scholarly journals Distribution Pattern of Gymnosperms’ Richness in Nepal: Effect of Environmental Constrains along Elevational Gradients

Plants ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 625
Author(s):  
Bikram Pandey ◽  
Nirdesh Nepal ◽  
Salina Tripathi ◽  
Kaiwen Pan ◽  
Mohammed A. Dakhil ◽  
...  
Keyword(s):  
Species Richness ◽  
Distribution Pattern ◽  
Species Distribution ◽  
Environmental Variables ◽  
Environmental Indicators ◽  
Climatic Variables ◽  
Elevation Gradients ◽  
Hypothesis Model ◽  
Richness Pattern ◽  
Richness Patterns

Understanding the pattern of species distribution and the underlying mechanism is essential for conservation planning. Several climatic variables determine the species diversity, and the dependency of species on climate motivates ecologists and bio-geographers to explain the richness patterns along with elevation and environmental correlates. We used interpolated elevational distribution data to examine the relative importance of climatic variables in determining the species richness pattern of 26 species of gymnosperms in the longest elevation gradients in the world. Thirteen environmental variables were divided into three predictors set representing each hypothesis model (energy-water, physical-tolerance, and climatic-seasonality); to explain the species richness pattern of gymnosperms along the elevational gradient. We performed generalized linear models and variation partitioning to evaluate the relevant role of environmental variables on species richness patterns. Our findings showed that the gymnosperms’ richness formed a hump-shaped distribution pattern. The individual effect of energy-water predictor set was identified as the primary determinant of species richness. While, the joint effects of energy-water and physical-tolerance predictors have explained highest variations in gymnosperm distribution. The multiple environmental indicators are essential drivers of species distribution and have direct implications in understanding the effect of climate change on the species richness pattern.

scholarly journals Contrasting Gymnosperm Diversity Across an Elevation Gradient in the Ecoregion of China: The Role of Temperature and Productivity

2021 ◽  
Vol 9 ◽  
Author(s):  
Bikram Pandey ◽  
Kaiwen Pan ◽  
Mohammed A. Dakhil ◽  
Ziyan Liao ◽  
Arbindra Timilsina ◽  
...  
Keyword(s):  
Species Richness ◽  
Elevation Gradient ◽  
Aridity Index ◽  
Climatic Variables ◽  
Equation Modeling ◽  
Precipitation Pattern ◽  
Elevation Gradients ◽  
Precipitation Seasonality ◽  
Richness Pattern ◽  
Richness Patterns

The species richness–climate relationship is a significant concept in determining the richness patterns and predicting the cause of its distribution. The distribution range of species and climatic variables along elevation have been used in evaluating the elevational diversity gradients (EDG). However, the species richness of gymnosperms along elevation and its driving factors in large geographic areas are still unknown. Here, we aimed at evaluating the EDG of gymnosperms in the ecoregions of China. We divided the geographical region of China into 34 ecoregions and determine the richness pattern of gymnosperm taxa along elevation gradients. We demonstrated the richness patterns of the 237-gymnosperm (219 threatened, 112 endemic, 189 trees, and 48 shrubs) taxa, roughly distributed between 0 and 5,300 m (above sea level) in China. As possible determinants of richness patterns, annual mean temperature (TEMP), annual precipitation (PPT), potential evapotranspiration (PET), net primary productivity (SNPP), aridity index (AI), temperature seasonality (TS), and precipitation seasonality (PS) are the major predictor variables driving the EDG in plants. We used the species interpolation method to determine the species richness at each elevation band. To evaluate the richness pattern of gymnosperms in an ecoregion, generalized additive modeling and structural equation modeling were performed. The ecoregions in the southern part of China are rich in gymnosperm species, where three distinct richness patterns—(i) hump-shaped, (ii) monotonic increase, and (iii) monotonic decline—were noticed in China. All climatic variables have a significant effect on the richness pattern of gymnosperms; however, TEMP, SNPP, TS, and PS explained the highest deviance in diversity-rich ecoregions of China. Our results suggests that the highest number of gymnosperms species was found in the southwestern and Taiwan regions of China distributed at the 1,600- and 2,800-m elevation bands. These regions could be under severe stress in the near future due to expected changes in precipitation pattern and increase of temperature due to climate change. Thus, our study provided evidence of the species–climate relationship that can support the understanding of future conservation planning of gymnosperms.

