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Global scientific partnerships should generate and share knowledge equitably, but too often exploit research partners in lower-income countries, while disproportionately benefitting those in higher-income countries. Here, I outline my suggestions for more-equitable partnerships.

A fire probability map is an important tool for landscape management, providing better identification of areas prone to fires and helping optimize the allocation of limited resources for fire prevention, control, and management. In this study, the random forest machine learning algorithm was applied to model the probability of fire occurrence in the Colombian-Venezuelan plains (llanos) ecoregion in South America. Information on burned areas was collected using Moderate Resolution Imaging Spectroradiometer (MODIS) Product MCD64A1 for the period 2015–2019. We also used spatial information of related factors that were grouped into four levels of information: topography, human presence, vegetation, and climate-related variables. The model had an accuracy of 94%, which indicates the performance of the model was excellent. The cartography generated from the model can be used as base information in the context of fire management in the region, to identify areas for prioritizing efforts and attention. The probability of occurrence zoning results indicates that the very low category covers the largest area (28.2%), followed by low (23.2%), very high (17.6%), moderate (17.2%), and high (13.8%).

Fire is a natural agent with a paramount role in ecosystem functioning and biodiversity maintenance. Still, it can also act as a negative force against many ecosystems. Despite some knowledge of the interactions of fire and vegetation, there is no clear understanding of how different components of fire regimes (i.e., severity, history, or frequency) influence known patterns of animal communities. Therefore, we performed a systematic review on the global responses of arthropods, birds, mammals, reptiles, and amphibians to different fire regimes. Specifically, we focused on assessing how fire severity, history, and frequency modulate the effect of fire on the richness and abundance of faunal communities. We conducted a systematic review of 566 papers retrieved from the Scopus database. We also scrutinized all the documents included in the meta-analysis of Pastro et al. (Pastro et al. Glob Ecol Biogeogr 23:1146–1156, 2014). Our selection criteria excluded studies without data on species richness or abundance. We also excluded studies without adequate controls and those without information about the fire regime of the study zone. After careful examination, we used data from 162 studies to perform a quantitative meta-analysis. From the 162 studies meeting our selection criteria, nearly 60% of the studies are from North America, 25% from Australia, 11% from Europe, and 4% from the tropics. According to the ecological role of fire, 90% of the studies were carried out in fire-dependent ecosystems (i.e., conifer forests, natural savannas, pastures). Finally, 40% of the studies analyzed birds, 22% mammals, and 20% arthropods. The meta-analysis of the available evidence indicates that fire history is an important modulator of animal richness and abundance. Whether negative or positive, animal responses depended on the time since the last fire event. Considering that short-term studies may not capture such a long-term effect on fauna, this translates to more challenges at implementing fire management strategies. Whether or not we can anticipate the impact of the fire will then depend on future efforts to implement long-term research.

The Amazon biome, spanning nine countries, has one of the highest rates of deforestation worldwide. This deforestation contributes to biodiversity loss, climate change, the spread of infectious diseases, and damage to rural and indigenous livelihoods. Hundreds of articles have been published on the topic of deforestation across Amazonia, yet there has been no recent synthesis of deforestation drivers and deforestation-control policy effectiveness in the region. Here we undertook the first systematic review of papers published between 2000 and 2021 that have causally linked proximate and underlying drivers and policies to deforestation outcomes in Amazonia. In the 155 articles that met our inclusion criteria, we find that causal research is concentrated in Brazil, and to a lesser degree Peru, Ecuador, and Bolivia. There has been little study of the Guianas, Venezuela or Colombia. Large- and small-scale agriculture linked to improved market access and high agricultural prices are frequently researched underlying drivers of deforestation across the heavily researched regions. In the Guianas research focuses on mining with little focus on underlying causes. Research on infrastructure expansion, mining, and oil extraction and on technological, sociocultural, and institutional factors remains sparse. Many public and private policies have been found to be effective in controlling deforestation across the biome, with protected areas and public policies standing out as particularly successful in slowing deforestation vis-à-vis supply chain approaches. Frontier age, land tenure, and policy interactions are key moderating factors affecting the outcomes of different underlying causes and policies. Our findings indicate a greater need for research on (i) additional deforestation drivers beyond agriculture and economic factors, (ii) the complex interactions between different drivers and deforestation control policies, (iii) causes underlying deforestation in low or new deforestation areas, and (iv) the dynamics between Amazonian subregions and countries. Understanding the extent and diversity of deforestation drivers and effectiveness of existing deforestation mitigation policies across Amazonia is a necessary first step toward designing policies to further reduce deforestation in the biome.

