Rosa Reyes-Riveros

Aim: Dominant trees govern the structure and functioning of temperate forests, and their decline following disturbance often signals reduced resilience and diminished capacity for ecosystem recovery. Disturbances affecting these species have been widely documented in isolation, yet their combined and interacting effects remain poorly synthesized, particularly outside the Northern Hemisphere. Location: Southern cone of South America. Taxon: Nothofagus pumilio (Poepp. & Endl.) Krasser (Magnoliopsida: Nothoafaceae). Methods: We review the effects of individual and combined disturbances on dominant tree species of temperate forests, with a particular focus on Nothofagus pumilio , the dominant tree species of southern South American temperate forests. Using a two‐scale literature review, we first conducted a restricted global search to identify disturbance categories documented in temperate forests and their reported effects on dominant tree species. This served as a framework for a subsequent in‐depth analysis of how those disturbances affect N. pumilio forests across their distribution. We searched Web of Science and Scopus for empirical studies explicitly addressing disturbance impacts on dominant tree species and classified articles by disturbance type. Results: Climatic disturbances, wildfires, biological disturbances, and logging are recurrently documented in temperate forests, and strongly affect N. pumilio throughout its range. Interactions among multiple disturbances represent an increasingly important driver of N. pumilio forest degradation. Climate change amplifies fire activity, triggering cascading effects when combined with pressures such as grazing and biological invasions. N. pumilio exhibits variable and sometimes contrasting responses to the same disturbance depending on local conditions. Main Conclusions: We conclude that multiple, interacting disturbances can jeopardize the persistence of even dominant, plastic species. Forest dynamics models and management strategies should integrate these complex interactions to better anticipate the feedbacks and thresholds that may endanger tree populations and to guide effective mitigation measures. Promoting mixed‐species stands through active restoration, reducing anthropogenic pressures, and controlling invasive species are essential strategies for maintaining ecosystem resilience under global change.

This study developed and tested a neighborhood-scale framework that integrates unmanned aerial vehicle (UAV)-based multispectral mapping and georeferenced socioeconomic data to identify inequities in urban green infrastructure and translate them into an operational prioritization tool for inclusive planning. Using object-based image analysis, impervious surfaces, low vegetation, and woody vegetation (trees and shrubs) were mapped across 33 Neighborhood Units in Temuco, Chile, and landscape metrics describing dominance, edge, isolation/connectivity, and diversity were derived. Socioeconomic conditions were summarized through Principal Component Analysis, and their relationships with vegetation metrics were evaluated using Generalized Additive Models. The results revealed strongly nonlinear and metric-specific associations, with the most robust relationships observed for woody-structure metrics, particularly total woody edge and built-environment isolation, whereas landscape diversity showed weaker but still significant dependence on resource-access gradients. To support inclusive planning, a dimensionless Green Infrastructure Prioritization Index (GIPI) was computed by combining standardized green deficit and standardized social vulnerability with equal weights. GIPI values ranged from 0.318 to 0.740 (median = 0.528), identifying 11 high-priority units characterized by higher social vulnerability and less favorable woody structure, including lower largest-patch dominance and greater isolation. Sensitivity analyses varying the deficit weight from 0.30 to 0.70 showed that 10 of the 11 high-priority units remained in the same class in at least 80% of weighting scenarios, indicating a stable priority set. Further classification of high-priority units according to dominant deficit type supported a staged intervention strategy, in which woody canopy is first increased in deficit nodes and subsequently reinforced through corridor-oriented greening to improve structural connectivity. These findings demonstrate the value of coupling fine-scale vegetation mapping with socioeconomic gradients to support more equitable urban green infrastructure planning.

