Search Results (110)

Elephants exhibit remarkable cognitive and social abilities, which are integral to their navigation, resource acquisition, and responses to environmental challenges such as climate change and human–wildlife conflict. Their capacity to acquire, recall, and utilise spatial information enables them to traverse large, fragmented landscapes, locate essential resources, and mitigate risks. While older elephants, particularly matriarchs, are often regarded as repositories of ecological knowledge, the mechanisms by which younger individuals acquire this information remain uncertain. Existing research suggests that elephants follow established movement patterns, yet direct evidence of intergenerational knowledge transfer is limited. This review synthesises current literature on elephant navigation and decision-making, exploring how their behavioural strategies contribute to resilience amid increasing anthropogenic pressures. Empirical studies indicate that elephants integrate environmental and social cues when selecting routes, accessing water, and avoiding human-dominated areas. However, the extent to which these behaviours arise from individual memory, social learning, or passive exposure to experienced individuals requires further investigation. Additionally, elephants function as ecosystem engineers, shaping landscapes, maintaining biodiversity, and contributing to climate resilience. Recent research highlights that elephants’ ecological functions can indeed contribute to climate resilience, though the mechanisms are complex and context-dependent. In tropical forests, forest elephants (Loxodonta cyclotis) disproportionately disperse large-seeded, high-carbon-density tree species, which contribute significantly to above-ground carbon storage. Forest elephants can improve tropical forest carbon storage by 7%, as these elephants enhance the relative abundance of slow-growing, high-biomass trees through selective browsing and seed dispersal. In savannah ecosystems, elephants facilitate the turnover of woody vegetation and maintain grassland structure, which can increase albedo and promote carbon sequestration in soil through enhanced grass productivity and fire dynamics. However, the ecological benefits of such behaviours depend on population density and landscape context. While bulldozing vegetation may appear destructive, these behaviours often mimic natural disturbance regimes, promoting biodiversity and landscape heterogeneity, key components of climate-resilient ecosystems. Unlike anthropogenic clearing, elephant-led habitat modification is part of a long-evolved ecological process that supports nutrient cycling and seedling recruitment. Therefore, promoting connectivity through wildlife corridors supports not only elephant movement but also ecosystem functions that enhance resilience to climate variability. Future research should prioritise quantifying the net carbon impact of elephant movement and browsing in different biomes to further clarify their role in mitigating climate change. Conservation strategies informed by their movement patterns, such as wildlife corridors, conflict-reducing infrastructure, and habitat restoration, may enhance human–elephant coexistence while preserving their ecological roles. Protecting older individuals, who may retain critical environmental knowledge, is essential for sustaining elephant populations and the ecosystems they influence. Advancing research on elephant navigation and decision-making can provide valuable insights for biodiversity conservation and conflict mitigation efforts. Full article

In Mediterranean regions, fires are a key ecological factor, altering soil properties, biodiversity, and landscape dynamics. Post-fire recovery varies based on vegetation type, fire severity, and climate conditions. However, the specific relationship between post-fire vegetation recovery and soil temperature regimes remains poorly investigated. This study investigates this relationship in an area severely affected by a megafire. Three plots (unburned, low-severity fire, and high-severity fire) were monitored for species richness, vegetation cover and height, and soil temperature, with data from 2021 to 2024 analyzed. Vegetation surveys revealed that fire severity influenced species richness and vegetation cover and height. Particularly, burned areas showed a higher proliferation of pioneer and herbaceous species three years post-fire. Moreover, after the same period, burned areas showed consistently higher soil temperatures than the unburned ones, reflecting altered microclimatic conditions. This could be because the presence of more pioneer and herbaceous species is insufficient to mitigate the air temperatures. Our results show the impact of fires on soil and vegetation, highlighting the critical role of vegetation in modeling soil temperature. However, long-term monitoring is necessary to assess the real effect of vegetation type on soil temperature. Full article

Wildfires are a recurrent and intensifying natural hazard in Mediterranean regions like Greece, driven by prolonged heatwaves, evolving climatic conditions, and human activities. This study leverages Sentinel-2 satellite imagery and Copernicus geospatial data to assess four early-season wildfire events during May and June 2024, which collectively affected 43.44 km². Burn severity, land cover, and tree cover density were analyzed to evaluate the spatial and environmental impacts of these fires. Validation against Copernicus Emergency Management Service (CEMS) data yielded an overall accuracy of 95.79%, confirming the reliability of the methodology. The Achaia-Ilia wildfire, spanning 40.55 km², exhibited the highest severity, with 26.93% classified as moderate to high severity. Smaller fires, such as Katsimidi (0.66 km²) and Stamata (1.41 km²), revealed the influence of vegetation type and density on fire dynamics, with Stamata’s sparse tree cover mitigating fire spread. The findings highlight the utility of remote sensing technologies for wildfire monitoring, and underscore the need for tailored management strategies, from vegetation control to urban planning, to enhance ecosystem resilience and mitigate wildfire risks in Mediterranean landscapes. Full article

