic risks to produce more food. We additionally highlight that strategic ecosystem restoration can achieve higher gains in biodiversity and carbon with lower costs of restoration actions and with minimal impacts on agriculture. Analyses like ours demonstrate how scenarios of land allocation that simultaneously address climate mitigation and biodiversity conservation through ecosystem restoration, while also minimizing possible impacts on food production, can be sought to move the world towards a sustainable future.

Unequal ecosystems of global health authorial expertise: Decolonising noncommunicable disease.

The decolonisation agenda is gathering momentum in global health. Within this movement, one domain of analysis has been the ways in which the geographies of scholarly knowledge production (re)produce the inequities of coloniality. Drawing on the example of noncommunicable diseases (NCDs), here we deviate from this and instead examine the authorship of the key global documents that were used to ignite and mobilise the NCD advocacy agenda from 2000 to 2020. In doing so, we reflect on the changing ecosystems of authorial expertise. It shows that while the geographic distribution of expertise has broadened over time, the NCD domain remains a fairly tight and circumscribed network. Importantly this research also shows the complexities of ascribing location to expertise, a finding that speaks back to the decolonisation debate.

Transport cost to port though Brazilian federal roads network: Dataset for years 2000, 2005, 2010 and 2017.

Transport costs can play a significant role in agricultural exports and businesses profitability. It can also influence farmers' decisions regarding cropland expansion, intensification or land abandonment. Thus, transport is useful to take into account when modeling and evaluating land use and cover change related to agriculture production. The dataset described in this article represents the Infrastructure Capital in the work presented by Millington et al. (2021) [1], in which the CRAFTY-Brazil model is used to evaluate the impacts of changing global demand for agricultural products on land use and cover change. This modeling required a transport cost dataset that spanned the model calibration period, was consistent through time and covered the entire study area. The most recent federal road network (for year 2017) obtained in vector format (shapefile) was joined to road section surface status tables for past years (2000, 2005 and 2010) in order to reconstruct the historic road network. Export ports handling agricultural commodities, and their years of operation, were identified. Both datasets were used to derive the relative transport cost to the nearest port for Brazil, for years 2000, 2005, 2010 and 2017.

Connecting Earth observation to high-throughput biodiversity data.

Understandably, given the fast pace of biodiversity loss, there is much interest in using Earth observation technology to track biodiversity, ecosystem functions and ecosystem services. However, because most biodiversity is invisible to Earth observation, indicators based on Earth observation could be misleading and reduce the effectiveness of nature conservation and even unintentionally decrease conservation effort. We describe an approach that combines automated recording devices, high-throughput DNA sequencing and modern ecological modelling to extract much more of the information available in Earth observation data. This approach is achievable now, offering efficient and near-real-time monitoring of management impacts on biodiversity and its functions and services.

Characterizing wildfire regimes in the United States.

Wildfires statistics for the conterminous United States (U.S.) are examined in a spatially and temporally explicit manner. We use a high-resolution data set consisting of 88,916 U.S. Department of Agriculture Forest Service wildfires over the time period 1970-2000 and consider wildfire occurrence as a function of ecoregion (land units classified by climate, vegetation, and topography), ignition source (anthropogenic vs. lightning), and decade. For the conterminous U.S., we (i) find that wildfires exhibit robust frequency-area power-law behavior in 18 different ecoregions; (ii) use normalized power-law exponents to compare the scaling of wildfire-burned areas between ecoregions, finding a systematic change from east to west; (iii) find that wildfires in the eastern third of the U.S. have higher power-law exponents for anthropogenic vs. lightning ignition sources; and (iv) calculate recurrence intervals for wildfires of a given burned area or larger for each ecoregion, allowing for the classification of wildfire regimes for probabilistic hazard estimation in the same vein as is now used for earthquakes.