Global patterns of plant diversity and their evolutionary drivers

2020 ◽  
Author(s):  
Melanie Tietje ◽  
William J. Baker ◽  
Rafaël Govaerts ◽  
Stephen A. Smith ◽  
Miao Sun ◽  
...  
Keyword(s):  
Species Richness ◽  
Plant Diversity ◽  
Environmental Variables ◽  
Plant Species Richness ◽  
Richness Pattern ◽  
Forest Regions ◽  
Speciation Rates ◽  
Underlying Causes ◽  
Richness Patterns ◽  
Initial Results

<p>Spatial patterns of plant diversity follow the well-known global latitudinal biodiversity gradient, however there is little consensus about the underlying causes for this pattern. Here we present a spatial analysis of a complete checklist of the world’s seed plants, integrated with a comprehensive plant Tree of Life. This combination allows insights into the evolutionary drivers of plant species richness patterns, specifically current plant biodiversity patterns, and the diversification processes that shaped them. Our study provides a comprehensive global species richness map and relates the observed species richness pattern to speciation rates derived from phylogeny, and with environmental variables, which are hypothesized to impact speciation rates. Initial results show that tropical rain forest regions, although being areas that contain among the highest numbers of species, are regions with comparatively low speciation rates, contradicting the widespread notion that rainforests are “cradles” of biodiversity. This finding seems further supported by contrasting association of environmental variables, like precipitation and temperature, with speciation rates and species richness.</p>

scholarly journals The Effect of Climate and Human Pressures on Functional Diversity and Species Richness Patterns of Amphibians, Reptiles and Mammals in Europe

Diversity ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 275
Author(s):  
Mariana A. Tsianou ◽  
Maria Lazarina ◽  
Danai-Eleni Michailidou ◽  
Aristi Andrikou-Charitidou ◽  
Stefanos P. Sgardelis ◽  
...  
Keyword(s):  
Species Richness ◽  
Functional Diversity ◽  
Agricultural Land ◽  
Influential Factor ◽  
Climatic Variables ◽  
Quadratic Entropy ◽  
Functional Richness ◽  
Precipitation Seasonality ◽  
Rao’S Quadratic Entropy ◽  
Richness Patterns

The ongoing biodiversity crisis reinforces the urgent need to unravel diversity patterns and the underlying processes shaping them. Although taxonomic diversity has been extensively studied and is considered the common currency, simultaneously conserving other facets of diversity (e.g., functional diversity) is critical to ensure ecosystem functioning and the provision of ecosystem services. Here, we explored the effect of key climatic factors (temperature, precipitation, temperature seasonality, and precipitation seasonality) and factors reflecting human pressures (agricultural land, urban land, land-cover diversity, and human population density) on the functional diversity (functional richness and Rao’s quadratic entropy) and species richness of amphibians (68 species), reptiles (107 species), and mammals (176 species) in Europe. We explored the relationship between different predictors and diversity metrics using generalized additive mixed model analysis, to capture non-linear relationships and to account for spatial autocorrelation. We found that at this broad continental spatial scale, climatic variables exerted a significant effect on the functional diversity and species richness of all taxa. On the other hand, variables reflecting human pressures contributed significantly in the models even though their explanatory power was lower compared to climatic variables. In most cases, functional richness and Rao’s quadratic entropy responded similarly to climate and human pressures. In conclusion, climate is the most influential factor in shaping both the functional diversity and species richness patterns of amphibians, reptiles, and mammals in Europe. However, incorporating factors reflecting human pressures complementary to climate could be conducive to us understanding the drivers of functional diversity and richness patterns.

scholarly journals Elevational pattern of bird species richness and its causes along a central Himalaya gradient, China

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2636 ◽  
Author(s):  
Xinyuan Pan ◽  
Zhifeng Ding ◽  
Yiming Hu ◽  
Jianchao Liang ◽  
Yongjie Wu ◽  
...  
Keyword(s):  
Species Richness ◽  
Habitat Heterogeneity ◽  
Anthropogenic Activities ◽  
Bird Species ◽  
Primary Forest ◽  
Central Himalaya ◽  
Wet Season ◽  
Breeding Bird ◽  
Richness Pattern ◽  
Richness Patterns

