Search Results (609)

Mangroves support a diverse insect fauna that plays essential roles in ecosystem functioning; however, the diversity of bark and ambrosia beetles (Curculionidae: Scolytinae) in the mangroves of the Mexican Pacific remains poorly understood. This study aimed to characterize the diversity and community structure of Scolytinae associated with two mangrove ecosystems in the state of Colima, western Mexico: Palo Verde Estuary and Juluapan Lagoon. Beetles were sampled using ethanol-baited traps (70% ethanol). A total of 1869 individuals belonging to 19 species and 10 genera were collected. Hypothenemus was the most species-rich genus, whereas Xyleborus volvulus was the dominant species. Five species are reported for the first time in Colima: Ambrosiodmus obliquus, Corthylus comatus, Premnobius cavipennis, Hypothenemus dolosus, and Hypothenemus indigens. Palo Verde Estuary showed higher beetle abundance, whereas Juluapan Lagoon exhibited greater species diversity and community evenness. Although the community shared several genera with mangrove ecosystems from other regions of Mexico and Brazil, it differed in species composition and dominance patterns. This study provides the first baseline on the Scolytinae fauna associated with the mangroves of Colima and establishes a reference for future ecological monitoring and phytosanitary surveillance programs. Full article

Wetlands monitoring is essential for sustainable watershed biodiversity conservation, and climate resilience. This study performs a spatiotemporal wetland change analysis for the Sangamon River Watershed, Illinois between 2000 and 2025, using Landsat 5 Thematic Mapper (TM), Sentinel–2 Surface Reflectance (SR), Synthetic Aperture Radar (SAR), Gray–Level Co–occurrence Matrix (GLCM) and terrain data through cloud–based processing in Google Earth Engine (GEE), Google Colab and ArcGIS Pro 3.6.0. We conducted a comparative assessment of deep learning (Deep Neural Network [DNN], U-Net, Attention U-Net, and SegFormer), and machine learning models (Random Forest [RF], Gradient Tree Boosting [GTB], and Support Vector Machines [SVM]) through pixel–based and object–based methods. National Land Cover Database (NLCD) was used for training and validation using stratified random sampling for five categories namely wetlands, forest, agriculture/grassland/barren land, urban/developed and water. A proportion of 54.85% (860.68 km²) of wetlands extent was lost to other land uses, particularly agriculture, urban and forest, along with 46.51% (694.88 km²) forest and 36.80% (66.13 km²) water bodies loss. Agriculture/grassland/barren and urban/developed witnessed increases of 8.56% (820.62 km²) and 72.92% (799.52 km²), respectively. For Landsat–based and Sentinel–based classifications, SegFormer outperformed all ML and DL classifiers with (OA = 94%, Kappa = 0.89, mean F1 = 0.80, mean IoU = 0.70 and OA = 96%, Kappa = 0.92, mean F1 = 0.95, mean IoU = 0.73, respectively) with excellent wetland delineation (PA = 0.99, UA = 0.97, F1 = 0.98, IoU = 0.97 and PA = 0.99, UA = 0.99, F1 = 0.98, IoU = 0.99, respectively). Sentinel–based classifications had improved performance than Landsat, while object–based models consistently outperformed pixel–based methods. The Digital Elevation Model (DEM) and slope were the most influential predictors for RF models, while GLCM and SAR produced negligible influence. The integrated and comparative GeoAI framework provides a robust methodology for watershed–scale wetland monitoring and supports evidence–based conservation, restoration prioritization, climate resilience, and sustainable land–use planning, while offering strong potential for application in other agricultural watersheds following regional validation. Full article

