Identification of key environmental variables associated with the presence of Toothed Leionema (Leionema bilobum serrulatum) in the Strzelecki Ranges, Victoria, Australia

2011 ◽  
Vol 59 (3) ◽  
pp. 207
Author(s):  
Wendy Wright ◽  
Xuan Zhu ◽  
Mateusz Okurowski
Keyword(s):  
Environmental Factors ◽  
Habitat Suitability ◽  
Rare Species ◽  
Environmental Variables ◽  
Geographical Information Systems ◽  
Predictive Modelling ◽  
Geographical Information ◽  
Suitable Habitat ◽  
Small Tree ◽  
Disturbed Areas

Toothed Leionema is one of four subspecies of Leionema bilobum from the Rutaceae family. A dense shrub or small tree, growing to ~4 m high, it is a poorly investigated species which is considered rare in Victoria, Australia. This paper presents the results of a study using Geographical Information Systems and Weights-of-Evidence predictive modelling to assess the importance of seven environmental factors in determining habitat suitability for this species in the Strzelecki Ranges, Victoria. This method is particularly useful in understanding the distribution of rare species, especially where the ecology of the species of interest is not well understood. Of the seven environmental factors considered here, four were found to be important: elevation, aspect, distance to water and distance to plantation (disturbed) areas. The modelling results indicate that areas with elevations between 350 and 550 m and a dominant south-western aspect that are close to plantation areas (within 700 m), and to water (within 1100–1200 m), provide potentially suitable habitat for Toothed Leionema in the region.

scholarly journals Prediction of leopard habitat suitability in Taman Negara main forest complex, Malaysia

2021 ◽  
Vol 42 (3(SI)) ◽  
pp. 806-811
Author(s):  
N.F. Khodri ◽  
◽  
T. Lihan ◽  
M.A. Mustapha ◽  
T.M. Taher ◽  
...  
Keyword(s):  
Land Use ◽  
Habitat Suitability ◽  
Wildlife Conservation ◽  
Environmental Parameters ◽  
Geographical Information ◽  
Urban Habitat ◽  
Suitable Habitat ◽  
Habitat Suitability Modeling ◽  
Presence Data ◽  
Gis Data

Aim: This research assessed the distribution of leopard to predict the habitat suitability in Taman Negara National Park and adjacent forest area. Methodology: Environmental factors for habitat suitability were derived from geographical information system (GIS) data such as elevation, slope, land-use, distance from urban and distance from river. Leopard presence data from 1993 to 2008 were integrated with the environmental parameters using maximum entropy (MaxEnt) modeling to assess habitat suitability across the study area. Results: The results showed that distance from river contributed the most (39.3%) in the habitat suitability modeling followed by distance from urban (31.4%), elevation (12.3%), land use types (10.1%), and slope (6.9%). Distance from river and urban showed highest contribution that influenced leopard distribution in which most suitable habitat occurred in proximity with river and further from urban. Habitat suitability of leopard were distributed among 48% over 2,218,389 ha of the study area. Interpretation: The findings of this study provides knowledge on how the species move and exploit different habitat niches for more effective conservation management. It provide models for future wildlife conservation and urban planning.

scholarly journals The Importance of Environmental Factors for the Development of Water Erosion of Soil in Agricultural Land: The Southern Part of Hronská Pahorkatina Hill Land, Slovakia

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1234
Author(s):  
Viera Petlušová ◽  
Peter Petluš ◽  
Michal Ševčík ◽  
Juraj Hreško
Keyword(s):  
Land Use ◽  
Environmental Factors ◽  
Geographical Information Systems ◽  
Agricultural Land ◽  
Land Use Changes ◽  
Water Erosion ◽  
Geographical Information ◽  
Aerial Photographs ◽  
Slope Length ◽  
Erosion Processes

