Disentangling the effects of topography and space on the distributions of dominant species in a subtropical forest

Ecological niche modeling to find potential habitats of Vanda thwaitesii, a notified endangered orchid of Western Ghats, India

Conservation planning of a threatened species essentially requires information on its present population and extent of distribution. Ecological niche modeling (ENM) is a suitable machine learning technique to predict potential distribution of a species enabling to identify suitable habitat for conservation action. The present study undertook distribution modeling of Vanda thwaitesii, a notified endangered orchid species of the Indian Western Ghats and Sri Lanka using maxent software. Geographical coordinates of 54 occurrence points at 1 km resolutions gathered during the study were utilized for modeling. A total of 37 variables including bioclimatic, topographical, and seasonal climate subjected to principal component analysis extracted into three components based on temperature and precipitation. Four representative variables from each component in all possible combinations resulted consistent output showing distribution of the species extending from Gavi in Periyar Tiger Reserve of Kerala to Chikkamagalur of Karnataka. Habitat suitability was confined to the cooler regions receiving an average 3,400 mm annual mean precipitation, 22.70C annual mean temperature, and 290 mm summer precipitation. A total of 2,557 km2 in Kerala and Karnataka mostly outside protected forests demonstrated as the highly suitable habitats. Silent Valley National Park, Idukki Wildlife Sanctuary, Periyar Tiger Reserve, and Brahmagiri Wildlife Sanctuary in addition to a few reserve forests hold sufficient area for reinforcement of diversity of V. thwaitesii from vulnerable locations. The present study revealed niche modeling as a useful tool to find suitable habitats for V. thwaitesii in the Western Ghats.

Disentangling Environmental Effects on the Tree Species Abundance Distribution and Richness in a Subtropical Forest

As a transitional vegetation type between evergreen broadleaved forest and deciduous broadleaved forest, evergreen-deciduous broadleaved mixed forest is composed of diverse plant species. This distinctive forest is generally distributed in mountainous areas with complex landforms and heterogeneous microenvironments. However, little is known about the roles of environmental conditions in driving the species diversity patterns of this forest. Here, based on a 15-ha plot in central China, we aimed to understand how and to what extent topographical characteristics and soil nutrients regulate the number and relative abundance of tree species in this forest. We measured environmental factors (terrain convexity, slope, soil total nitrogen, and phosphorus concentrations) and species diversity (species abundance distribution and species richness) in 20 m × 20 m subplots. Species abundance distribution was characterized by skewness, Berger-Parker index, and the proportion of singletons. The generalized additive model was used to examine the variations in diversity patterns caused by environmental factors. The structural equation model was used to assess whether and how topographical characteristics regulate species diversity via soil nutrients. We found that soil nutrients had significant negative effects on species richness and positive effects on all metrics of species abundance distribution. Convexity had significant positive effects on species richness and negative effects on all metrics of species abundance distribution, but these effects were mostly mediated by soil nutrients. Slope had significant negative effects on skewness and the Berger-Parker index, and these effects were almost independent of soil nutrients. Soil nutrients and topographical characteristics together accounted for 9.5-17.1% of variations in diversity patterns and, respectively, accounted for 8.9-13.9% and 3.3-10.7% of the variations. We concluded that soil nutrients were more important than topographical factors in regulating species diversity. Increased soil nutrient concentration led to decreased taxonomic diversity and increased species dominance and rarity. Convexity could be a better proxy for soil nutrients than slope. Moreover, these abiotic factors played limited roles in regulating diversity patterns, and it is possible that the observed patterns are also driven by some biotic and abiotic factors not considered here.

Stand Structure and Abiotic Factors Modulate Karst Forest Biomass in Southwest China

Understanding the driving factors of forest biomass are critical for further understanding the forest carbon cycle and carbon storage management in karst forests. This study aimed to investigate the distribution of forest aboveground biomass (AGB) and the effects of stand structural and abiotic factors on AGB in karst forests in Southwest China. We established a 25 ha plot and sampled all trees (≥1 cm diameter) in a subtropical mixed evergreen–deciduous broadleaf forest. We mapped the forest biomass distribution and applied a variation of partitioning analysis to examine the topographic, stand structural, and spatial factors. Furthermore, we used structural equation models (SEM) to test how these variables directly and/or indirectly affect AGB. The average AGB of the 25 ha plot was 73.92 Mg/ha, but that varied from 3.22 to 198.11 Mg/ha in the 20 m × 20 m quadrats. Topographic, stand structural, and spatial factors together explained 67.7% of the variation in AGB distribution. The structural variables (including tree density and the diameter at breast height (DBH) diversity) and topographic factors (including elevation, VDCN (vertical distance to channel network), convexity, and slope) were the most crucial driving factors of AGB in the karst forests. Structural equation models indicated that elevation, tree density, and DBH diversity directly affected AGB, and elevation also indirectly affected AGB through tree density and DBH diversity. Meanwhile, AGB was indirectly influenced by VDCN, convexity, and slope. The evaluation of stand structural and abiotic drivers of AGB provides better insights into the mechanisms that play a role in carbon storage in karst forests, which may assist in improving forest carbon management.

Patterns and determinants of plant biodiversity in non-commercial forests of eastern China

Non-commercial forests represent important habitats for the maintenance of biodiversity and ecosystem function in China, yet no studies have explored the patterns and determinants of plant biodiversity in these human dominated landscapes. Here we test the influence of (1) forest type (pine, mixed, and broad-leaved), (2) disturbance history, and (3) environmental factors, on tree species richness and composition in 600 study plots in eastern China. In total, we found 143 species in 53 families of woody plants, with a number of species rare and endemic in the study region. Species richness in mixed forest and broad-leaved forest was higher than that in pine forest, and was higher in forests with less disturbance. Species composition was influenced by environment factors in different ways in different forest types, with important variables including elevation, soil depth and aspect. Surprisingly, we found little effect of forest age after disturbance on species composition. Most non-commercial forests in this region are dominated by species poor pine forests and mixed young forests. As such, our results highlight the importance of broad-leaved forests for regional plant biodiversity conservation. To increase the representation of broad-leaved non-commercial forests, specific management practices such as thinning of pine trees could be undertaken.