Urban blue–green spaces (UBGSs) are critical for biodiversity, yet our understanding of how plant diversity in these spaces responds to urbanization across different UBGS types remains limited. Here, we investigated plant communities in four sampled UBGSs along an urban gradient in the Minjiang River Basin, China. Because each blue–green space type is represented by a single site, all comparisons are site-specific and descriptive. Using species richness (S), the Shannon–Wiener index (H′), Pielou’s evenness index (J′), frequency (F), and importance value (I.V.), we described whether taxonomic composition and diversity patterns differed among the four sampled sites. Across all sites, based on 615 species records, angiosperms dominated (92.6%), and cosmopolitan families (e.g., Asteraceae, Poaceae, Fabaceae) were ubiquitous, consistent with a strong regional species pool influence. However, our cross-site comparison showed a contrasting pattern: the near-natural Baihetan National Wetland Park showed the highest S (12.87) but low evenness (0.49), whereas the intensively managed Huoshui Park, with the lowest richness (9.67), achieved the highest evenness (0.68). Further, a discordance between F and I.V. rankings was observed in the managed site, where ornamental species showed high spatial coverage but low I.V. ranks. We report this rank discordance only as an observational finding, not as a proven metric or indicator. This discordance suggests that richness alone may not fully capture community structure, though its diagnostic value remains unverified. We interpret these contrasting richness–evenness patterns from the four sampled sites. Because site identity is confounded with management intensity, habitat area, and landscape context, no causal attribution to ecological or anthropogenic factors can be made. Evenness and species richness showed different site-to-site patterns, but this association remains observational. We hypothesize that a resilient urban biodiversity network could combine complementary nodes, with large natural wetlands as species-rich sites and constructed parks as structurally balanced units, rather than pursuing a single diversity target. This study provides preliminary insights that may inform planning considerations under Chengdu’s Park City initiative, but these suggestions should be viewed as hypotheses requiring further validation rather than as established management guidelines. The proposed network approach, while conceptually appealing, requires empirical testing through replicated studies before it can be considered for broader application. Full article

High-altitude wetlands in the Caucasus Anatolia transition zone remain among the least-documented avian habitats in the Western Palearctic. Standardised avian biodiversity assessment in such systems provides essential evidence for sustainable wetland management, supporting the conservation planning and long-term ecological monitoring needed to safeguard these ecosystems under increasing anthropogenic pressure. We report on the avifauna of Çalı Lake (2237 m a.s.l.; 391 ha; Kars Province, Türkiye), a nationally designated wetland located on the Central Asian Flyway, based on five systematic survey periods conducted from March 2024 to Spring 2026 using line transects and point counts, combined with a 25 × 25 m grid-based GIS analysis encompassing 498 cells. Approximately 31 ha of the core open-water and marsh perimeter within the 391 ha designated boundary is covered; upland steppe and pasture zones beyond the active survey perimeter were excluded. A total of 154 species belonging to 18 orders and 41 families were recorded, representing approximately 30.5% of Turkey’s national checklist. IUCN status assessment identified two Endangered species, Neophron percnopterus and Oxyura leucocephala, two Vulnerable, five Near Threatened, and 145 Least Concern species. Grid-level species richness averaged 1.47 ± 1.20 per cell per period; cumulative richness per grid reached 7.62 ± 2.73 across all five survey periods. Spearman rank correlation between per-grid richness (S) and abundance (N) was consistently strong across all five periods (ρ = 0.52–0.60; all p < 0.001). A Friedman test indicated significant overall variation across periods (χ²(4) = 127.73, p < 0.001, Kendall’s W = 0.064, a negligible effect size by conventional benchmarks, indicating that the statistically significant variation reflects trivially small per-cell richness differences at this block size). Bonferroni-corrected post hoc Wilcoxon tests revealed that all significant contrasts involved the 2024 Spring–Summer period or the 2026 partial Spring window, while the four fully comparable 2024 Autumn–2025 periods showed no significant differences. A Lorenz concentration curve yielded a Gini coefficient of 0.351, with the top 10% of grid cells concentrating 24.0% of all individual detections in the central and south-western lake zones. Collectively, these findings document Çalı Lake as a species-rich high-altitude wetland with significant conservation value, and establish a reproducible spatial and temporal baseline for long-term ornithological monitoring. These results demonstrate the value of standardised biodiversity assessment as a practical tool for sustainable wetland governance and align with international sustainability frameworks, including the UN Sustainable Development Goals on life on land and clean water and sanitation. Full article

