Search Results (247)

Tropical forest restoration has increased in the past decades, with possible advancements given the UN declaration of the “Decade of Ecosystem Restoration”. However, robust assessments to compare ecosystem functions among restored forest stages are essential. We evaluated 13 actively restored forest stands ranging from 3 to 21 years of age and compared measures of forest biodiversity, structure, and ecosystem function to four 70+ year old “reference” stands that serve as restoration “targets” in the study region of the Premontane wet forest of Costa Rica. The restored stands were planted with an average of 13 tree species on abandoned pastures that were fallow for at least two years. Sixteen tree-stand attributes and six ecosystem function estimates were assessed, including: annual biomass (C) accumulation, N-fixation potential, threatened species conservation, and the provision of avian frugivore forage, insect habitat, and insect pollination. Using Principal Component Analysis, linear modeling, and Mahalanobis distance analyses, we learned that planting a diversity of tree species sets the stage for forest recovery at early restoration ages, with an inflection point at 15 years towards older reference forest characteristics and functions. Given that all restoration ages provided tree diversity and some level of ecosystem functions, the value of all restored stands in the landscape is notable. The assessment methods are easily employed, thereby providing an accessible tool to restoration practitioners. Full article

High-Andean grasslands in the Central Andes of Peru are severely degraded by Lepidium meyenii (maca) cultivation, compromising pasture structure and forage availability for sustainable livestock production. A factorial field experiment evaluated restoration timing and pasture-oriented seed mixtures by manipulating resting time after abandonment (0, 1, 2, and 3 years) and restoration treatment (control; Festuca dolichophylla monoculture; full mixture of Dactylis glomerata + Lolium spp. + Trifolium repens + F. dolichophylla; and mixture without F. dolichophylla) across 64 plots. Vegetation was assessed eight months after seeding, and responses were analysed with ordination, PERMANOVA with restricted permutations, PERMDISP, and generalised linear models and mixed-effects models for diversity metrics. Community composition differed significantly among resting times and seed treatments, with resting time explaining the largest proportion of variance (R² = 0.353), followed by treatment (R² = 0.236), while the interaction was significant but smaller (R² = 0.102, p = 0.002). PERMDISP detected significant differences in multivariate dispersion for both Resting Time and Treatment, indicating that compositional differences may reflect both centroid shifts and heterogeneity among groups. Passive recovery and Festuca-only plots showed slower, more variable compositional change, whereas productive mixtures produced clearer, treatment-specific trajectories over time, suggesting possible divergence in community development patterns, rather than providing formal evidence of distinct alternative stable states. Establishment was consistently high for D. glomerata and Lolium spp., supporting rapid ground cover, which may be associated with short-term forage potential, while F. dolichophylla showed chronically low establishment consistent with limited germination performance. The invasive Pennisetum clandestinum was most pronounced under passive recovery and was reduced under seeded mixtures, suggesting a potential competitive suppression effect. Overall, early seeding with productive mixtures appeared to influence community assembly trajectories, while resting time remained the dominant driver of compositional variation, suggesting potential implications for restoration management in maca-degraded landscapes, although outcomes related to sustainable grazing systems were not directly evaluated. Full article

Wearable sensors and remote sensing technologies are rapidly increasing opportunities to measure grazing animal behavior, energetics, and performance in extensive rangeland systems. However, despite significant advances in device capabilities, the livestock sector lacks an ecological framework that connects sensor data to the metabolic processes driving animal growth and efficiency. In this paper, we apply the movement ecology paradigm to grazing beef cattle as a demonstration of how metabolic theory, animal behavior, and landscape heterogeneity interact to influence energy budgets. We first describe the mechanistic relationships among basal metabolism, thermoregulation, activity, and forage intake, highlighting how movement patterns reflect underlying metabolic states. Next, we review key variables measurable through modern sensors, including GPS, accelerometers, rumen temperature boluses, and remote sensing of forage quantity and quality and explain how these data can be integrated into an information system to estimate energy expenditure, resource selection, and physiological stress. Finally, we show how combining movement, behavioral, and landscape data can yield meaningful indicators of performance and health, paving the way for precision livestock management grounded in ecological principles. Integrating metabolic and movement ecology with emerging technologies offers a strong framework for enhancing efficiency, welfare, and sustainability in grazing beef systems. Full article

