Aquatic and semi aquatic Hemiptera community of Sonebeel, the largest wetland of Assam, northeastern India

2018 ◽  
Vol 10 (13) ◽  
pp. 12792-12799
Author(s):  
Anupama Saha ◽  
Susmita Gupta
Keyword(s):  
Species Richness ◽  
Pest Control ◽  
Relative Abundance ◽  
Species Distribution ◽  
Diversity Indices ◽  
Environmental Data ◽  
Northeastern India ◽  
Ecological Roles

Aquatic and semiaquatic Hemiptera bugs play significant ecological roles, and they are important indicators and pest control agents.  Little information is currently available concerning its populations in southern Assam.  This study assessed hemipterans in four sites of Sonebeel, the largest wetland in Assam (3458.12 ha at full storage level), situated in Karimganj District.  The major inflow and outflow of the wetland are the rivers Singla and Kachua, respectively (the Kachua drains into the Kushiyara River).  Samples were trapped with pond nets and were seasonally recorded.  This study recorded a total of 28 species of aquatic and semiaquatic hemipterans belonging to 20 genera under nine families.  Population, geographical and environmental data (e.g., rainfall) were used to assess the relative abundance of species, species richness and different diversity indices, and species distribution. 

Forty years of dietary studies on barn owl (Tyto alba) reveal long term trends in diversity metrics of small mammal prey

2018 ◽  
Vol 68 (2) ◽  
pp. 129-146 ◽  
Author(s):  
Giuliano Milana ◽  
Luca Luiselli ◽  
Giovanni Amori
Keyword(s):  
Species Richness ◽  
Relative Abundance ◽  
Negative Correlation ◽  
Linear Models ◽  
Prey Availability ◽  
Diversity Indices ◽  
Barn Owl ◽  
Tyto Alba ◽  
Local Conditions ◽  
Over Time

AbstractThe diet of predators is influenced by local conditions (e.g., characteristics of habitat and microhabitat, seasonality, prey availability) and therefore tends to change across time. In this paper, the diet composition of the barn owl (Tyto alba) in Italy was studied using a meta-analysis of 47 articles (covering 212 independent sites, with multiple surveys for some sites, thus giving a total of 290 datasets) between 1972 and 2012. General Linear Models were used to assess the effects of year and study site on four distinct diversity indices (species richness, dominance, Shannon-Weaver diversity and equitability). The year of data collection was a factor used in all analyses. Year had a greater effect than study site on all diversity indices, but the effect was not significant for the evenness and the species richness. However, dietary dominance increased significantly over the years, the Shannon-Weaver index of diversity decreased significantly over time, and equitability also decreased significantly over time. The relative abundance of various species of rodents did not increase/decrease progressively over the years, although there were inter-annual fluctuations. On the other hand, the relative abundance of insectivores tended to decrease with time, and there was a significantly negative correlation between year and the frequency of consumption of Sorex spp. and a marginally significant negative correlation for Crocidura leucodon.

Spatial prediction of brushtail possum (Trichosurus vulpecula) distribution using a combination of remotely sensed and field-observed environmental data

2013 ◽  
Vol 40 (7) ◽  
pp. 578 ◽  
Author(s):  
Thibaud Porphyre ◽  
Joanna McKenzie ◽  
Andrea E. Byrom ◽  
Graham Nugent ◽  
James Shepherd ◽  
...  
Keyword(s):  
Pest Control ◽  
Relative Abundance ◽  
Forest Cover ◽  
Remotely Sensed ◽  
Environmental Data ◽  
Effective Control ◽  
Brushtail Possum ◽  
Mean Annual Temperature ◽  
Trichosurus Vulpecula ◽  
Remotely Sensed Data