Urbanization and agricultural expansion have led to widespread habitat loss and fragmentation, profoundly altering avian community structure. To understand how different habitat types shape bird diversity and assembly rules, we investigated bird communities across four major habitats (farmland, forest, urban, and wetland) in Henan province. Our results showed that wetland habitats supported the highest species richness, while forest habitats exhibited the highest Shannon–Wiener diversity and evenness. Rarefaction curves indicated that wetland and forest communities harbored the greatest species diversity even with increased sampling effort, while farmland communities showed early saturation. Venn diagram analysis revealed that 30.0% of species were unique to wetlands, 25.0% to forests, 8.3% to urban areas, and only 5.0% to farmland, with limited species overlap across habitats. Rank-abundance distribution (RAD) models varied significantly by habitat: the lognormal distribution best described farmland communities, preemption fit forest and wetland communities, and the Mandelbrot distribution best fit urban communities. Indicator species analysis identified Spilopelia chinensis as a significant indicator for farmland habitats (Indicator Value = 0.938, p < 0.01), reflecting its strong association with open agricultural landscapes. NMDS ordination (Stress = 0.152) showed partial overlap in community composition across habitats, while redundancy analysis (RDA) revealed that longitude (15.3% variance explained), latitude, altitude, and temperature collectively shaped bird community structure. These findings highlight that habitat type is a key driver of avian diversity and community assembly, with forests and wetlands serving as critical refuges for diverse bird communities. Urban and farmland habitats, while supporting lower diversity, host specialized species adapted to human-altered conditions. Our study emphasizes the need for multi-habitat conservation strategies to maintain avian biodiversity in fragmented landscapes. Full article

Poyang Lake is a typical floodplain lake hydrologically linked to the middle-lower Yangtze River. Its peripheral saucer-shaped sub-lakes undergo seasonal hydrological alternation between isolation and connectivity driven by annual water level fluctuations. To date, the coupling between seasonal hydrological rhythms and zooplankton metacommunity assembly in these saucer floodplain lakes remains poorly understood. In this study, four representative saucer sub-lakes within the Poyang Lake National Nature Reserve (Banghu, Zhonghuchi, Shahu and Dahuchi) were selected as research objects. Seasonal quantitative zooplankton surveys and synchronous hydro-physicochemical monitoring were conducted across four hydrological phases from 2012 to 2013: low-water isolation (spring), high-water connectivity (summer), water recession transition (autumn), and extreme low-water closure (winter). We systematically explored how water level fluctuations regulate zooplankton metacommunity assembly processes. In total, 95 zooplankton species were identified, among which rotifers (68 species) constituted the absolute dominant taxon, and 15 species were identified as year-round absolute dominants exhibiting regular seasonal succession in response to hydrological shifts. Our results demonstrate that hydrological connectivity plays a strong role in regulating the relative strength of species dispersal and environmental filtering. During spring and winter, complete hydrological isolation blocked inter-lake species exchange, making local environmental filtering the main driver of metacommunity assembly. Isolated sub-lakes harbored fewer total species but abundant endemic taxa, accompanied by pronounced spatial community heterogeneity. When water levels exceeded the 17.3 m threshold in summer, full water exchange between sub-lakes and the main lake coincided with widespread species dispersal, which appeared to represent the primary assembly process. The four sub-lakes shared 23 co-occurring species during this period, with highly homogenized community structures and minimal spatial differentiation (Global test: R = 0.47, p = 0.001). In autumn, receding water levels weakened inter-lake connectivity, such that environmental filtering and dispersal jointly structured zooplankton metacommunities; significant spatiotemporal differences were detected in zooplankton density, biomass and α-diversity (p < 0.05). Critical hydro-physicochemical factors of environmental filtering included water temperature, chlorophyll a, pH, electrical conductivity and turbidity, yet the dominant limiting factor varied spatially across sub-lakes due to divergent basin topography and water residence time. Species co-occurrence network analysis revealed that zooplankton communities achieved the highest stability during the fully connected summer phase. In early autumn water drawdown, species association networks became fragmented, and community stability reached its annual minimum. This study elucidates the mechanistic link between floodplain lake hydrological rhythms and zooplankton metacommunity assembly, providing theoretical support and baseline data for wetland biodiversity conservation and ecosystem management of Poyang Lake floodplains. Full article