Mediterranean rural landscapes are globally important biocultural systems in which long-standing low-intensity farming, grazing, terracing, and agroforestry have historically maintained fine-grained habitat mosaics and high vascular-plant diversity. This review adopts a systematic scoping approach focused on farmland abandonment and High Nature Value (HNV) farming, with a search window extending from 1996 to April 2026. Following PRISMA 2020 and PRISMA-ScR principles, the review maps evidence on plant richness, diversity indices, floristic turnover, indicator species, and vegetation trajectories across Mediterranean agricultural and semi-natural systems. The literature shows that abandonment does not produce a single biodiversity outcome. Early abandonment can maintain or temporarily increase local richness through overlap among remnant grassland species, annuals, and colonizing shrubs, whereas prolonged abandonment more often drives shrub encroachment, woody dominance, and losses of open-habitat specialists. By contrast, HNV systems such as extensive grazing, agro-pastoral mosaics, wood pastures, and dehesa/montado-like agroforestry more consistently maintain habitat interfaces, beta diversity, and plant assemblages associated with cultural landscape continuity. The review argues that biodiversity-sensitive policy in the Mediterranean should move beyond the binary of abandonment versus conservation, and instead support landscape-specific combinations of passive succession, targeted grazing, agroforestry renewal, and rural livelihood viability. Full article

Mountain pastoralism in the Pyrenees has undergone profound transformations in recent decades, driven by socio-economic change, rural depopulation, and the adoption of new technologies. This study examines the evolution of shepherding practices in the Jacetania region of the Western Spanish Pyrenees, with a focus on the interplay between technological innovation and the preservation of traditional ecological knowledge (TEK), which includes a detailed understanding of pasture dynamics, animal behavior, and environmental conditions that guide grazing management. Drawing on interviews with experienced shepherds, and participant observation, we compared historical management of the Collarada mountain pasture—previously under continuous human supervision—with its current use under free-grazing conditions monitored via GPS. The results show a shift from continuous human oversight to technology-assisted management, with reduced labor demands, while traditional ecological knowledge remains essential for effective grazing decisions and adaptation to environmental conditions. We argue that combining modern technologies with the experiential knowledge of pastoralists offers the best pathway toward sustaining both the ecological integrity of high-altitude landscapes and the cultural continuity of pastoral traditions. These findings have the potential to generate broader impacts beyond the study area, contributing to improved ecosystem management, supporting rural livelihoods, and informing policy frameworks aimed at sustaining mountain pastoral systems. Full article

Hyperspectral airborne data combined with machine learning has proven effective for characterizing plant nutritional quality. However, terrain, viewing geometry, and illumination can distort spectral signatures, leading to biased models with limited generalizability for large-scale mapping across farms with a heterogeneous landscape. In this study, we developed a framework for mapping pasture quality using airborne hyperspectral imaging while explicitly accounting for in-field acquisition and environmental effects. Nitrogen content (N%) and metabolizable energy (ME) were used as reference indicators across four hill country farms in New Zealand with contrasting environmental and management conditions. Ground truth was obtained using standard laboratory wet chemistry methods and paired with AisaFENIX airborne hyperspectral data, resulting in 1610 spectral samples derived from 161 spatially independent ground plots. Gaussian Process Regression (GPR) and a one-dimensional convolutional neural network (1D-CNN) were trained and evaluated on an independent test dataset. Both models achieved strong predictive performance (R² > 0.8); however, GPR provided more reliable estimates through predictive uncertainty. Using a 95% confidence interval threshold to mask uncertain predictions increased overall performance (R² > 0.9) and consequently improved the reliability of the mapped outputs. This approach enables spatially explicit pasture nutrient assessment to support precision land management for carbon and nitrogen. Full article