Co-varying disturbance and environmental gradients can shape vegetation dynamics and increase the diversity of plant communities and their features. Pinyon–juniper woodlands are widespread in semi-arid climates of western North America, encompassing extensive environmental gradients, and a knowledge gap is how the diversity in features of these communities changes across co-varying gradients in fire history and soil. In pinyon–juniper communities spanning soil parent materials (basalt, limestone) and recent fire histories (0–4 prescribed fires or managed wildfires and 5–43 years since fire) in Grand Canyon-Parashant National Monument (Arizona, USA), we examined variation at 25 sites in three categories of plant community features including fuels, tree structure, and understory vegetation. Based on ordinations, canonical correlation analysis, and permutation tests, plant community features varied primarily with the number of fires, soil coarseness and chemistry, and additionally with tree structure for understory vegetation. Fire and soil variables accounted for 33% of the variance in fuels and tree structure, and together with tree structure, 56% of the variance in understories. The cover of the non-native annual Bromus tectorum was higher where fires had occurred more recently. In turn, B. tectorum was positively associated with the percentage of dead trees and negatively associated with native forb species richness. Based on a dendroecological analysis of 127 Pinus monophylla and Juniperus osteosperma trees, only 18% of trees presently around our study sites originated before the 1870s (Euro-American settlement) and <2% originated before the 1820s. Increasing contemporary fire activity facilitated by the National Park Service since the 1980s corresponded with increasing tree mortality and open-structured stands, apparently more closely resembling pre-settlement conditions. Using physical geography, such as soil parent material, as a landscape template shows promise for (i) incorporating diversity in long-term community change serving as a baseline for vegetation management, (ii) customizing applying treatments to unique conditions on different soil types, and (iii) benchmarking monitoring metrics of vegetation management effectiveness to levels scaled to biophysical variation across the landscape. Full article

In the fire-prone tropical savanna landscapes of northern South America, forest edge effects significantly shape tree structural integrity and functional traits, with implications for ecosystem resilience, carbon storage, and biodiversity. This study examines how the edge effect, intensified by fire, affects species dominance, forest structure, and functional trait distributions in this region. Using non-metric multidimensional scaling (NMDS) and generalized additive mixed models (GAMMs), we analyzed changes in species abundance and structural variables (biomass, basal area, tree height, and wood density), as well as leaf (leaf thickness, leaf moisture, leaf dry matter content (LDMC), and specific leaf area (SLA)) and stem (bark and stem thickness and stem-specific density) traits across edge-to-interior gradients. The key findings indicate significant reductions in tree height (F = 19.27, p < 0.01), basal area (F = 6.52, p < 0.01), and biomass (F = 5.44, p < 0.01) near the edges. Leaf moisture (F = 11.8, p < 0.01) and specific leaf area (SLA, F = 7.02, p < 0.01) increased at the edges, reflecting microenvironmental gradients, with heightened fire sensitivity seen in traits like bark thickness (F = 11.88, p < 0.01). Fire-affected areas displayed intensified adaptive trait shifts, suggesting a compounded resilience but potential functional convergence, limiting adaptive capacity under climate stressors. These findings emphasize the ecological significance of edge–fire interactions, advocating conservation strategies to enhance structural and trait diversity for ecosystem stability. Our study underscores the need for targeted management to bolster resilience and biodiversity within these dynamic landscapes as climate pressures intensify. Full article

The protected areas (PA) of the Democratic Republic of the Congo serve as vital carbon reservoirs and are crucial for biodiversity conservation and climate regulation. Despite their significance, these areas face escalating rates of deforestation and degradation, often poorly understood at the local level. This study focuses on the dynamics of tropical moist forest (TMF) and the relative importance of the driving factors in the landscape of Kahuzi-Biega National Park (KBNP), one of the country’s prominent PAs. Analyzing annual TMF dynamics from 1990 to 2022 using data classified by Vancutsem and his collaborators in 2021 from Landsat imagery alongside spatial datasets of deforestation and degradation drivers, we employed a comprehensive analytical approach. This included meshing, multi-scale analysis, principal component analysis, zoning, multiple linear regression, and relative importance analysis through bootstrapping. The findings indicate that the grid size considered does not significantly influence TMF dynamics in the KBNP landscape (p-value = 0.67, α = 0.05). The edge and outer zones experienced substantial dynamics, with approximately 30% forest cover loss in both areas, contrasting with the relatively stable TMF cover (~100%) in the inner zone. Fire emerged as the most influential driver, explaining TMF dynamics with a relative importance of approximately 55%, 30%, and 23% in the inner, edge, and outer zones, respectively. This study underscores KBNP’s efficacy in curbing TMF loss but highlights the need for enhanced protection around its periphery. Management efforts should prioritize sustainable land use practices, livelihood improvement, and the establishment of an officially recognized buffer zone. Full article