This study examines the relative importance of six variables: area, the mid-domain effect, temperature, precipitation, productivity, and habitat heterogeneity on elevational patterns of species richness for breeding birds along a central Himalaya gradient in the Gyirong Valley, the longest of five canyons in the Mount Qomolangma National Nature Reserve. We conducted field surveys in each of twelve elevational bands of 300 m between 1,800 and 5,400 m asl four times throughout the entire wet season. A total of 169 breeding bird species were recorded and most of the species (74%) were small-ranged. The species richness patterns of overall, large-ranged and small-ranged birds were all hump-shaped, but with peaks at different elevations. Large-ranged species and small-ranged species contributed equally to the overall richness pattern.Based on the bivariate and multiple regression analyses, area and precipitation were not crucial factors in determining the species richness along this gradient. The mid-domain effect played an important role in shaping the richness pattern of large-ranged species. Temperature was negatively correlated with overall and large-ranged species but positively correlated with small-ranged species. Productivity was a strong explanatory factor among all the bird groups, and habitat heterogeneity played an important role in shaping the elevational richness patterns of overall and small-ranged species. Our results highlight the need to conserve primary forest and intact habitat in this area. Furthermore, we need to increase conservation efforts in this montane biodiversity hotspot in light of increasing anthropogenic activities and land use pressure.

scholarly journals Historical dynamics and current environmental effects explain the spatial distribution of species richness patterns of New World monkeys

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3850 ◽  
Author(s):  
Paulo Vallejos-Garrido ◽  
Reinaldo Rivera ◽  
Oscar Inostroza-Michael ◽  
Enrique Rodríguez-Serrano ◽  
Cristián E. Hernández
Keyword(s):  
Species Richness ◽  
Amazon Basin ◽  
New World ◽  
Climatic Variables ◽  
New World Monkeys ◽  
Biodiversity Hotspots ◽  
Environmental Constraints ◽  
Spatial Autoregressive ◽  
Richness Patterns ◽  
Source Sink

Background Why biodiversity is not uniformly distributed on the Earth is a major research question of biogeography. One of the most striking patterns of disparity in species distribution are the biodiversity hotspots, which generally do not fit with the distribution of relevant components of the Neotropical biota. In this study, we assess the proximal causes of the species-richness pattern of one of the most conspicuous groups of Neotropical mammals, the New World monkeys the Platyrrhini. We test two complementary hypotheses: (1) there is a historical source-sink dynamic (addressed using macroevolutionary and macroecological approaches); (2) the large number of species in the Amazon basin is due to the constraints imposed by environmental variables occurring outside this area. Methods We first characterize spatial patterns of species richness and biodiversity hotspots using a new, objective protocol based on probabilities. Then we evaluate the source-sink hypothesis using BioGeoBEARS analysis and nestedness analysis of species richness patterns. Complementarily, to measure how often different species pairs appear in the same sites, we used null models to estimate the checkerboard score index (C-score). Finally, we evaluate the relationship between several climatic variables and species richness through ordinary least squares (OLS) and spatial autoregressive (SAR) models, and the potential environmental constraints on the pattern. Results We found one significant cluster of high values for species richness in the Amazon basin. Most dispersal events occurred from the Amazonian subregion to other Neotropical areas. Temperature (T), discrepancy (BR), and NODF indexes show a significant nesting in the matrix ordered by species richness and available energy. The C-score observed was significantly smaller than the null expectation for all sites in the Neotropics where there are records of platyrrhine species. Ten climatic variables comprised the best-fitting model that explains species richness. OLS and SAR models show that this set of variables explains 69.9% and 64.2% of species richness, respectively. Potential of evapotranspiration is the most important variable within this model, showing a linear positive relationship with species richness, and clear lower and upper limits to the species richness distribution. Discussion We suggest that New World monkeys historically migrated from their biodiversity hotspot (energetically optimal areas for most platyrrine species) to adjacent, energetically suboptimal areas, and that the different dispersal abilities of these species, the lack of competitive interactions at a macroecological scale, and environmental constraints (i.e., energy availability, seasonality) are key elements which explain the non-uniform pattern of species richness for this clade.

Small mammals in fragments of Atlantic Forest: species richness answering to field methods and environment

2020 ◽  
Vol 36 (3) ◽  
pp. 101-108
Author(s):  
Daniele Pereira Rodrigues ◽  
Fabrício Luiz Skupien ◽  
Jady de Oliveira Sausen ◽  
Daniela Oliveira de Lima
Keyword(s):  
Species Richness ◽  
Atlantic Forest ◽  
Small Mammals ◽  
Small Mammal ◽  
Environmental Variables ◽  
Regression Tree ◽  
Environmental Indicators ◽  
Pitfall Traps ◽  
Field Methods ◽  
Forest Strata

AbstractSmall mammals can be used as environmental indicators and have been intensively studied in fragmented landscapes of Atlantic Forest, with a wide range of field methods. Our aim in this study was two-fold: we tested for the effects of methods and for the effects of the main environmental variables on observed small mammal richness in fragments of Atlantic Forest. We gathered information on small mammal richness, methods and environmental variables from 122 fragments of Atlantic Forest through literature review. These data were analysed using linear models and model selection based on AIC values along with a regression tree analysis. We found that studies will record more species with bigger trapping effort, using pitfall traps and sampling all forest strata. We also confirmed two important ecological assumptions: fragments at lower latitudes and bigger fragments were the ones with higher species richness. Methodological and environmental variables were analysed together on a regression tree, where trapping effort was the most important variable, surpassing any environmental effect. Considering that a significant number of the studies on Atlantic Forest fragments did not use pitfall traps or sample all forest strata, their results on forest fragmentation were affected by sampling bias.

