scholarly journals Species Richness, Ecology, and Prediction of Orchids in Central Europe: Local-Scale Study

Diversity ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 154
Author(s):  
Matúš Hrivnák ◽  
Michal Slezák ◽  
Dobromil Galvánek ◽  
Jaroslav Vlčko ◽  
Eva Belanová ◽  
...  
Keyword(s):  
Species Richness ◽  
Agricultural Land ◽  
Ecological Factors ◽  
Solar Irradiation ◽  
Environmental Predictors ◽  
Orchid Species ◽  
Explanatory Variables ◽  
Ecological Predictors ◽  
Richness Patterns ◽  
The Relationship

Orchids are one of the most species-rich families in the world, and many species are under threat in numerous countries. Biodiversity research focusing on the relationship between the richness of orchid species and ecological factors was performed across the Cerová vrchovina Mts (Western Carpathians) testing impact of 26 explanatory variables. We aimed to determine the main ecological predictors controlling species richness and to predict potential species richness patterns. Altogether, 19 orchid species were found in the studied area, with Cephalanthera damasonium and Epipactis microphylla being the most common. Four environmental predictors (minimal longitude, carbonate-containing sediments, maximal yearly solar irradiation, and agricultural land) had statistically significant effects on orchid richness following regression analysis. Predictive models for the nine most frequent species using MaxEnt software showed (i) that land cover and geological substrate had the highest contribution to the explained variance in the models and (ii) strong potential for occurrence of given orchids in several poorly mapped parts of the studied area.

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 Evolutionary time drives global tetrapod diversity

2018 ◽  
Vol 285 (1872) ◽  
pp. 20172378 ◽  
Author(s):  
Julie Marin ◽  
Giovanni Rapacciuolo ◽  
Gabriel C. Costa ◽  
Catherine H. Graham ◽  
Thomas M. Brooks ◽  
...  
Keyword(s):  
Species Richness ◽  
Evolutionary Rate ◽  
Ecological Factors ◽  
Evolutionary Time ◽  
Secondary Importance ◽  
Persistence Time ◽  
Relative Contribution ◽  
Competing Hypotheses ◽  
Richness Patterns ◽  
Broad Spatial Scale

Global variation in species richness is widely recognized, but the explanation for what drives it continues to be debated. Previous efforts have focused on a subset of potential drivers, including evolutionary rate, evolutionary time (maximum clade age of species restricted to a region), dispersal (migration from one region to another), ecological factors and climatic stability. However, no study has evaluated these competing hypotheses simultaneously at a broad spatial scale. Here, we examine their relative contribution in determining the richness of the most comprehensive dataset of tetrapods to our knowledge (84% of the described species), distinguishing between the direct influences of evolutionary rate, evolutionary time and dispersal, and the indirect influences of ecological factors and climatic stability through their effect on direct factors. We found that evolutionary time exerted a primary influence on species richness, with evolutionary rate being of secondary importance. By contrast, dispersal did not significantly affect richness patterns. Ecological and climatic stability factors influenced species richness indirectly by modifying evolutionary time (i.e. persistence time) and rate. Overall, our findings suggest that global heterogeneity in tetrapod richness is explained primarily by the length of time species have had to diversify.

Which Parameters Determine the Development of Farm Numbers in Germany?

2011 ◽  
Vol 231 (3) ◽  
Author(s):  
Norbert Röder ◽  
Stefan Kilian
Keyword(s):  
Agricultural Land ◽  
Driving Forces ◽  
Local Level ◽  
Farm Size ◽  
Explanatory Variables ◽  
Determining Factors ◽  
Size Population ◽  
Management Orientation ◽  
On Farm ◽  
The Relationship

SummaryIn Germany, agricultural land use is very heterogeneous with respect to management orientation and productivity even at the local level. In addition, there is a wide variation in the reasons for farm exits. A review of the literature shows that a limited number of explanatory variables are generally accepted as being driving forces for farm exit rates. For the majority of indicators, ambiguous results are reported. In this paper, we analyse the determining factors of farm exit rates in Germany by examining municipalities from 1999 to 2007.We evaluate the robustness of the relationship between a set of explanatory variables and farm exit rates at different spatial scales.Our results indicate that the direction of impact of some variables (farm size, population density and the share of ruminants kept at low intensity as a fraction of the total ruminant stock) on farm exit rates is unambiguous throughout Germany. For the majority of the analysed explanatory variables, the strength of their impact on farm exit rates depends on their observation level or regional context.