Climate change and unsustainable land-use practices are causing megafires in South America. Here we call for rigorous scientific coordination and global cooperation to claim back landscape planning, mitigate fire risk and foster resilience in the region.

Many studies have identified drivers of deforestation throughout the tropics and, in most cases, have recognised differences in the level of threat. However, only a few have also looked at the temporal and spatial dynamics by which those drivers act, which is critical for assessing the conservation of biodiversity as well as for landscape planning. In this study, we analyse land cover change between 2000 and 2009 in north-western Colombian Amazonia to identify the interactions between the use of fire, cultivation of illicit crops and establishment of pastures, and their impacts on the loss of forest in the region. Yearly analyses were undertaken at randomly selected sample areas to quantify the average areas of transition of land cover types under different landscape compositions: forest-dominated mosaics, pasture mosaics, fire mosaics, and illicit crop mosaics. Our results indicate that despite the fact that forest areas were well-preserved, deforestation occurred at a low annual rate (0.06%). Conversion to pasture was the main factor responsible for forest loss (the area of pastures tripled within forest mosaics over 8 years), and this process was independent of the landscape matrix in which the forests were located. In fire mosaics, burning is a common tool for forest clearing and conversion to pasture. Thus, forests in fire mosaics were highly disturbed and frequently transformed from primary to secondary forests. The use of fire for illicit cropping was not detected, partly due to the small size of common illicit crops. Forest regeneration from pastures and secondary vegetation was observed in areas with large amounts of natural forest. Overall, assuming the continuation of the observed pasture conversion trend and the use of forest fire, we suggest that our results should be incorporated into a spatially explicit and integrated decision support tool to target and focus land-planning activities and policies.

The ability to measure the ecological effects of understory fire in the Amazon on a landscape scale remains a frontier in remote sensing. The Global Ecosystem Dynamics Investigation’s (GEDI) LiDAR data have been widely suggested as a critical new tool in this field. In this paper, we use the GEDI Simulator to quantify the nuanced effects of understory fire in the Amazon, and assess the ability of on-orbit GEDI data to do the same. While numerous ecological studies have used simulated GEDI data, on-orbit constraint may limit ecological inference. This is the first study that we are aware of that directly compares methods using simulated and on-orbit GEDI data. Simulated GEDI data showed that fire effects varied nonlinearly through the canopy and then moved upward with time since burn. Given that fire effects peaked in the mid-canopy and were often on the scale of 2 to 3 m in height difference, it is unlikely that on-orbit GEDI data will have the sensitivity to detect these same changes.

Armed conflict, and its end, can have powerful effects on natural resources, but the influence of war and peace on highly biodiverse tropical forests remains disputed. We found a sixfold increase in fires in protected areas across biodiversity hotspots following guerrilla demobilization in Colombia, and a 52% increase in the probability of per-pixel deforestation within parks for 2018. Peace requires urgent shifts to include real-time forest monitoring, expand programmes to pay for ecosystem services at the frontier, integrate demobilized armed groups as staff of protected areas, and establish a domestic market for frontier deforestation permits. Signing of peace agreements in Colombia has brought armed conflict to an end, but has also led to encroachment, development and deforestation of previously disputed forested areas, as revealed by remote sensing data.

Mineral licks are faunal attractors, whose distribution determines the structure and composition of Amazonian landscapes and the way they are used by wildlife and traditional communities. Research on the distribution of mineral licks is scarce, limiting the possibility of using them in conservation beyond local scales. Using the species distribution modeling framework, we predicted the distribution of suitable conditions for mineral licks in the Northwest Amazon, compiling localities from academic and traditional sources and using environmental variables associated with geology, geomorphology, edaphology, topography, and hydrology. Best models, selected according to evaluation metrics incorporated in the ENMeval “R” package, showed to be robust and predict sectors with different areas, but similar distributions. Suitable areas covered up to 14.6% of the study area and confirmed the association of mineral licks with the drainage system. The erosive capacities of the rivers and their roles in terms of sediment deposition allowed the generation of ideal conditions for the expression of mineral licks in past and present riparian zones. Closeness to salt deposits and the seacoast was also important, giving information about the underground and aboveground mineral availability, crucial aspects for mineral lick formation. Considering the extension and distribution of our predictions, we proposed its use as input for other spatial modeling exercises, for example, as part of a complex resistance matrix to evaluate ecological connectivity or as criteria to prioritize sectors for restoration in the Colombian Amazon, where it is imperative to consolidate functional networks to prevent isolation between the Amazon and Andes regions.