High-severity wildfires create heterogeneous patterns of vegetation across burned landscapes. While these spatial patterns are well-documented, less is known about the short- and long-term effects of large-scale high-severity wildfires on insect community assemblages and dynamics. Ants are bottom-up indicators of ecosystem health and function that are sensitive to disturbance and fill a variety of roles in their ecosystems, including altering soil chemistry, dispersing seeds, and serving as a key food resource for many species, including the federally endangered Jemez Mountain salamander (Plethodon neomexicanus). We examined the post-fire effects of the 2011 Las Conchas Wildfire on ant communities in the Valles Caldera National Preserve (Sandoval County, New Mexico, USA). We collected ants via pitfall traps in replicated burned and unburned sites across three habitats: ponderosa pine forests, mixed-conifer forests, and montane grassland. We analyzed trends in species richness, abundance, recruitment, loss, turnover, and composition over five sequential years of post-fire succession (2011–2015). Ant foraging assemblage was influenced by burn presence, season of sampling, and macrohabitat. We also found strong seasonal trends and decreases over time since fire in ant species richness and ant abundance. However, habitat and seasonal effects may be a stronger predictor of ant species richness than the presence of fire or post-fire successional patterns. Full article

Pinus albicaulis (whitebark pine) is a keystone species, providing food and habitat to wildlife, in high-elevation ecological communities. In recent years, this important species has been negatively impacted by changes in fire regimes, increased Dendroctonus ponderosae (mountain pine beetle) outbreaks associated with human landscape and climate modification, and the continued impact of the non-native Cronartium ribicola (white pine blister rust). This research investigates changes in fire occurrence, the establishment of Pinus albicaulis, and fuel availability at a high-elevation site in the Sawtooth National Recreation Area, Idaho, USA. Charcoal and pollen analyses were used to reconstruct fire and vegetation patterns for Phyllis Lake, Idaho, USA, over the past ~8200 cal y BP. We found that significant fire episodes occurred when the pollen accumulation rates (PARs) indicated more arboreal fuel availability, and we identified that Pinus albicaulis became well established at the site ~7200 cal y BP. The high-elevation nature of Phyllis Lake (2800 m) makes this record unique, as there are not many paleorecords at this high elevation from the Northern Rocky Mountains, USA. Additional high-elevation sites in Pinus albicaulis habitats will provide critical insight into the long-term dynamics of this threatened species. Full article

Wildfires are a critical driver of landscape transformation on Earth, representing a dynamic and ephemeral process that poses challenges for accurate early detection. To address this challenge, researchers have increasingly turned to deep learning techniques, which have demonstrated remarkable potential in enhancing the performance of wildfire detection systems. This paper provides a comprehensive review of fire detection using deep learning, spanning from 1990 to 2023. This study employed a comprehensive approach, combining bibliometric analysis, qualitative and quantitative methods, and systematic review techniques to examine the advancements in fire detection using deep learning in remote sensing. It unveils key trends in publication patterns, author collaborations, and thematic focuses, emphasizing the remarkable growth in fire detection using deep learning in remote sensing (FDDL) research, especially from the 2010s onward, fueled by advancements in computational power and remote sensing technologies. The review identifies “Remote Sensing” as the primary platform for FDDL research dissemination and highlights the field’s collaborative nature, with an average of 5.02 authors per paper. The co-occurrence network analysis reveals diverse research themes, spanning technical approaches and practical applications, with significant contributions from China, the United States, South Korea, Brazil, and Australia. Highly cited papers are explored, revealing their substantial influence on the field’s research focus. The analysis underscores the practical implications of integrating high-quality input data and advanced deep-learning techniques with remote sensing for effective fire detection. It provides actionable recommendations for future research, emphasizing interdisciplinary and international collaboration to propel FDDL technologies and applications. The study’s conclusions highlight the growing significance of FDDL technologies and the necessity for ongoing advancements in computational and remote sensing methodologies. The practical takeaway is clear: future research should prioritize enhancing the synergy between deep learning techniques and remote sensing technologies to develop more efficient and accurate fire detection systems, ultimately fostering groundbreaking innovations. Full article