scholarly journals An assessment of wetland nature reserves and the protection of China’s vertebrate diversity

2014 ◽  
Vol 37 (2) ◽  
pp. 217-225
Author(s):  
R. Sun ◽  
◽  
Y. Zheng ◽  
T. Lei ◽  
G. Cui ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Species Richness ◽  
Endemic Species ◽  
Nature Reserve ◽  
Nature Reserves ◽  
Analysis Method ◽  
Wetland Ecosystems ◽  
Terrestrial Vertebrates ◽  
Richness Patterns ◽  
The Relationship

We assessed all 148 wetland nature reserves in China and the distribution of the four taxa of endemic and threatened terrestrial vertebrates, reptiles, amphibians, birds and mammals. Assessment of the wetland nature reserves was combined with the governmental list of the endemic and threatened vertebrates to identify the richness of the species. Species richness was scored as high, medium or low using a factor analysis method, and 31 wetland ecosystems were marked as high protection areas. The relationship between the threatened species and the endemic species in the reserves was also analyzed. We found that both richness patterns were similar. Based on the richness study, a nature reserve classification system with corresponding.

scholarly journals Of food and fauna: investigating the relationship between global agricultural land use and biodiversity

2018 ◽  
Author(s):  
Laura Kehoe
Keyword(s):  
Land Use ◽  
Species Richness ◽  
Agricultural Land ◽  
Global Scale ◽  
Agricultural Land Use ◽  
Land Use Intensity ◽  
Research Gaps ◽  
The Impact ◽  
The Relationship ◽  
Broad Scale

Agricultural land use dominates one third of the Earth’s land surface and is the single biggest driver of biodiversity loss. Moreover, with a growing human population and a rising demand for resources, the impact of agricultural land use on biodiversity is projected to escalate. The main goal of this thesis was to gain a deeper understanding of the relationship between agricultural land use and biodiversity on a global scale. In approaching this goal, this thesis aims to bridge three main research gaps. First, while much research has addressed the effect of agricultural expansion on biodiversity, relatively little work has investigated the relationship between the many facets of agricultural intensification and biodiversity. Second, most studies on land use and biodiversity have assessed local to regional scale impacts, whereas few have assessed this relationship on a global scale. This gap is particularly critical in terms of predicting species richness – where environmental factors rather than human driven factors have traditionally been thought to be important in driving and predicting broad-scale patterns of biodiversity. Third, in light of growing future demand for resources, a better understanding is needed regarding the impact of future agricultural land use on biodiversity. This thesis made progress in bridging these research gaps by (i) mapping patterns of multiple metrics of land-use intensity and biodiversity, (ii) improving species- area relationships with the inclusion of land cover and land-use intensity metrics, and (iii) identifying highly biodiverse areas at risk under trajectories of potential future agricultural expansion and intensification. Patterns of land-use intensity metrics were heterogeneously distributed in areas of high biodiversity, suggesting that conservation research should include multiple intensity metrics in order to avoid underestimating biodiversity threat. Furthermore, results show land-use intensity was found to rival biomes in predicting global species richness, thus upgrading one of the most fundamental laws in ecology, and providing an improved understanding of broad-scale species richness patterns. Finally, areas most at-risk under potential future agricultural change were found to be widespread across Latin America and Sub-Saharan America. These results deliver crucial insights in proactively mitigating future potential conflicts in the nexus of biodiversity and land use. Overall, considering the great threat agriculture poses to biodiversity, this thesis highlighted the complexity and importance of land-use intensity in its relationship with biodiversity and uncovered highly biodiverse areas threatened by agricultural land use, both currently and in the future.

