Grazing leads to the reduction of biomass and plays a critical role in land degradation in arid and semiarid lands. However, the indirect effects of grazing on the ecosystem, e.g., the effect on seed dispersal, have not been well understood. In this study, we built an agent-based model (ABM) to simulate how grazing intensity affects the seed dispersal of elm trees, one of the native vegetation species of temperate woodlands in semiarid lands. The simulated results from the ABM and observed data from the real world were compared to assess the accuracy and validity of the ABM.

The 2019 fire crisis in Amazonia dominated global news and triggered fundamental questions about the possible causes behind it. Here we performed an in-depth investigation of the drivers of active fire anomalies in the Brazilian Amazon biome. We assessed a 2003–2019 time-series of active fires, deforestation, and water deficit and evaluated potential drivers of active fire occurrence in 2019, at the biome-scale, state level, and local level. Our results revealed abnormally high monthly fire counts in 2019 for the states of Acre, Amazonas, and Roraima.

Human activities and environmental deterioration have resulted in land use transition (LUT), which seriously affects the ecosystem service value (ESV) of its region. Therefore, relevant policy measures are urgently needed. Nevertheless, research on the relationships between LUTs and ESVs from the overall watershed scale is lacking. Thus, the geo-information Tupu method was applied to analyze the dynamic patterns of LUT based on land use data from 1990, 2000, 2010, and 2018 of the Yellow River Basin (YRB).

Case studies offer rich insight into the way knowledge is gathered, understood, and applied (or not) in parks and conservation contexts. This study aims to understand how knowledge and information have been used to inform decision-making about human-wildlife co-existence—specifically what knowledge has informed decisions related to grizzly bear management in the Kananaskis Valley. Focus groups of decision-makers involved in the valley’s bear program painted a rich account of decision-making since the late 1970s that was coded thematically.

Farm abandonment and over-extensification trends in less-favored livestock breeding areas in the Mediterranean have led to socio-environmental issues that are difficult to assess and address, due to the characteristics of these areas (e.g., poor data availability and reliability). In a study case that presents many of the characteristics common to these areas, we combine qualitative and quantitative approaches to assess (i) the relationship between livestock production and land-cover change and (ii) the drivers of farmer decisions, concerning the types of livestock they breed.

The amount of habitat in a landscape is an important metric for evaluating the effects of land cover on biodiversity, yet it fails to capture complex temporal dimensions of resource availability that could be consequential for species population dynamics. Here, we use a spatially-explicit predator–prey metapopulation model to test the effect of different spatiotemporal resource patterns on insect predators and their prey. We examined population responses in model landscapes that varied in both the amount and temporal variability of basal vegetation.

The rain gardens at Bryggen in Bergen, Western Norway, is designed to collect, retain, and infiltrate surface rainfall runoff water, recharge the groundwater, and replenish soil moisture. The hydraulic infiltration capacity of the Sustainable Drainage System (SuDS), here rain gardens, has been tested with small-scale and full-scale infiltration tests. Results show that infiltration capacity meets the requirement and is more than sufficient for infiltration in a cold climate.

Green infrastructure is a strategically planned network of natural and semi-natural areas, including green and blue spaces and other ecosystems, designed and managed to deliver a wide range of ecosystem services at various scales. Apart from the ecological functions, green infrastructure, as a planning tool, contributes to social and economic benefits, leading to the achievement of sustainable, resilient, inclusive and competitive urban areas.

Many of the world’s agricultural frontiers are located in the tropics. Crop and cattle expansion in these regions has a strong environmental impact. This paper examines land use and land cover transformations in Brazil, where large swaths of natural vegetation are being removed to make way for agricultural production. In Brazil, the land use dynamics are of great interest regarding the country’s sustainable development and climate mitigation actions, leading to the formulation and implantation of public policies and supply chain interventions to reduce deforestation.

With 15–20% of Indonesian oil palms located, without a legal basis and permits, within the forest zone (‘Kawasan hutan’), international concerns regarding deforestation affect the totality of Indonesian palm oil export. ‘Forest zone oil palm’ (FZ-OP) is a substantive issue that requires analysis and policy change.

The nexus of food, energy, and water systems (FEWS) has become a salient research topic, as well as a pressing societal and policy challenge. Computational modeling is a key tool in addressing these challenges, and FEWS modeling as a subfield is now established. However, social dimensions of FEWS nexus issues, such as individual or social learning, technology adoption decisions, and adaptive behaviors, remain relatively underdeveloped in FEWS modeling and research.

Soil organic carbon (SOC) is an important indicator of soil quality and directly determines soil fertility. Hence, understanding its spatial distribution and controlling factors is necessary for efficient and sustainable soil nutrient management. In this study, machine learning algorithms including artificial neural network (ANN), support vector machine (SVM), cubist regression, random forests (RF), and multiple linear regression (MLR) were chosen for advancing the prediction of SOC.