Wildfires have a significant influence on ecosystems globally, shaping vegetation, biodiversity, landscapes, soil properties, and other ecosystem processes. Despite extensive research on different aspects of wildfires, the edges of burned areas remain understudied, even though they involve complex dynamics. In this study, we analyzed the post-fire vegetation recovery across the edges of a large wildfire in a Mediterranean area. The investigations were focused on patches of woodlands that, in a previous study, showed a normalized burn ratio (NBR) decline one year after the fire. Field vegetation surveys were carried out in areas characterized by different NBR recovery rates and in areas outside the burned area as controls. Five hypotheses were tested, identifying delayed tree mortality as a key factor linked to NBR decline, particularly in low-severity fire zones in proximity to the fire edges. Delayed mortality, observed predominantly near the edges, may also affect unburned or less severely burned patches within the main fire perimeter, highlighting the need for ongoing monitoring. As these areas play a crucial role in the post-fire succession and vegetation dynamics, understanding the second-order effects of a fire is imperative for effective ecosystem management. This study underscores the importance of the long-term assessment of fire impacts, emphasizing the necessity of field surveys alongside remote sensing. Continued observation is essential to elucidate the enduring impacts of wildfires and to facilitate informed restoration strategies. Full article

The Land Use Change Alert (LUCA) dataset was developed for effective and timely monitoring of global forest changes that are mostly associated with human activities. Near- real-time changes of forest land use are mapped at 0.05 ha minimum mapping unit for all forest types across the Earth’s ecoregions, every two weeks. LUCA is based on Sentinel-1 cloud penetrating synthetic aperture radar (SAR) observations to circumvent limitations of optical imagery from pervasive cloud cover over forested areas globally, and especially in the tropics. The methodology is based on a combination of time-series change detection and machine learning analytics to achieve high accuracy of alerts across all ecoregions and landscapes globally with an average area-adjusted users and producers accuracy of 83% and 63%, respectively. The bi-weekly global alert maps capture forest clearing associated with deforestation and industrial timber harvesting, along with forest degradation associated with selective logging, fragmentation, fire, and roads. The product was developed and released publicly through Google Earth Engine to allow for the rapid assessment of land use change activities, quantifying patterns and processes driving forest change and dynamics across forest ecoregions. LUCA is designed to help monitor a variety of emission reduction programs at the local to regional scales and play a key role in implementing regulations on deforestation-free products. Full article

Recently, as global climate change and local disturbances such as wildfires continue, long- and short-term changes in the high-latitude vegetation systems have been observed in various studies. Although remote sensing technology using optical satellites has been widely used in understanding vegetation dynamics in high-latitude areas, there has been limited understanding of various landscape changes at different spatiotemporal scales, their mutual relationships, and overall long-term landscape changes. The objective of this study is to devise a change monitoring strategy that can effectively observe landscape changes at different spatiotemporal scales in the boreal ecosystems from temporally sparse time series remote sensing data. We presented a new post-classification-based change analysis scheme and applied it to time series Landsat data for the central Yakutian study area. Spectral variability between time series data has been a major problem in the analysis of changes that make it difficult to distinguish long- and short-term land cover changes from seasonal growth activities. To address this issue effectively, two ideas in the time series classification, such as the stepwise classification and the lateral stacking strategies were implemented in the classification process. The proposed classification results showed consistently higher overall accuracies of more than 90% obtained in all classes throughout the study period. The temporal classification results revealed the distinct spatial and temporal patterns of the land cover changes in central Yakutia. The spatiotemporal distribution of the short-term class illustrated that the ecosystem disturbance caused by fire could be affected by local thermal and hydrological conditions of the active layer as well as climatic conditions. On the other hand, the long-term class changes revealed land cover trajectories that could not be explained by monotonic increase or decrease. To characterize the long-term land cover change patterns, we applied a piecewise linear model with two line segments to areal class changes. During the former half of the study period, which corresponds to the 2000s, the areal expansion of lakes on the eastern Lena River terrace was the dominant feature of the land cover change. On the other hand, the land cover changes in the latter half of the study period, which corresponds to the 2010s, exhibited that lake area decreased, particularly in the thermokarst lowlands close to the Lena and Aldan rivers. In this area, significant forest decline can also be identified during the 2010s. Full article