Context In New Zealand, the introduced brushtail possum, Trichosurus vulpecula, is a reservoir of bovine tuberculosis and as such poses a major threat to the livestock industry. Aerial 1080 poisoning is an important tool for possum control but is expensive, creating an ongoing need for ever more cost-effective ways of using this technique. Aims To develop geographic information system (GIS) models to better predict spatial variation in the distribution of unmanaged possum populations, to facilitate better targeting of control activities. Methods Relative abundance of possums and their distribution among habitat types were surveyed in a dry high-country area of the northern South Island. Two GIS-based models were developed to predict the relative abundance of possums on trap lines. The first model used remotely sensed (digital) environmental data; the second complemented the remotely sensed data with fine-scale habitat and topographic data collected on the ground. Key results Digital environmental factors and habitat features proved to be key predictors of relative possum abundance. In both GIS models, height above valley floor, presence of forest cover and mean annual temperature were the strongest predictors. Conclusions Predictive maps (projections) of relative possum abundance produced from these models can provide useful decision-support tools for pest-control managers, by enabling possum control to be targeted spatially. Implications Spatially targeted pest control could allow effective control activities for invasive species or disease vectors to be applied at a lower cost for the same benefit.

scholarly journals Ephemeroptera (Mayflies) Assemblages and Environmental Variation along Three Streams Located in the Dry-Hot Valleys of Baima Snow Mountain, Yunnan, Southwest China

Insects ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 775
Author(s):  
Muhammad Farooq ◽  
Xianfu Li ◽  
Lu Tan ◽  
Davide Fornacca ◽  
Yanpeng Li ◽  
...  
Keyword(s):  
Species Richness ◽  
Species Composition ◽  
Community Composition ◽  
Environmental Variation ◽  
Diversity Indices ◽  
Freshwater Ecosystems ◽  
Environmental Data ◽  
Elevation Gradients ◽  
Depth Analysis ◽  
The Impact

Mountain freshwater ecosystems are threatened all over the world by a range of human-induced stresses, ensuing in a rapid loss of habitats and species diversity. Many macroinvertebrates are reactive to habitat disturbance, and mayflies (Ephemeroptera) are amongst the most sensitive groups. Despite they are susceptible to environmental deviation, knowledge concerning their species richness and diversity is still unknown in remote areas. The objectives of this study were to (1) investigate the mayfly species assemblage and community composition along different mountain streams and assess potential differences, and (2) identify the environmental variation and its influence on the structure of mayfly communities within such freshwater systems. We collected biological and environmental data from 35 sites situated along elevation gradients in the Baima Snow Mountain, northwest Yunnan, China. Multivariate analyses were performed on the environmental variables and the mayfly species composition, as well as on richness and diversity indices. We found that the community composition of mayflies was different across all three watercourses. Among the 18 Ephemeroptera taxa identified, Baetis sp. and Baetiella marginata were highly dominant, accounting for over 50% of the dissimilarity of each stream. In terms of species assemblages, almost all sites in the Yeri stream hosted good-quality habitats for several mayfly species, as reflected by the highest species richness. The Benzilan stream followed, whereas the Sharong stream showed relatively low mayfly assemblage. This variation was explained by the high environmental heterogeneity between the three watercourses. In particular, the RDA model revealed that among the different environmental factors analyzed, altitude, conductivity, total dissolved solids, water temperature, dissolved silicon, and pH explained most of the variation in species composition. Moreover, the altitude alone explained 17.74% of the variation, and in-depth analysis confirmed its significant effect on diversity indices. Further research should focus on evaluating the scale of threats to this important group of insects in the mountain freshwater ecosystem, particularly the impact of human-induced disturbances such as land use/landcover alterations.

scholarly journals A Robust Prediction Model for Species Distribution Using Bagging Ensembles with Deep Neural Networks

2021 ◽  
Vol 13 (8) ◽  
pp. 1495
Author(s):  
Jehyeok Rew ◽  
Yongjang Cho ◽  
Eenjun Hwang
Keyword(s):  
Neural Networks ◽  
Species Distribution ◽  
Best Practice ◽  
Deep Neural Networks ◽  
Species Distribution Models ◽  
Species Distribution Model ◽  
Environmental Data ◽  
Distribution Model ◽  
Distribution Models ◽  
Robust Prediction

Species distribution models have been used for various purposes, such as conserving species, discovering potential habitats, and obtaining evolutionary insights by predicting species occurrence. Many statistical and machine-learning-based approaches have been proposed to construct effective species distribution models, but with limited success due to spatial biases in presences and imbalanced presence-absences. We propose a novel species distribution model to address these problems based on bootstrap aggregating (bagging) ensembles of deep neural networks (DNNs). We first generate bootstraps considering presence-absence data on spatial balance to alleviate the bias problem. Then we construct DNNs using environmental data from presence and absence locations, and finally combine these into an ensemble model using three voting methods to improve prediction accuracy. Extensive experiments verified the proposed model’s effectiveness for species in South Korea using crowdsourced observations that have spatial biases. The proposed model achieved more accurate and robust prediction results than the current best practice models.