This paper explores the relationship between random matrix theory (RMT) and the use of weight conditioning for training deep neural networks by employing an integrated framework. It has been shown that trained neural networks produce singular value distributions that follow universal distributions prescribed by RMT; however, the presence of non-universal outliers in the distribution can contain significant information particular to the task being performed. In addition, this research investigates how the application of diagonal row equilibration as a form of conditioning affects spectral behavior and optimization stability within deep neural networks. The results show that through conditioning, the random bulk of the singular value decomposition (SVD) spectrum is effectively compressed into a narrow band about the value 1, significantly reducing the Marchenko–Pastur bounds. The results also support the claim that weight conditioning retains the informative nature of the spectral outliers. The experimental results show that weight condition numbers (κ(W)) decreased from extremely ill-conditioned regimes of approximately 10³ to 10⁴ to almost 1.0, producing smoother training landscapes, a quicker convergence rate, and an improved ability for gradients to propagate. These results suggest that conditioning weights can be thought of as an implicit spectral regularize linking RMT evidence and concepts to the practical optimization of deep learning methods. Full article

Earthworms are ecosystem engineers that are sensitive to land-use intensification and edaphic conditions, yet their ecology remains poorly understood in transformed semi-arid landscapes. We hypothesized that, in recently colonized agroecosystems, land-use intensity and physicochemical soil conditions jointly filter the earthworm assembly. In the recently irrigated Lower Valley of the Negro River, Patagonia, Argentina, we sampled earthworms and soils across five land uses—riparian reference sites, fruit orchards, pastures, cereal crops, and horticulture plots—in landscapes dominated by Natrargid Ustolls and Fluventic Haplocambids. We found five species, all of which were exotic Lumbricidae, including the first Argentine record for Murchieona minuscula, indicating a recent colonization following human-mediated niche construction that created an ecological island. The earthworm abundance and biomass were highest in permanent and semi-permanent uses and were driven primarily by soil moisture, pH, and particulate organic matter. Crucially, our results reveal that land-use intensity filters communities by restricting the initial colonization rather than through local extinctions. These findings confirm that soil properties mediate the impact of land use on earthworm assemblages. The inclusion of pastures and fruit orchards in the rotations favors the earthworm populations that, despite low diversity, enhance soil functioning and contribute to agricultural sustainability in semi-arid irrigated agroecosystems. Full article

Climate-induced drought and intensifying land-use pressures threaten ecosystem services and agricultural productivity, particularly in regions with distinctive soil and ecological characteristics. Alabama’s Black Belt, defined by its clay-rich soils and shaped by a legacy of plantation agriculture, uneven land tenure, and persistent socioeconomic disadvantage, is increasingly vulnerable to these interacting stressors. This study analyzes long-term (2000–2023) spatiotemporal patterns of Land Use Land Cover (LULC) change and vegetation response to drought to inform sustainable resource management. Multi-temporal Landsat imagery and National Land Cover Database (NLCD) products were used to quantify LULC dynamics. At the same time, vegetation condition and moisture stress were assessed using the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Moisture Index (NDMI). Drought conditions were evaluated using the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI), which incorporates temperature-driven evaporative demand. Results indicate substantial landscape change, including declines in deciduous forest (−17.78%) and pasture/hay (−13.17%), alongside increases in medium-intensity developed land (+20.25%) and evergreen forest (+10.62%). Declining NDVI and NDMI values indicate increasing vegetation stress, particularly during prolonged droughts. Vegetation response exhibited a weak relationship with SPI (R = 0.37) but a stronger association with SPEI (R = 0.59), underscoring the importance of accounting for atmospheric water demand. These findings highlight the growing vulnerability of Black Belt ecosystems to coupled climate and land-use pressures and provide insights to strengthen climate-resilient agricultural management. Full article