Urban wetlands and agricultural lands are among the most important socio-ecological systems in urban areas. They support food production, biodiversity conservation, water regulation, climate resilience, and human well-being. However, rapid urbanization negatively affects wetland–agricultural coexistence (WAC) by destroying habitats, fragmenting landscapes, and intensifying land-use conflicts. Our study proposed a Wetland–Agriculture Coexistence Index (WACI) to assess the spatial pattern of WAC in Colombo, Sri Lanka. We considered four components for the WACI framework: wetland condition (WC), agricultural condition (AC), urban pressure (UP), and hydrological connectivity (HC). The WACI was developed using Landsat 8/9, Sentinel-1 Synthetic Aperture Radar (SAR), and Advanced Land Observing Satellite (ALOS) data, along with road network, population, and hydrological network data. Variables used in this study include land surface temperature (LST), Enhanced Vegetation Index (EVI), Modified Soil-Adjusted Vegetation Index (MSAVI), Bare Soil Index (BSI), soil moisture, elevation, slope, population density, distance to roads, hydrological connectivity, and built-up %, which were normalized and integrated into four dimensions using an equal-weighted approach to develop the WACI. The results showed substantial spatial heterogeneity in WAC across Colombo. The average WACI was 0.51, indicating a moderate WAC. This study further identified that favorable environmental conditions, rich hydrological connectivity, and low urban pressure increased coexistence potentials. The spatial pattern of WACI identified priority areas for conservation, restoration, and sustainable urban planning implications in Colombo. Our WACI framework provides a practical and transferable method for assessing WAC in urban areas. The findings of this study support balanced urban wetland–agricultural management, conservation, food security, and long-term sustainability of rapidly urbanizing cities. Full article

The Larus ridibundus (L. ridibundus), a prominent part of Kunming’s landscape, attracts many tourists and boosts the local tourism industry. Effective population monitoring of this species matters for wetland environment evaluation, biodiversity conservation, and ecological civilization construction. Currently, L. ridibundus population statistics mainly rely on manual methods, which are labor-intensive and inefficient. To overcome these limits, we propose a deep learning (DL) framework. It automatically recognizes and counts L. ridibundus by combining CDSP2-YOLOv8n with ByteTrack, aiming to efficiently monitor their population metrics. Our framework uses the optimized YOLOv8n model to achieve excellent multi-object detection for this species. It also uses ByteTrack to effectively reduce target loss from occlusion or overlap during the birds’ flight, providing a sophisticated DL approach for population monitoring. Experimental results show the modified CDSP2-YOLOv8n model works well on the collected L. ridibundus multi-object detection dataset. Its mAP@0.5, mAP@0.5:0.95, Precision, and Recall reach 0.9705, 0.6557, 0.9685, and 0.9496, respectively. When combined with ByteTrack, the proposed framework achieved a Multiple Object Tracking Accuracy (MOTA) of 89.7% and a Multiple Object Tracking Precision (MOTP) of 83.5%. It also demonstrated superior performance in terms of IDF1, Mostly Tracked (MT), Mostly Lost (ML), and Identity Switches (IDSs). Compared to manual counting, our framework has an average accuracy of 91.58%, greatly enhancing the efficiency and accuracy of L. ridibundus population monitoring. In summary, we successfully achieved the automated recognition and counting of L. ridibundus. The proposed method accurately identifies and consistently tracks individual birds, enabling effective population counting. It provides a novel and comprehensive technical approach for the monitoring and conservation of this species and demonstrates promising potential for practical applications. Full article

The Chilean flamingo (Phoenicopterus chilensis) is a widely distributed South American species inhabiting diverse wetland ecosystems from Ecuador and Peru south to Chile and Argentina, and east to Brazil, Uruguay, and Paraguay, ranging from sea level to high-altitude Andean salars. Despite its broad distribution, local populations are increasingly exposed to anthropogenic pressures, raising conservation concerns at regional scales. In this study, we generated mitogenomic resources and developed a molecular framework for species identification using non-invasive samples. We sequenced genomic DNA from P. chilensis and assembled its complete mitogenome, enabling the in silico evaluation of commonly used metabarcoding markers. Subsequently, we collected eight fecal samples from a feeding site in a high-Andean lagoon where P. chilensis co-occurs with Phoenicoparrus andinus and Phoenicoparrus jamesi. As a positive control, nine additional fecal samples were collected from the Zoológico Nacional, Santiago, Chile, where only P. chilensis is maintained. DNA was extracted and initially screened via Sanger sequencing. To robustly assign taxonomic identity, we implemented a probabilistic framework combining maximum likelihood and Bayesian inference to estimate the posterior probability of species membership based on observed genetic variants. This approach revealed the presence of two genetically distinct groups not attributable to P. chilensis, indicating the coexistence and detectability of other flamingo taxa through fecal DNA. Our results demonstrate the value of integrating mitogenomic resources, metabarcoding, and statistical inference for non-invasive species identification in mixed-species systems. This framework provides a scalable tool for biodiversity monitoring and has direct implications for conservation strategies and evidence-based policy development in fragile high-Andean ecosystems. Full article