scholarly journals Temperature and Prey Species Richness Drive the Broad-Scale Distribution of a Generalist Predator

Diversity ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 169
Author(s):  
Danai-Eleni Michailidou ◽  
Maria Lazarina ◽  
Stefanos P. Sgardelis
Keyword(s):  
Species Richness ◽  
Species Distribution ◽  
Prey Species ◽  
Abiotic Factors ◽  
Biodiversity Loss ◽  
Generalist Predator ◽  
Distributional Patterns ◽  
The Future ◽  
Grass Snake ◽  
Broad Scale

The ongoing climate change and the unprecedented rate of biodiversity loss render the need to accurately project future species distributional patterns more critical than ever. Mounting evidence suggests that not only abiotic factors, but also biotic interactions drive broad-scale distributional patterns. Here, we explored the effect of predator-prey interaction on the predator distribution, using as target species the widespread and generalist grass snake (Natrix natrix). We used ensemble Species Distribution Modeling (SDM) to build a model only with abiotic variables (abiotic model) and a biotic one including prey species richness. Then we projected the future grass snake distribution using a modest emission scenario assuming an unhindered and no dispersal scenario. The two models performed equally well, with temperature and prey species richness emerging as the top drivers of species distribution in the abiotic and biotic models, respectively. In the future, a severe range contraction is anticipated in the case of no dispersal, a likely possibility as reptiles are poor dispersers. If the species can disperse freely, an improbable scenario due to habitat loss and fragmentation, it will lose part of its contemporary distribution, but it will expand northwards.

scholarly journals Modelling Maritime Pine (Pinus pinaster Aiton) Spatial Distribution and Productivity in Portugal: Tools for Forest Management

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 368
Author(s):  
Cristina Alegria ◽  
Natália Roque ◽  
Teresa Albuquerque ◽  
Paulo Fernandez ◽  
Maria Margarida Ribeiro
Keyword(s):  
Spatial Distribution ◽  
Forest Management ◽  
Species Distribution ◽  
Pinus Pinaster ◽  
Landscape Planning ◽  
Environmental Data ◽  
Maritime Pine ◽  
Future Climate Change ◽  
Sequential Simulation ◽  
Model Species

Research Highlights: Modelling species’ distribution and productivity is key to support integrated landscape planning, species’ afforestation, and sustainable forest management. Background and Objectives: Maritime pine (Pinus pinaster Aiton) forests in Portugal were lately affected by wildfires and measures to overcome this situation are needed. The aims of this study were: (1) to model species’ spatial distribution and productivity using a machine learning (ML) regression approach to produce current species’ distribution and productivity maps; (2) to model the species’ spatial productivity using a stochastic sequential simulation approach to produce the species’ current productivity map; (3) to produce the species’ potential distribution map, by using a ML classification approach to define species’ ecological envelope thresholds; and (4) to identify present and future key factors for the species’ afforestation and management. Materials and Methods: Spatial land cover/land use data, inventory, and environmental data (climate, topography, and soil) were used in a coupled ML regression and stochastic sequential simulation approaches to model species’ current and potential distributions and productivity. Results: Maritime pine spatial distribution modelling by the ML approach provided 69% fitting efficiency, while species productivity modelling achieved only 43%. The species’ potential area covered 60% of the country’s area, where 78% of the species’ forest inventory plots (1995) were found. The change in the Maritime pine stands’ age structure observed in the last decades is causing the species’ recovery by natural regeneration to be at risk. Conclusions: The maps produced allow for best site identification for species afforestation, wood production regulation support, landscape planning considering species’ diversity, and fire hazard mitigation. These maps were obtained by modelling using environmental covariates, such as climate attributes, so their projection in future climate change scenarios can be performed.