The Land Use and Land Cover (LULC) of many regional landscapes are changing due to natural effects and anthropogenic activities, impacting biodiversity and ecosystem services. LULC dynamics reflect the altered flow of energy, water, and greenhouse gases, influencing the pillars of sustainability: society, environment, and economy. Thus, assessing LULC changes is vital for understanding the relationship between nature and society. This study used multi-temporal remotely sensed imagery to examine LULC change between 1990 and 2019 in the context of Forest Transition Theory (FTT) across the Greater Shawnee National Forest (GSNF) area of southern Illinois, USA, using a random forest algorithm, and projecting change to 2050 with a Land Change Model integrated with IPCC temperature and precipitation scenarios. From 1990 to 2019, LULC analysis showed increases in deciduous forest (1.35%), mixed forest (26.40%), agriculture (2.15%), and built-up areas (6.70%), while hay/grass/pasture declined (16.0%). LULC change intensity was highest from 1990 to 2001 (2.35% annually), slowing to 0.23% (2001–2010) and 0.18% (2010–2019). The overall accuracy (OA) of LULC classification ranged from 0.9 to 0.95 at a 95% confidence interval (CI). Projections to 2050 showed consistent increases in built-up areas (17.12–42.61%), water (28.75–39.70%), and hay/grass/pasture (6.23–38.38%), while overall forest cover declined in all scenarios. Deciduous forests decreased by 3.11–19.87% and were replaced by mixed forests in some scenarios (12.45–23.63%), while evergreen forests showed mixed responses, ranging from a decline of up to 17.13% to an increase of 2.90%. The OA of projected LULC ranged from 0.71 to 0.83 (95% CI) across SSP-RCP-based temperature and precipitation scenarios. The results showed that the GSNF broadly follows the FTT framework: forest recovery since 2001 coincided with rural depopulation, slow agricultural expansion, and rising incomes. However, climate change is expected to disrupt this recovery, pushing transitions toward mixed and evergreen forests. Findings demonstrate the importance of integrating remote sensing-based LULC with socio-economic trends and climate adaptation strategies to sustain forests and ecosystem services under future environmental pressures. Full article

Urban sprawl promotes significant changes in land use and occupation by interfering with the dynamics of functional ecosystems. Among other things, it encourages forest fragmentation, the degradation of woodland edges, and altered habitat integrity. This study aims to propose a simplified and low-cost methodological framework that integrates open data and open-source tools to monitor the potential of ecosystem services (ESs) at the municipal scale. Guided by the hypothesis that rapid suburbanization leads to measurable declines in ecological integrity, the InVEST Habitat Quality model was used as a proxy to analyze the landscape’s capacity to support ES. The procedure included data acquisition and organization, land use reclassification, and scores for the threats and sensitivities, implemented through the InVEST software 3.14.2. Results indicated that urban areas more than doubled between 1985 and 2005, while habitat quality scores declined across Campinas, reflecting a decrease in the potential for ES provision. Urban expansion, mainly concentrated in the central region, occurred at the expense of agricultural and pasture areas. Forest remnants, which currently occupy only 8.5% of the municipal territory, are small and fragmented, intensifying edge effects and reducing the potential capacity to provide regulatory ES. Fragmentation and adjacent land use changes limit these habitats’ capacity to provide ES. The proposed methodology demonstrates the potential for simple and reproducible monitoring of ecosystem services at the municipal scale, providing support to local governments with limited financial and technical capacity in geospatial data processing. This framework enables municipalities to incorporate environmental indicators into planning tools, offering a scalable approach for monitoring ecosystem dynamics in urbanized regions. Full article

Pasture ecosystems provide essential ecosystem services, yet poisonous plants create persistent veterinary and economic risks. We examined how hydroclimatic variability restructures the poisonous-plant assemblage across three Central Kazakhstan rangelands during an extremely dry year (2023) and an exceptionally wet year (2024). A total of 32 toxic vascular plant species were recorded. Xeromorphic pastures maintained a stable floristic core across years, whereas the wet year triggered recruitment of wet-associated poisonous taxa (hydrophytic/hygrophytic group) exclusively in the Nura River floodplain and increased species richness. Thus, interannual variability was controlled by hydrologically sensitive habitats rather than wholesale community turnover. The principal grazing hazard was associated with flood-related species (e.g., Cicuta virosa, Oenanthe aquatica) and persistent forage contaminants (Datura/Hyoscyamus, Lolium temulentum). These findings indicate that toxic-plant risk follows an asymmetric seasonal pattern: episodic post-flood hazard in floodplains combined with constant background risk in steppe pastures. Therefore, grazing management should integrate event-based monitoring of wet habitats with continuous forage-quality control. Full article