The relationships between terrestrial vertebrate species richness in China’s nature reserves and environmental variables

2006 ◽  
Vol 84 (9) ◽  
pp. 1368-1374 ◽  
Author(s):  
Shuqing Zhao ◽  
Jingyun Fang ◽  
Changhui Peng ◽  
Zhiyao Tang
Keyword(s):  
Species Richness ◽  
Primary Productivity ◽  
Environmental Variables ◽  
Net Primary Productivity ◽  
Nature Reserves ◽  
Vertebrate Species ◽  
Terrestrial Vertebrate ◽  
Physiologically Based ◽  
Richness Patterns ◽  
Terrestrial Vertebrate Species

Explaining species richness patterns over broad geographic scales is a central issue of biogeography and macroecology. In this study, we took spatial autocorrelation into account and used terrestrial vertebrate species richness data from 211 nature reserves, together with climatic and topographical variables and reserve area, to explain terrestrial vertebrate species richness patterns in China and to test two climatically based hypotheses for animals. Our results demonstrated that species richness patterns of different terrestrial vertebrate taxa were predicted by the environmental variables used, in a decreasing order, as reptiles (56.5%), followed by amphibians (51.8%), mammals (42%), and birds (19%). The endothermic vertebrates (mammals and birds) were closely correlated with net primary productivity (NPP), which supports the productivity hypothesis, whereas the ectothermic vertebrates (amphibians and reptiles) were strongly associated with both water and energy variables but weakly with NPP, which supports the physiologically based ambient climate hypothesis. The differences in the dependence of endothermic and ectothermic vertebrates on productivity or ambient climate may be due in part to their different thermoregulatory mechanisms. Consistent with earlier studies, mammals were strongly and positively related to geomorphologic heterogeneity, measured by elevation range, implying that the protection of mountains may be especially important in conserving mammalian diversity.

scholarly journals Using climatic variables alone overestimate climate change impacts on predicting distribution of an endemic species

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0256918
Author(s):  
Somayeh Zangiabadi ◽  
Hassan Zaremaivan ◽  
LIuis Brotons ◽  
Hossein Mostafavi ◽  
Hojjatollah Ranjbar
Keyword(s):  
Climate Change ◽  
Plant Species ◽  
Species Distribution ◽  
Environmental Variables ◽  
Area Under The Curve ◽  
Predictive Ability ◽  
Principal Component ◽  
Distribution Range ◽  
Climatic Variables ◽  
Prediction Ability

Plant species distribution is constrained by both dynamic and static environmental variables. However, relative contribution of dynamic and static variables in determining species distributions is not clear and has far reaching implications for range change dynamics in a changing world. Prunus eburnea (Spach) Aitch. & Hemsl. is an endemic and medicinal plant species of Iran. It has rendered itself as ecologically important for its functions and services and is currently in need of habitat conservation measures requiring investigation of future potential distribution range. We conducted sampling of 500 points that cover most of Iran plateau and recorded the P. eburnea presence and absence during the period 2015–2017. In this study, we evaluated impacts of using only climatic variables versus combined with topographic and edaphic variables on accuracy criteria and predictive ability of current and future habitat suitability of this species under climate change (CCSM4, RCP 2.6 in 2070) by generalized linear model and generalized boosted model. Models’ performances were evaluated using area under the curve, sensitivity, specificity and the true skill statistic. Then, we evaluated here, driving environmental variables determining the distribution of P. eburnea by using principal component analysis and partitioning methods. Our results indicated that prediction with high accuracy of the spatial distribution of P. eburnea requires both climate information, as dynamic primary factors, but also detailed information on soil and topography variables, as static factors. The results emphasized that environmental variable grouping influenced the modelling prediction ability strongly and the use of only climate variables would exaggerate the predicted distribution range under climate change. Results supported using both dynamic and static variables improved accuracy of the modeling and provided more realistic prediction of species distribution under influence of climate change.

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