Urban vegetation plays a vital role in mitigating the impacts of urbanization, improving biodiversity, and providing key ecosystem services. However, the spatial distribution, ecological dynamics, and social implications of urban vegetation remain insufficiently understood, particularly in underrepresented regions. This systematic review aims to synthesize global research trends in very-high-resolution (VHR) remote sensing of urban vegetation between 2000 and 2024. A total of 123 peer-reviewed empirical studies were analyzed using bibliometric and thematic approaches, focusing on the spatial resolution (<10 m), sensor type, research objectives, and geographic distribution. The findings reveal a predominance of biophysical studies (72%) over social-focused studies (28%), with major thematic clusters related to urban climate, vegetation structure, and technological applications such as UAVs and machine learning. The research is heavily concentrated in the Global North, particularly China and the United States, while regions like Latin America and Africa remain underrepresented. This review identifies three critical gaps: (1) limited research in the Global South, (2) insufficient integration of ecological and social dimensions, and (3) underuse of advanced technologies such as hyperspectral imaging and AI-driven analysis. Addressing these gaps is essential for promoting equitable, technology-informed urban planning. This review provides a comprehensive overview of the state of the field and offers directions for future interdisciplinary research in urban remote sensing.

The Nahuelbuta Mountain Range in the south-central zone of Chile is a biodiversity hotspot that has undergone intense land use/cover transformation. This study analyses two decades of land use change (1999–2018) in the watersheds of the Lebu and Leiva rivers. The magnitude and spatial configuration of these changes were assessed using detailed spatial information, transition matrices, and landscape metrics. The results show that between 1999 and 2018, temperate native forest decreased by 30.3% in Lebu and 22.8% in Leiva, being replaced mainly by exotic forest plantations, which increased by 20.2% and 13.5%, respectively. The spatiotemporal analysis revealed losses concentrated in the lowland and middle zones of both watersheds, with persistence of temperate native forest in higher elevations. Landscape metrics showed an increase in diversity (SIDI: Lebu 0.41–0.65; Leiva 0.29–0.57) and a decrease in aggregation (AI: 92–86%; 95–90%). At the class level, the temperate native forest presented greater fragmentation, with a reduction in size and proximity, an increase in density, and more irregular shapes. In contrast, exotic forest plantations increased in size and proximity, with a slight decrease in density and greater complexity of form, consolidating their expansion and spatial continuity in both watersheds. These findings emphasise the need to implement territorial planning and conservation strategies adapted to the Nahuelbuta context, through native forest management plans that promote ecological conservation, the recovery of degraded landscapes, and the strengthening of ecosystem services, thus contributing to the well-being of local communities and long-term environmental sustainability.

Distinguishing between natural forests from exotic tree plantations is essential to get an accurate picture of the world’s state of forests. Most exotic tree plantations support lower levels of biodiversity and have less potential for ecosystem services supply than natural forests, and differencing them is still a challenge using standard tools. We use a novel approach in south-central of Chile to differentiate tree cover dynamics among natural forests and exotic tree plantations. Chile has one of the world’s most competitive forestry industry and the region is a global biodiversity hotspot. Our collaborative visual interpretation method combined a global database of tree cover change, remote sensing from high-resolution satellite images and expert knowledge. By distinguishing exotic tree plantation and natural forest loss, we fit spatially explicit models to estimate tree-cover loss across 40 millions of ha between 2000 and 2016. We were able to distinguish natural forests from exotic tree plantations with an overall accuracy of 99% and predicted forest loss. Total tree cover loss was continuous over time, and the disaggregation revealed that 1 549 909 ha of tree plantations were lost (mean = 96 869 ha year⁻¹), while 206 142 ha corresponded to natural forest loss (mean = 12 884 ha year⁻¹). Mostly of tree plantations lost returned to be plantation (51%). Natural forests were converted mainly (75%) to transitional land covers (e.g. shrubland, bare land, grassland), and an important proportion of these may finish as tree plantation. This replacement may undermine objectives of increasedcarbon storage and biodiversity. Tree planting as a solution has gained increased attention in recen years with ambitious commitments to mitigate the effects of climate change. However, negative outcomes for the environment could result if strategies incentivize the replacement of natural forests into other land covers. Initiatives to reduce carbon emissions should encourage differentiating natural forests from exotic tree plantations and pay more attention on protecting and managing sustainably the former.