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Detailed maps of forest structure attributes are crucial for sustainable forest management, conservation, and forest ecosystem science at the landscape level. Mapping the structure of broad heterogeneous forests is challenging, but the integration of extensive field inventory plots with wall-to-wall metrics derived from synthetic aperture radar (SAR) and optical remote sensing offers a potential solution. Our goal was to map forest structure attributes (diameter at breast height, basal area, mean height, dominant height, wood volume and canopy cover) at 30-m resolution across the diverse 463,000 km2 of native forests of Argentina based on SAR Sentinel-1, vegetation metrics from Sentinel-2 and geographic coordinates. We modelled the forest structure attributes based on the latest national forest inventory, generated uncertainty maps, quantified the contribution of the predictors, and compared our height predictions with those from GEDI (Global Ecosystem Dynamics Investigation) and GFCH (Global Forest Canopy Height). We analyzed 3788 forest inventory plots (1000 m2 each) from Argentina's Second Native Forest Inventory (2015–2020) to develop predictive random forest regression models. From Sentinel-1, we included both VV (vertical transmitted and received) and VH (vertical transmitted and horizontal received) polarizations and calculated 1st and 2nd order textures within 3 × 3 pixels to match the size of the inventory plots. For Sentinel-2, we derived EVI (enhanced vegetation index), calculated DHIs (dynamic habitat indices (annual cumulative, minimum and variation) and the EVI median, then generated 1st and 2nd order textures within 3 × 3 pixels of these variables. Our models including metrics from Sentinel-1 and 2, plus latitude and longitude predicted forest structure attributes well with root mean square errors (RMSE) ranging from 23.8% to 70.3%. Mean and dominant height models had notably good performance presenting relatively low RMSE (24

Closing the research-implementation gap is key for advancing biodiversity conservation. One approach is to generate ecologically relevant spatial datasets that integrate easily with existing management plans. Our goal was to identify priority forest conservation areas in Argentina by combining species distributions, human footprint data, and existing forest zoning. We: (i) mapped potential habitat distributions of 70 plant and animal species associated with forests, and of recognized social and ecological importance, (ii) combined the species distributions with human footprint data to identify priority conservation areas, and (iii) evaluated the juxtaposition of our priority conservation areas with current forest management zones. We found that priority conservation areas (i.e., high number of species and low human footprint) are poorly protected by the current zoning scheme. While the Andean-Patagonian region had a substantial portion (57 %) of priority conservation areas in high protection zones, in four other forest regions we evaluated, only 16–37 % of priority areas had high protection levels. Of great concern are the Chaco and Espinal regions, where 36 % and 39 %, respectively, of priority conservation areas are in low protection zones, where conversion to other uses (row crops, livestock) is allowed. Our results provide new spatial information to managers and conservationists highlighting where current forest zoning performs well, and where it may warrant re-evaluation. Overall, our study highlights the value of integrating species distributions and human footprint maps into existing land use plans to guide conservation efforts in data-poor countries, and is an example of a strategy for closing the research-implementation gap.

Conserving the remaining wildest forests is a top priority for conservation, and human footprint maps are a practical way to identify wild areas. However, available global assessments of wild areas are too coarse for land use decisions, especially in countries with high deforestation rates, such as Argentina. Our main goal was to map the human footprint in Argentina's forested areas to improve conservation planning at regional and country levels. Specifically, we quantified the level of human influence on the environment and mapped the wildest native forests (i) across forest regions, and (ii) in the different land-use categories of the National Forest Plan, which is a key policy instrument for conserving the nation's native forests through zoning, and (iii) identified wildest forests that are at risk due to human activities. We analyzed detailed spatial data on settlements, transportation, energy, and land use change, and estimated the areal extent to which these various human activities disrupt natural processes. We defined pixels with human footprint index of zero as wildest areas. We found that a substantial portion (43%) of Argentina's forested area remains wild, which suggests there are opportunities for conservation. However, levels of human influence varied substantially among forest regions, and Atlantic and Chaco forests have the highest levels of human influence. Further, we found that the National Forest Plan does not conserve the wildest forests of the nation, as most (78%) of the wildest native forests are located in zones that allow silvopasture, timber production, and/or forest conversion to crops, thus potentially threatening biodiversity in these areas. Our map of wildest forests is an important, but first, step in identifying wildland forests in Argentina, as available spatial data layers of human activities capture many, but not all, human influences on forests. For instance, small human features, like certain rural roads, trails, and rural se