Very high resolution environmental predictors in species distribution models

2013 ◽  
Vol 38 (1) ◽  
pp. 79-96 ◽  
Author(s):  
Jean-Nicolas Pradervand ◽  
Anne Dubuis ◽  
Loïc Pellissier ◽  
Antoine Guisan ◽  
Christophe Randin
Keyword(s):  
High Resolution ◽  
Species Distribution ◽  
Species Distribution Models ◽  
Environmental Data ◽  
Swiss Alps ◽  
Fine Scale ◽  
Distribution Models ◽  
Model Quality ◽  
Vegetation Height ◽  
Very High

Recent advances in remote sensing technologies have facilitated the generation of very high resolution (VHR) environmental data. Exploratory studies suggested that, if used in species distribution models (SDMs), these data should enable modelling species’ micro-habitats and allow improving predictions for fine-scale biodiversity management. In the present study, we tested the influence, in SDMs, of predictors derived from a VHR digital elevation model (DEM) by comparing the predictive power of models for 239 plant species and their assemblages fitted at six different resolutions in the Swiss Alps. We also tested whether changes of the model quality for a species is related to its functional and ecological characteristics. Refining the resolution only contributed to slight improvement of the models for more than half of the examined species, with the best results obtained at 5 m, but no significant improvement was observed, on average, across all species. Contrary to our expectations, we could not consistently correlate the changes in model performance with species characteristics such as vegetation height. Temperature, the most important variable in the SDMs across the different resolutions, did not contribute any substantial improvement. Our results suggest that improving resolution of topographic data only is not sufficient to improve SDM predictions – and therefore local management – compared to previously used resolutions (here 25 and 100 m). More effort should be dedicated now to conduct finer-scale in-situ environmental measurements (e.g. for temperature, moisture, snow) to obtain improved environmental measurements for fine-scale species mapping and management.

Field Margin Weed-Species Diversity in Relation to Landscape Attributes and Adjacent Land Use

Weed Science ◽  
2007 ◽  
Vol 55 (2) ◽  
pp. 129-136 ◽  
Author(s):  
Lynn M. Sosnoskie ◽  
Edward C. Luschei ◽  
Mark A. Fanning
Keyword(s):  
Land Use ◽  
Species Richness ◽  
Agricultural Landscape ◽  
Elevation Gradient ◽  
Shape Index ◽  
Diversity Indices ◽  
Weed Species ◽  
Field Margin ◽  
Local Climate ◽  
Modeling Strategy

The importance of managing weeds in seminatural habitats that are adjacent to farm fields is unclear. Weedy-margin vegetation may harbor pests or pathogens and may ALSo serve as source populations for ongoing immigration of weeds into the field. It is ALSo possible, however, that margin vegetation provides habitat for organisms that consume weed seeds or suppress the likelihood of pest or pathogen outbreak. We examined the nature of margin habitat using spatial-scaling of Weed-Species richness as an ecological assay. In 2003, we recorded the occurrence of weedy species along the perimeters of 63 fields in Wisconsin. The fields were distributed within six counties that differed in topography, geological history, local climate, and soil type and which spanned the range of variability in the agricultural landscape. We identified seven habitats that differed in geology and land use. The relationship between species richness and margin class was estimated using an analog of the power law. Additionally, we investigated broadscale correlates of habitat heterogeneity at the field level, using a modeling strategy that included additional explanatory factors logically connected to plant diversity. Using a model-confrontation approach, the survey supported the inclusion of two topographical diversity indices, elevation gradient and a field-shape index, into our model. Our broadscale survey provides information on one of a suite of important considerations needed to make decisions about the importance of managing weeds in field margins.

scholarly journals Structure of three subtropical bat assemblages (Chiroptera) in the Andean rainforests of Argentina

Mammalia ◽  
2016 ◽  
Vol 80 (1) ◽  
Author(s):  
Mariano S. Sánchez
Keyword(s):  
Species Richness ◽  
Relative Abundance ◽  
Seasonal Changes ◽  
Common Species ◽  
Guild Structure ◽  
Trophic Guild ◽  
Long Tail ◽  
Mist Net ◽  
Yungas Forests

AbstractI evaluated bat assemblages in terms of species richness, relative abundance, trophic guild structure, and seasonal changes at three sites along of the Southern Yungas forests. A total of 854 individuals were captured, representing 25 species of three families, with an effort of 27,138 m of mist net opened per hour. Subtropical assemblages showed a similar structure to those from tropical landmark, with a dominance of frugivorous Phyllostomid; in addition, a few species were abundant, followed by a long tail of less common species. However, subtropical sites differed due to the dominance of the genus

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