Ecological niche modeling (ENM) is widely used to predict species distributions and support biodiversity conservation under environmental change, yet its application to Amazonian wetland plants has not been systematically synthesized. We conducted a systematic review following the PRISMA 2020 guidelines to evaluate methodological approaches, environmental predictors, model performance, and research gaps. Literature searches were performed in Web of Science, Scopus, and Consensus (as a complementary AI-assisted academic search platform), yielding 1789 records, of which 48 met the eligibility criteria. Correlative models predominated, with MaxEnt, Random Forest, and ensemble frameworks being the most frequently applied algorithms. Across studies, integrating hydrological and edaphic predictors consistently improved model performance and ecological realism compared with climate-only approaches. Future climate projections indicated greater vulnerability for habitat-specialist species, whereas western Amazonia and the Andean foothills were repeatedly identified as potential climatic refugia. Major limitations included geographically biased occurrence records, limited high-resolution environmental datasets, and the underrepresentation of several Amazonian wetland ecosystems. Overall, the evidence indicates that reliable ENMs for Amazonian wetlands require integrating climatic, hydrological, and edaphic drivers rather than relying solely on macroclimate. Future research should prioritize geographically representative sampling, improved environmental datasets, transparent workflows, and process-informed modeling to strengthen ecological forecasting and conservation planning under climate and land-use change. Full article

Coal mining in areas with high groundwater levels often induces land subsidence and water accumulation, leading to the formation of artificial secondary wetlands. Reclaimed wetlands may provide important opportunities for regional biodiversity recovery. Taking Shuoxi Lake Wetland in Huaibei City as a case study, this research aims to reveal the characteristics of waterbird diversity in artificial wetlands after ecological reclamation in a coal mining subsidence area and to identify their key environmental drivers, thereby providing a scientific basis for optimizing the habitat service functions of such wetlands. Based on habitat identification and classification of the reclaimed wetland, waterbird diversity was surveyed, and redundancy analysis (RDA), Mantel tests, and ridge regression models were used to identify the major environmental factors influencing the distribution of different waterbird groups and to quantify their relative contributions. The results showed that after ecological reclamation, a total of 28 waterbird species belonging to 7 families and 6 orders were recorded in the artificial wetland of the coal mining subsidence area. Redundancy analysis (RDA) indicated that wader assemblages were more sensitive to vegetation cover (VC), distance to water bodies (DTW), and distance to buildings (DTB), whereas waterfowl assemblages were mainly affected by distance to buildings (DTB), area (A), and distance to water bodies (DTW), and showed no significant response to vegetation heterogeneity. Mantel tests further confirmed significant spatial correlations between waterbird assemblages and area (A), distance to major roads (DTR), distance to buildings (DTB), water depth (WD), and distance to water bodies (DTW). Ridge regression analysis showed that, under conditions in which anthropogenic disturbance was minimized, vegetation cover (VC) and water depth (WD) were the main positive drivers of wader diversity, whereas perimeter to area ratio (PAR) was the main negative driver. Waterfowl diversity was mainly negatively affected by perimeter to area ratio (PAR) and distance to water bodies (DTW). These findings suggest that appropriately regulating water depth, increasing vegetation cover, and reducing patch fragmentation and anthropogenic disturbance are key measures for enhancing the habitat service functions of artificial secondary wetlands in mining areas. These management strategies provide an important reference for wetland rehabilitation in other coal mining subsidence areas. Full article

