A functional traits approach was adopted to examine patterns of fish diversity in relation to environmental and spatial variables and for comparison with findings from earlier analyses of fish taxonomic diversity in a nearly pristine river in the Llanos region of Colombia. Fishes were surveyed during the low-water period at 34 sites along the longitudinal fluvial gradient of the Bita River, a clearwater tributary of the Orinoco River. We compiled a matrix of 37 traits associated with locomotion, feeding, and defense for 132 species to compute functional β diversity metrics among four reaches along the entire longitudinal fluvial gradient and also within reaches. Functional redundancy (trait under-dispersion) was found to be common throughout the fluvial gradient. Functional β diversity was high at both spatial scales, with widespread evidence of functional nestedness and functional turnover, especially in upper reaches. In the Bita River, environmental filtering and stochastic processes, such as random dispersal, appear to be the dominant mechanisms influencing fish functional diversity. Inferences derived from analysis of functional versus taxonomic diversity are largely congruent, although analysis of functional β diversity found more evidence of nestedness than turnover at both spatial scales. Both lines of evidence stress the importance of habitat heterogeneity and aquatic habitat connectivity for conservation of high species diversity in this system.

Revealing the impact of forest succession processes on changes in plant diversity is crucial for understanding the mechanisms that maintain plant diversity across various succession stages. While previous research has predominantly focused on the influence of environmental factors or management strategies on plant diversity within rubber plantation understories, there is a scarcity of studies examining the effects of forest succession processes on plant diversity. This study focuses on the plant diversity of the understory herbaceous layer within the rubber forest of the Yinggeling area, located in National Park of Hainan Tropical Rainforest. It employs a spatial analysis approach, rather than a temporal one, to examine the characteristics of the understory herbaceous community. The findings revealed that (1) The understory of Yinggeling rubber plantations harbors 175 plant species from 149 genera and 75 families, with Gramineae and Rubiaceae representing 46.45% of total species. And the dominant families are Rubiaceae, Gramineae, and Moraceae, with Ficus and Pteris being the dominant genera. (2) The dominant species vary with succession duration, with Tetrastigma pachyphyllum dominating in 0-year succession, Paspalum conjugatum in 3-year succession, and Microstegium fasciculatum in 7-year succession. (3) Diversity indices such as the Shannon–Wiener index, Simpson index, and Pielou index peak at 7 years of natural succession, while the species richness is highest at 3 years. (4) The similarity coefficient between understory herbaceous plant communities in rubber plantations undergoing 0 and 3 years of natural succession is highest 0.56, indicating a significant similarity, while similarity is lowest between 0 and 7 years of succession. This research shows that natural restoration helps increase species diversity in the understory herb layer of rubber forests. Succession leads to changes in the dominant families, genera, and species of the herbaceous layer. This change can be attributed to the intraspecific competition and ecological competition that occur during the succession process, leading to changes in biological and resource allocation.

Pteridophytes are excellent ecological indicators of habitat quality. In this study, we built a model that predicts the habitat suitability of Elaphoglossum beddomei Sledge, an epiphytic or lithophytic and endemic pteridophyte in Southern Western Ghats, by using the technique of species distribution modelling. The occurrence data of E. beddomei from field explorations as well as from various herbaria were collected during 2018–2022. These occurrence data along with climatic data were processed by R packages. The processed data were further analysed using MaxEnt software to project the distribution of E. beddomei in future climatic scenarios. After correlation analysis, five bioclimatic variables – Mean Temperature of Wettest Quarter (bio8), Precipitation of Driest Quarter (bio17), Precipitation of Warmest Quarter (bio18), Precipitation of Wettest Quarter (bio16) and Temperature Annual Range (BIO5-BIO6) (bio7) – were selected from 19 bioclimatic variables with less correlation. Precipitation of Warmest Quarter (bio18) had the most influence in determining the distribution of E. beddomei, with a permutation importance of 83%. Conversely, Temperature Annual Range (BIO5-BIO6) (bio7) and Precipitation of Driest Quarter (bio17) showed least influence in determining the distribution of E. beddomei, and hence, the models created without these variables are considered for prediction. The habitat suitability predictions of the model indicate that the potential habitats of the species may get reduced in Southern Western Ghats in future climatic scenarios. It is in tune with the predicted expansion of drier climatic zones in Southern Western Ghats, which may reduce the suitable habitats for the E. beddomei in near future. So, it demands formulating suitable strategies for reducing the emission of greenhouse gases, regenerating forests and conserving forests by implementing more stringent policies on the environment to protect such highly habitat-specific evergreen elements.