Tree-based production systems embedded within Amazonian biocultural landscapes remain systematically undervalued in global climate, biodiversity, and development policy frameworks. This study assessed tree diversity, structural attributes, and carbon stocks across traditional cacao-based Amazonian agroforestry systems (Chakra), tree-rich silvopastoral systems, and old-growth forests in the Andean–Amazon transition zone of Ecuador. Based on 28 sampling plots (DBH ≥ 10 cm), old-growth forests stored the highest aboveground carbon stocks, while agroforestry and silvopastoral systems retained approximately 20–30% of forest carbon, equivalent to ~100–180 Mg CO₂-equivalent ha⁻¹—far exceeding values reported for monocultures or treeless pastures. A total of 151 tree species were recorded across all land-use systems, with forests harboring the highest richness (122 species), followed by agroforestry (35 species) and silvopastoral systems (28 species). Carbon storage was highly concentrated in a limited subset of multifunctional species: in agroforestry systems, eight species accounted for ~80% of total aboveground CO₂-equivalent stocks, whereas in silvopastoral systems only five species explained a similar proportion. Dominant taxa such as Cordia alliodora, Inga edulis, Jacaranda copaia, Piptocoma discolor, and Piptadenia pteroclada illustrate a process of biocultural species filtering, whereby trees providing food, timber, shade, and cultural value are selectively retained while sustaining significant carbon stocks. These findings demonstrate that tree-based productive systems function as biocultural productive landscapes that conserve carbon, biodiversity, and livelihoods beyond forest boundaries. We argue for their formal inclusion, particularly traditional silvopastoral systems, within climate finance mechanisms, nationally determined contributions (NDCs), and biocultural heritage frameworks, alongside forest conservation strategies. Full article

This study presents new phytolith data that reconstruct the vegetation patterns and environmental context of medieval sites in northeastern Romania, integrated with previously published archaeozoological evidence. Sediment samples from cultural layers at Târgu Neamț–La Damian and Neamț Fortress were analysed following standard extraction protocols and classified according to the International Code for Phytolith Nomenclature (ICPN 2.0). The newly obtained phytolith assemblages are dominated by morphotypes from the Poaceae family, with diagnostic cereal forms, indicating intensive cereal use. The presence of arboreal and non-grass phytoliths further suggests a mosaic landscape combining grass-dominated open areas, pastures, and nearby woodland. When compared with existing faunal data, characterized by a predominance of domestic species such as cattle, sheep/goat, and pig, the results support the reconstruction of a diversified agro-pastoral economy adapted to local geomorphological and climatic conditions. The integration of new phytolith and existing archaeozoological data highlights the complementary role of plant microremains in reconstructing medieval environments, providing valuable insight into agro-pastoral resources, vegetation dynamics, and human–landscape interactions in the eastern Carpathian region. This approach enhances our understanding of the ecological basis of medieval Moldavian communities and contributes to the reconstruction of Late Holocene anthropogenic landscape dynamics within a Quaternary environmental framework. Full article

Following Romania’s regime change in 1989 and its accession to the European Union (EU) in 2007, the country experienced substantial land-use and land cover (LULC) changes driven by political, economic, and demographic processes. Early post-socialist property restitution led to land fragmentation, agricultural abandonment, and the expansion of pastures and semi-natural vegetation, while rural areas became dominated by small, semi-subsistence farms. After EU accession, the implementation of the Common Agricultural Policy (CAP), combined with foreign direct investment and market consolidation, reshaped agricultural practices and intensified urbanization, particularly in suburban municipalities, with growth following radial and linear patterns along major transportation corridors. This study analyses LULC dynamics in the Bucharest-Ilfov Development Region across three distinct phases—post-communist transition (1993–2000), EU pre-accession (2000–2015), and post-accession (2015–2022)—combining regional- and municipality-level analyses and using Landsat imagery, GIS, and landscape metrics. Four LULC maps (1993, 2000, 2015, and 2022) were produced with a Random Forest classifier, achieving macro F1-scores above 0.86. Population data from the National Institute of Statistics suggest contrasting patterns between urban expansion and demographic trends, with Bucharest showing population decline despite modest urban growth, and Ilfov County exhibiting parallel increases in population and urbanized areas. Results highlight rapid urban sprawl, sustained agricultural decline, and increasing landscape fragmentation. Discrepancies with earlier studies partly reflect temporal effects related to post-socialist industrial restructuring and differences in data sources and spatial resolution. These findings highlight the need for integrated urban planning strategies to balance development pressures with the preservation of agricultural land and ecological resources. Full article