The Laspias River and Lissos River sustain the hydrological and ecological functioning of the Vistonida Lake wetland complex, a protected Natura 2000 site and Ramsar Convention Wetland of International Importance, by regulating nutrient transport and supporting aquatic biodiversity. Thus, the water quality of the rivers Laspias and Lissos and their adjacent coastal zones located in the prefectures of Xanthi and Rhodope (NE Greece) respectively was monitored regarding key metal concentrations for a period of two years. The monitoring of these watersheds and coastal zones was based on seven sampling stations in the Laspias River, twelve stations in the Lissos River and four stations in each river’s coastal zone. During water monitoring of both rivers, a wide range of chemical elements was analyzed to assess water quality. In the present work, the heavy metal pollution index (HPI) and the heavy metal evaluation index (HEI) were assessed in both rivers and their coastal area for four successive seasons. The mean HPI and HEI values for the Laspias River were 54.66 ± 10.82 and 1.45 ± 0.22, whereas the respective indices in the Lissos River were 14.43 ± 4.14 and 0.39 ± 0.14. The mean HPI and HEI values for the adjacent coastal zones of the Laspias and Lissos Rivers were 7.42 ± 1.52 and 0.14 ± 0.05, as well as 10.39 ± 0.83 and 0.23 ± 0.02, respectively. Therefore, the average HPI values for both rivers and their coastal zones were below the proposed threshold (<100), while the HEI of the Laspias River classified the water quality in the second category (slightly affected, HEI from 1.0 to 2.0 due to the effect of Mn) and the Lissos River in the first category (very pure/pure, HEI < 1), respectively, considering drinking water thresholds. The HEI indices of their coastal zones characterized the water quality as very pure/pure. Full article

Invasive species represent a major threat to global biodiversity, highlighting the need for continuous monitoring and research to better understand their ecology, distribution, and invasion dynamics. Among freshwater leeches (Hirudinea), Helobdella europaea is considered one of the most successful and widespread invasive taxa. This study provides an updated assessment of the distribution of H. europaea in Morocco and identifies the main environmental factors influencing its occurrence and spread across the country. Field surveys were conducted between 2014 and 2024 in northern Morocco, with particular focus on protected wetlands, including Ramsar sites, and major biogeographical barriers such as the Middle Atlas Mountains and the Sebou and Moulouya river basins. Specimens were collected using Surber samplers (20 × 25 cm, 400 μm mesh), while physicochemical water parameters and other abiotic variables were simultaneously recorded. Since its first detection in Morocco in 2014, H. europaea has significantly expanded its geographic range. The species exhibited broad ecological tolerance, occurring in a wide variety of habitats, including environmentally degraded sites, and enduring substantial variation in water conditions. Among the environmental variables examined, water velocity and salinity were identified as the primary factors constraining the species’ distribution and abundance. Nevertheless, additional studies are required to better predict the future expansion dynamics of H. europaea, particularly under ongoing hydrological alterations and climate change scenarios. Full article

Kazakhstan’s Ili River delta nourishes a unique wetland ecosystem in arid Central Asia. The delta is dominated by common reed [Phragmites australis (Cav.) Trin. ex Steud.], an ecologically and economically significant species that is sensitive to water levels. We used machine learning methods, including the Random Forest algorithm, to classify common reed-containing wetland vegetation and water surfaces in the delta based on satellite data from 2000 to 2023. The remote sensing results were integrated with field-based geobotanical studies conducted between 2017 and 2019. These studies, which facilitated identification of three classes of vegetation: meadow, marsh and aquatic, also revealed a good correspondence between predicted and measured common reed biomass per unit area. The long-term dynamics of four wetland communities with a common reed content of ≥25% were analyzed with respect to significant interannual variability in the flow of the Ili River. The highest water inflows and water surface areas in the delta were recorded in 2002, 2010 and 2016, and in each case, a statistically significant expansion of common reed was observed one year later. Common reed areas subsequently declined—rapidly or after a lag of several years. Temporal expansion and contraction of these areas following pulses of water differed substantially from that of overall wetland vegetation as measured previously. The identified patterns have important scientific and practical significance for assessing the stability of the surrounding wetlands, preservation of the delta environment, and sustainable use of common reed. Full article