The anti-seasonal drawdown zone of the Three Gorges Reservoir (TGR) presents a unique ecological filter characterized by prolonged winter flooding and summer drought. This study investigated plant functional traits (PFTs) and CSR (Competitor–Stress tolerator–Ruderal) ecological strategies across an elevation gradient (145–175 m) in the TGR drawdown zone and the adjacent non-inundated reservoir shore slope (>175 m), to examine plant adaptation to the hydrological gradient. We measured 15 PFTs from 32 dominant species across three sites and calculated CSR strategies using three leaf traits (leaf area, specific leaf area, and leaf dry matter content). The results showed that elevation zone had significant effects on PH, SDMC, LL/LW, SLW, LDMC, SPAD, and SRA. LL/LW, LDMC, RL and FRTD were identified as hub traits in the trait correlation network. Stem traits were significantly related to slope, flooding and TP. Overall mean CSR values for the plant community were 47.90% for C, 37.01% for S, and 15.10% for R. However, the data revealed a clear elevation-dependent shift in the C–S balance: S declined from 45.78% in Zone I to 21.46% in Zone IV, while C increased from 41.86% to 55.61% and R increased to 22.93% in Zone IV. Key stress-tolerant species, such as Cynodon dactylon and Cyperus rotundus exhibited high CS-strategy values across all elevations. CSR strategies were correlated with SWC, flooding, elevation, TC and TN. Correlation heatmaps revealed distinct trait–strategy syndromes: the C strategy was negatively correlated with SDMC and LL/LW but positively correlated with SPAD and LN, whereas the S strategy showed the exact opposite pattern. Water-related factors mainly drove the C and S strategies, with SWC negatively correlated with C and flooding duration negatively correlated with S. These are correlative associations rather than causal pathways. These observed associations are consistent with the hypothesis that intense hydrological stress acts as an environmental filter shaping plant ecological strategies, although the historical filtering process itself is not directly observed in this cross-sectional study. Within this framework, niche differentiation is realized through subtle trait variations and mixed strategies.
Mangrove-fringed coastal areas provide habitat and sediment regulation ecosystem services, increasingly affected by land-use change. However, integrated local-scale assessments of habitat quality and sediment dynamics remain limited. This study assessed land-use and land-cover (LULC) changes in Mueang Samut Sakhon District, Thailand, for 2000–2020 and projected a business-as-usual (BAU) scenario for 2040 using a cellular automata-artificial neural network model (hindcast overall accuracy 74.7%). Habitat quality and sediment dynamics were assessed for 2000, 2020, and 2040 using the InVEST Habitat Quality and Sediment Delivery Ratio models, and tested with an independent mangrove dataset, sensitivity analyses, and an analysis by LULC transition. Between 2000 and 2020, built-up land increased by 34.7% and mapped mangroves declined by 50.6%, with further changes of +4.8% and −9.3% projected for 2040. Global Mangrove Watch indicated a smaller decline (29%), so the mapped loss is an upper estimate. Total habitat quality declined by 22.2% (2000–2020), mainly through habitat loss and remains concentrated along coastal and estuarine zones, with degradation increasing locally near development corridors. Under the 2040 scenario, potential soil erosion increased by 0.86%, while sediment export rose by 4.28%. The increase in avoided sediment export (3.64%) resulted mainly from higher modelled connectivity around new built-up land. Continued urban expansion may intensify pressure on remaining mangroves, reduce habitat quality, and alter sediment delivery. Integrating LULC modelling with InVEST-led assessment can support coastal planning and identify candidate areas for nature-based solutions, including mangrove restoration, which can be improved through field assessment.
Understanding how landscape and local factors influence biodiversity in agroforestry systems is essential for conservation in fragmented tropical landscapes. We investigated the relative importance of forest proximity and local environmental variables (canopy openness, temperature, and air humidity) in shaping bryophyte assemblages in shaded cacao agroforests in the Brazilian Atlantic Forest. Bryophytes were sampled on 218 trees across six agroforestry sites, totaling 1304 occurrences and 87 taxa. Generalized linear mixed models and multivariate analyses were used to assess patterns of species richness, occurrence frequency, and composition. Moss richness and occurrence frequency increased with forest distance, whereas liverworts showed no clear relationship. Liverwort richness was positively associated with temperature, while occurrence frequency was positively associated with temperature and negatively with air humidity. When accounting for spatial nesting via site-level block permutations, neither forest distance nor microclimate significantly structured species composition (p ≥ 0.313), reflecting site-level spatial heterogeneity. Bryoflora was dominated by generalist taxa and species with intermediate desiccation tolerance, and assemblages showed taxon-specific relationships with local environmental conditions. Our findings suggest the hypothesis that long-established, shaded cacao agroforests may support diverse bryophyte assemblages in fragmented tropical landscapes, a pattern that requires formal evaluation with native forest reference controls.
Body mass is a fundamental functional trait influencing mammalian biology, ecology, and conservation status. In Neotropical studies, species are conventionally classified into small (<1 kg), medium (1–44 kg), and large (>44 kg) mammals. However, whether these operational thresholds reflect natural discontinuities in body mass across regional faunas remains untested. We compiled body mass data for 529 Brazilian terrestrial mammal species across nine orders (excluding Chiroptera) to evaluate body-size distribution and test whether conventional categories align with empirical body-mass structure using Gaussian finite mixture modeling (GMM). Small mammals dominated the fauna (73.9%), followed by medium (24.8%) and large species (1.3%). A four-component Gaussian mixture model was retained as a biologically interpretable representation of body-mass structure. The estimated component means were approximately 22, 65, 298, and 1210 g. However, the observed body-mass ranges of species assigned to the components were not fully separated, particularly for the broad fourth component. These results suggest substantial structure within the lower portion of the body-mass distribution, while highlighting the limitations of interpreting probabilistic components as discrete body-size classes. We provide a standardized framework for body-size classification to enhance comparability across macroecological and conservation studies in the Neotropics.
The results of a metabolomic profile analysis of subaerial biofilms (SABs) of varying taxonomic compositions formed under various conditions are presented. The temporal and spatial characteristics of the SAB metabolic profile within a single biotope in St. Petersburg were also studied in detail. Metabolomic profiling was performed using gas chromatography–mass spectrometry (GC-MS). Dimensionality reduction methods, including principal component analysis, partial least squares discriminant analysis, and hierarchical clustering, were used to visualize the data structure and potential class separation. The metabolomic profile reflects the dominant group of organisms, even when the abundance of a particular group of organisms is not significant. Metabolomic analysis using GC-MS allows for rapid acquisition of information on the diversity of small organic molecules in the profile, specifically those belonging to actively growing organisms, which will allow for a better understanding not only of the composition but also of the functioning of the community. Within a single biotope, temporal factors can contribute significantly more to the metabolomic differences in biofilms than spatial heterogeneity. Polyols, fatty acids, terpenoids, and sterols contribute most to the structural differences in the SAB metabolite network from different biotopes, as well as to the spatial and dynamic changes in SAB within a single biotope.