The Relationship between Mobility and COVID-19 in Germany: Modeling Case Occurrence using Apple's Mobility Trends Data

2021 ◽  
Author(s):  
Mark David Walker ◽  
Mihály Sulyok
Keyword(s):  
Generalized Additive Models ◽  
Information Criterion ◽  
Additive Models ◽  
Online Data ◽  
German Government ◽  
Explanatory Variables ◽  
Mobility Data ◽  
Community Mobility ◽  
The Relationship ◽  
Potential Use

Abstract Background Restrictions on social interaction and movement were implemented by the German government in March 2020 to reduce the transmission of coronavirus disease 2019 (COVID-19). Apple's “Mobility Trends” (AMT) data details levels of community mobility; it is a novel resource of potential use to epidemiologists. Objective The aim of the study is to use AMT data to examine the relationship between mobility and COVID-19 case occurrence for Germany. Is a change in mobility apparent following COVID-19 and the implementation of social restrictions? Is there a relationship between mobility and COVID-19 occurrence in Germany? Methods AMT data illustrates mobility levels throughout the epidemic, allowing the relationship between mobility and disease to be examined. Generalized additive models (GAMs) were established for Germany, with mobility categories, and date, as explanatory variables, and case numbers as response. Results Clear reductions in mobility occurred following the implementation of movement restrictions. There was a negative correlation between mobility and confirmed case numbers. GAM using all three categories of mobility data accounted for case occurrence as well and was favorable (AIC or Akaike Information Criterion: 2504) to models using categories separately (AIC with “driving,” 2511. “transit,” 2513. “walking,” 2508). Conclusion These results suggest an association between mobility and case occurrence. Further examination of the relationship between movement restrictions and COVID-19 transmission may be pertinent. The study shows how new sources of online data can be used to investigate problems in epidemiology.

scholarly journals A Model of Stress Change under the First COVID-19 Pandemic among the General Public in Japanese Major Cities and Rural Areas

2021 ◽  
Vol 13 (3) ◽  
pp. 1207
Author(s):  
Misato Uehara ◽  
Makoto Fujii ◽  
Kazuki Kobayashi
Keyword(s):  
Rural Areas ◽  
Healthcare Workers ◽  
Explanatory Variable ◽  
Large City ◽  
Stress Change ◽  
Multiple Factor Analysis ◽  
Explanatory Variables ◽  
Private Research ◽  
The Difference ◽  
The Relationship

Research on stress related to the COVID-19 pandemic has been dominated by the cases of healthcare workers, students, patients, and their stress during the COVID-19 pandemic. This study examined the relationship between the amount of stress change under the COVID-19 pandemic and demographic factors (age, sex, occupation, etc.) in residents of a large city and a rural area of Japan. A total of 1331 valid responses were received in June 2020 from residents of Tokyo, Osaka, and Nagano registered with a private research firm. We were able to identify 15 statistically significant variables out of 36 explanatory variables, which explained the significant increase in stress compared to the pre-pandemic period. Multiple-factor analysis showed that the relationship with people is a more significant explanatory variable for the level of increase in stress than the difference in environment between big cities (Tokyo, Osaka) and rural areas (Nagano), the type of housing, and the decrease in income compared to the pre-pandemic period.

scholarly journals The Modeling and Forecasting of Carabid Beetle Distribution in Northwestern China

Insects ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 168
Author(s):  
Xueqin Liu ◽  
Hui Wang ◽  
Dahan He ◽  
Xinpu Wang ◽  
Ming Bai
Keyword(s):  
Generalized Additive Models ◽  
Additive Models ◽  
Carabid Beetle ◽  
Conservation Strategies ◽  
Environmental Predictors ◽  
Temperate Steppe ◽  
Temperature And Precipitation ◽  
Steppe Ecosystems ◽  
Modeling And Forecasting ◽  
Richness Patterns

Beetles are key insect species in global biodiversity and play a significant role in steppe ecosystems. In the temperate steppe of China, the increasing degeneration of the grasslands threatens beetle species and their habitat. Using Generalized Additive Models (GAMs), we aimed to predict and map beetle richness patterns within the temperate steppe of Ningxia (China). We tested 19 environmental predictors including climate, topography, soil moisture and space as well as vegetation. Climatic variables (temperature, precipitation, soil temperature) consistently appeared among the most important predictors for beetle groups modeled. GAM generated predictive cartography for the study area. Our models explained a significant percentage of the variation in carabid beetle richness (79.8%), carabid beetle richness distribution seems to be mainly influenced by temperature and precipitation. The results have important implications for management and conservation strategies and also provides evidence for assessing and making predictions of beetle diversity across the steppe.

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