Ecological records from before and after the creation of natural parks are valuable for informing conservation and management but are often unavailable. High-resolution paleoecological studies may bridge the gap and provide the required information. This paper presents a 20th-century subdecadal reconstruction of vegetation and landscape dynamics in a national park of the Pyrenean highlands. The park lands had traditionally been used for cultivation, extensive grazing, forest exploitation, and hydroelectricity generation following the damming of numerous glacial lakes. A significant finding is that forests have dominated the landscape, with negligible changes in composition, and only experienced fluctuations in forest cover, influenced by both climatic and anthropogenic factors. The creation of the park (1955) and the initial restrictions on forest exploitation did not significantly affect vegetation cover or composition. Major forest expansion did not occur until several decades later, 1980, when the park was enlarged and forest exploitation was further restricted. This expansion peaked in the 1990s, coinciding with a warming trend and a decrease in fire incidence, before declining due to warmer and drier climates. This decline was coeval with the ongoing global forest dieback and may be exacerbated by the predicted global warming in this century, which could also increase fire incidence due to dead-wood accumulation. Currently, the main threats are global warming/drying, fire, and tourism intensification. Similar high-resolution paleoecological records in protected areas are globally scarce and would be capable in providing the long-term ecological scope required to properly understand forest dynamics and optimize conservation measures. Full article

Wildfires represent a significant threat to both ecosystems and human assets in Mediterranean countries, where fire occurrence is frequent and often devastating. Accurate assessments of the initial fire severity are required for management and mitigation efforts of the negative impacts of fire. Evapotranspiration (ET) is a crucial hydrological process that links vegetation health and water availability, making it a valuable indicator for understanding fire dynamics and ecosystem recovery after wildfires. This study uses the Mapping Evapotranspiration at High Resolution with Internalized Calibration (eeMETRIC) and Operational Simplified Surface Energy Balance (SSEBop) ET models based on Landsat imagery to estimate fire severity in five large forest fires that occurred in Spain and Portugal in 2022 from two perspectives: uni- and bi-temporal (post/pre-fire ratio). Using-fine-spatial resolution ET is particularly relevant for heterogeneous Mediterranean landscapes with different vegetation types and water availability. ET was significantly affected by fire severity according to eeMETRIC (F > 431.35; p-value < 0.001) and SSEBop (F > 373.83; p-value < 0.001) metrics, with reductions of 61.46% and 63.92%, respectively, after the wildfire event. A Random Forest machine learning algorithm was used to predict fire severity. We achieved higher accuracy (0.60 < Kappa < 0.67) when employing both ET models (eeMETRIC and SSEBop) as predictors compared to utilizing the conventional differenced Normalized Burn Ratio (dNBR) index, which resulted in a Kappa value of 0.46. We conclude that both fine resolution ET models are valid to be used as indicators of fire severity in Mediterranean countries. This research highlights the importance of Landsat-based ET models as accurate tools to improve the initial analysis of fire severity in Mediterranean countries. Full article

Risks associated with severe wildfire are growing in forest landscapes due to interactions among climate change, fuel accumulation from fire suppression, an expanding wildland–urban interface, and additional factors. People, infrastructure, ecosystem services, and forest health all face varying degrees of risk. The spatial distributions of the many social and ecological factors that influence wildfire, its impacts, and management responses are an important landscape-level context for managing risks and fostering resilient lands and communities. Decision-support tools that integrate these varied distributions can provide a holistic and readily interpreted characterization of landscapes, helping fire management decision making be appropriate, efficient, and effective. Firescapes—landscape types defined in relation to fire, its drivers, and its effects as a socioecological system—fill this role, providing a way to organize and interpret spatial variation along multiple relevant dimensions. We describe a quantitative approach for classifying and mapping firescapes for decision support, using the southeastern United States as a case study. We worked with regional partners to compile relevant large-scale datasets and identify 73 variables for analysis. We used factor analysis to reduce the data to eight factors with intuitive interpretations relevant to fire dynamics, fire history, forest characteristics, climate, conservation and ecosystem service values, social and ecological landscape properties, and social vulnerabilities. We then used cluster analysis on the factors to generate quantitative landscape classes, which we interpreted as nine distinctive firescape classes. The firescapes provide a broad-scale socioecological information context for wildfire risk management and planning. The analytical approach can accommodate different data types at a variety of scales, incorporate new monitoring data as they are available, and can be used under data-driven scenarios to assess possible consequences of future change. The resulting firescape maps can provide decision support to forest managers, planners, and other stakeholders, informing appropriate strategies to manage fire and associated risks, build community and forest resilience to fire, and improve conservation outcomes. Full article