The role of biodiversity in natural forests is critical as a regulator of ecosystem function, productivity, and provision of ecosystem services. The objective was to analyse the conservation value of Nothofagus forests in Southern Patagonia (Santa Cruz and Tierra del Fuego provinces), Argentina, through integration of maps of potential biodiversity (MPB) and human footprint (HFM), which can help to improve the natural reserve designs through the spatial prioritization of their conservation values. To achieve the, first we determine that the different forest types presented different species assemblage with specific ecological niche requirements which justify differential conservation or management strategies. We used understory plants as proxy, and we selected indicator species of the understory plants for the following analyses. With these species we produce the MPB, and we found that the occurrence of MPB differ from the pattern of HFM according to the different forest types. After that, we identify woodland patches with special values of MPB and low HFM according to the different forest types, and analyzed if the distribution of MPB of the different forest types changed across the current natural protected reserve network, private and public lands. Finally, with these outputs, we propose new methodologies to enhance the current natural reserve network effectiveness. These outputs can be used as a tool to determine new strategies for management and conservation at landscape level in Southern Patagonia.

Understanding human influence on ecosystems and their services is crucial to achieve sustainable development and ensure the conservation of biodiversity. In this context, the human footprint index (HFI) represents the anthropogenic impacts on ecosystems and the natural environment. Our objective was to characterize the HFI in Southern Patagonia (Argentina) across the landscape, qualifying the differences among the main ecological areas and especially the forested landscapes. We also assessed the potential utility of HFI to identify priority conservation areas according to their wilderness quality and potential biodiversity values. We created a HFI map (scores varied from 0 representing high wilderness quality to 1 representing maximum human impact) using variables related to direct (e.g. infrastructure) and indirect (e.g. derived from economic activities) human impacts, including settlements, accessibility, oil industry, and sheep production. HFI varied significantly across the natural landscapes, being lower (0.07−0.11) in remote ecosystems close to the Andes Mountains and higher (0.38−0.40) in southern areas close to the provincial capital city. Forested landscapes presented different impact values, which were directly related to the economical values of the different forest types. We determined that the current protected area network is not equally distributed across the different ecological areas and forest types. Priority conservation areas were also identified using the fragmentation produced by the human impact, the patch size, and the potential biodiversity values. HFI can present high compatibility with other land-use management decision making tools, acting as a complement to the existing tools for conservation planning or management.

Human activities have modified wetlands all over the word. Water control structures that are frequently implemented in these ecosystems to keep lands free of flooding can decrease or degrade habitat for biodiversity. The Paraná River Delta, one of the largest wetlands in Argentina, has recently experienced rapid cattle grazing intensification facilitated by water control structures, resulting in extensive conversion of wetlands to pastures. It is unclear if this loss of wetlands has had a negative impact on the highly diverse bird community. Here, we evaluated the changes in bird assemblages in the Lower Delta of Paraná River after 14 years of cattle grazing intensification. We compared point count data from 1997 to 1999 with data collected in 2012 and 2013 using the same survey methods. We assessed the temporal changes in bird richness and composition using paired permutation tests and multivariate analysis. We related the bird composition to landscape changes to analyse if avian changes were associated with landscape dynamics. We found that after 14 years, the bird community differed greatly. In general, species richness decreased, especially in wet years. We found fewer wetland species in recent surveys; in particular we did not register saffron-cowled blackbird (Xanthopsar flavus), a species listed as globally vulnerable. Changes in bird composition were associated with an increase in bare soil due to land-use changes. Even though inter-annual differences in precipitation and river stage have great effects on the species present in the surveys, the absence of many wetland species in recent wet years, that is when habitat is suitable for them, is most likely due to changes in land cover. Globally, agricultural land use makes inroads into many wetlands, eroding their quality and extent. Maintenance of wetland species requires that conservation efforts focus on these vulnerable ecosystems before full-scale land conversion occurs.