The concept of ecosystem services (ES) provides a potentially useful tool for decision‐making in natural area management. Provisioning and regulating ES often occur in “bundles” that are cohesive because of coprovisioning or codependence. We asked whether individual preferences for cultural benefits also define service bundles. Data from a large survey of visitor preferences ( n = 3,131 respondents) from all 19 South African National Parks indicated five bundles of cultural ecosystem services: (1) “natural history,” (2) “recreation,” (3) “sense of place,” (4) “safari experiences,” and (5) “outdoor lifestyle.” Trade‐offs and synergies between bundles of services depended on the ecosystem providing them and on alignment between demand for services and the supply of particular service bundles in specific ecosystems. Our results show that identifying demand for multiple services can both help us to understand why people visit and value protected areas, and better inform the management choices that influence service provision.

The UN Sustainable Development Goals (SDGs) represent a universal agenda that nations have committed to achieving by 2030. The challenge is substantial, with no country excelling across all SDGs. Using global UN data, we assess patterns of positive and negative correlations between indicators of SDG status and progress. For nearly 70% of SDG indicators, status is positively associated with GDP/capita. Progress on SDG indicators, however, occurs in both poorer and wealthier countries. When GDP/capita is controlled for, positive associations remain between health, environment and energy usage indicators. Economic growth is negatively associated with changes in some health and environment indicators. For SDGs targets to be achieved, major opportunities and conflicts will need to be identified, prioritized and acted upon.

Ecosystems degradation, and consequently biodiversity loss, has severe impacts on people around the world. The Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) is one of the international initiatives that have emerged to inform policy makers and aid decisions to prevent further global biodiversity loss, focusing on the interdependence between natural systems and human culture. IPBES promotes the use of scenarios and modelling approaches as a fundamental tool to advance the understanding of the relationships between drivers of change, Nature’s Contributions to People (NCP), and social systems. Local-scale case studies with a system approach demonstrating how current knowledge can be used to inform decision-making are still scarce. Here, we present a comprehensive conceptual model and a series of four scenarios under different policies for shea tree species management, as a case-study of applying systems thinking and the NCP concept to a local-scale socio-ecological system. We first characterized the central processes, NCP, drivers and pressures affecting the shea tree system, to investigate the impacts of the multiple uses of the shea tree species on the system as a whole. We then described potential policy options, developed four scenarios, and evaluated them by a Bayesian Belief Network (BBN). We predicted qualitative outcomes of the proposed scenarios: Business-as-usual (BAU), “Conservation and fair trade”, “Agroforestry and fair trade” and “Industrial development”. We found that the scenarios focussing on conservation, fair trade and agroforestry, can improve the conservation status of shea trees, and enhance wellbeing in the local communities. In this case study, we demonstrate that the development of a comprehensive conceptual model at a local scale can be a useful exercise to identify opportunities for effective policy strategies and social innovation. The shea tree case study can provide an example for modelling non-timber forest products in other regions around the world that face similar drivers and pressures. Species for which this model could be adapted include Central and South American species such as the Brazilian nut (Bertholletia excelsa), cocoa (Theobroma cacao), andiroba (Carapa guianensis), açai (Euterpe oleracea) and the wax palm (Ceroxylon quindiuense). The model and workflow applied here may thus be used to understand similar socio-ecological systems with local and international economic value across the Neotropical region.

The UN Sustainable Development Goals (SDGs) include economic, social and environmental dimensions of human development and make explicit commitments to all of life on Earth. Evidence of continuing global biodiversity loss has, at the same time, led to a succession of internationally agreed conservation targets. With multiple targets (even within one policy realm, e.g. the CBD Aichi Targets for biodiversity), it is possible for different indicators to respond in the same direction, in opposite directions or to show no particular relationship. When considering the different sectors of the SDGs, there are many possible relationships among indicators that have been widely discussed, but rarely analysed in detail. Here, we present a comparative cross-national analysis exploring temporally integrated linkages between human development indicators and wildlife conservation trends. The results suggest that in lower income countries there are negative relationships between measures of human population growth and bird and mammal population abundance trends outside protected areas. The results also suggest a positive relationship between economic growth and wildlife population trends in lower income countries. We stress, however, the need for future research to further explore the relationships between economic growth and natural resource-based imports. Our results highlight a clear potential for compatibility of the conservation and development agendas and support the need for further integration among sustainable development strategies. A free Plain Language Summary can be found within the Supporting Information of this article.

Palm oil accounts for approximately 50% of global vegetable oil production, and trends in consumption have driven large-scale expansion of oil palm ( Elaeis guineensis ) plantations in Southeast Asia. This expansion has led to deforestation and other socio-environmental concerns that challenge consumer goods companies to meet no deforestation and sustainability commitments. In support of these commitments and supply chain traceability, we seek to improve on the current industry standard sourcing model for ascribing social and environmental risks to particular actors. Using passive geolocational traceability data ( n = 3,355,437 cellular pings) and machine learning models, we evaluate the industry standard sourcing model, and we predict with high accuracy the undisclosed sourcing domains for 1,570 Indonesian and Malaysian palm oil mills on the Universal Mill List (as of November 2021). In combination with the World Wide Fund for Nature – Netherlands’ Forest Fore-sight, we use our predicted sourcing domains to provide an illustrative example of the proportional allocation of future deforestation, carbon loss, and biodiversity risk to relevant actors, permitting targeted outreach, contract negotiation, and mitigation of large-scale resource degradation. This example depends on a subset of model predictions in the absence of disclosed traceability data. The utilization of additional predictions or disclosed traceability data would influence and improve the results.