The water erosion research was carried out in the lowland type of hilly landscape. The aim was to monitor and evaluate the importance of environmental factors (steepness of slope, relief shapes, aspect, slope length, combination slope length (L) and slope (S)—LS factor, types of land use changes) for the development of water erosion. We focused on the identification of areas threatened by erosion by interpreting aerial photographs from several time periods. This was followed by verification of erosion using soil probes. We identified 408.44 ha of areas affected by erosion, and measured the depth of soil and “A” horizons thickness. The environmental factors were modeled in geographical information systems by tools for spatially oriented data. Subsequently, the influence and significance of individual environmental factors were compared, and the probability of erosion was statistically estimated. The decisive factors in the formation of erosive surfaces are the LS factor and the slope. We also consider the factor of the relief shape to be important. The shape did not appear to be very significant as a separately evaluated factor, but all convex parts correlate with the identified erosion surfaces. The susceptibility of erosion related to the aspect of the slopes to the cardinal directions has not been confirmed. Types of land use changes with the most significant relation of erosion were confirmed in areas of strong intensification. We confirmed the importance of factors and land use for the development of erosion processes.

scholarly journals Distance from Healthcare Facilities Is Associated with Increased Morbidity of Acute Infection in Pediatric Patients in Matiari, Pakistan

2021 ◽  
Vol 18 (21) ◽  
pp. 11691
Author(s):  
Elise Corden ◽  
Saman Hasan Siddiqui ◽  
Yash Sharma ◽  
Muhammad Faraz Raghib ◽  
William Adorno ◽  
...  
Keyword(s):  
Random Forest ◽  
Environmental Factors ◽  
Geographical Information Systems ◽  
Pearson Correlation ◽  
Acute Infection ◽  
Disease Prevalence ◽  
Geographical Information ◽  
Continuous Variables ◽  
Gis Technology ◽  
Healthcare Facilities

The relationship between environmental factors and child health is not well understood in rural Pakistan. This study characterized the environmental factors related to the morbidity of acute respiratory infections (ARIs), diarrhea, and growth using geographical information systems (GIS) technology. Anthropometric, address and disease prevalence data were collected through the SEEM (Study of Environmental Enteropathy and Malnutrition) study in Matiari, Pakistan. Publicly available map data were used to compile coordinates of healthcare facilities. A Pearson correlation coefficient (r) was used to calculate the correlation between distance from healthcare facilities and participant growth and morbidity. Other continuous variables influencing these outcomes were analyzed using a random forest regression model. In this study of 416 children, we found that participants living closer to secondary hospitals had a lower prevalence of ARI (r = 0.154, p < 0.010) and diarrhea (r = 0.228, p < 0.001) as well as participants living closer to Maternal Health Centers (MHCs): ARI (r = 0.185, p < 0.002) and diarrhea (r = 0.223, p < 0.001) compared to those living near primary facilities. Our random forest model showed that distance has high variable importance in the context of disease prevalence. Our results indicated that participants closer to more basic healthcare facilities reported a higher prevalence of both diarrhea and ARI than those near more urban facilities, highlighting potential public policy gaps in ameliorating rural health.

Identifying Potential Habitat for the Endangered Aleutian Shield Fern Using Topographical Characteristics

2012 ◽  
Vol 3 (2) ◽  
pp. 303-310
Author(s):  
Adam Duarte ◽  
Daniel M. Wolcott ◽  
T. Edwin Chow ◽  
Mark A. Ricca
Keyword(s):  
Habitat Suitability ◽  
Habitat Characteristics ◽  
Geographical Information ◽  
Slope Aspect ◽  
Suitable Habitat ◽  
Gis Model ◽  
Potential Habitat ◽  
Suitability Map ◽  
Habitat Suitability Map ◽  
The U.S

Abstract The Aleutian shield fern Polystichum aleuticum is endemic to the Aleutian archipelago of Alaska and is listed as endangered pursuant to the U.S. Endangered Species Act. Despite numerous efforts to discover new populations of this species, only four known populations are documented to date, and information is needed to prioritize locations for future surveys. Therefore, we incorporated topographical habitat characteristics (elevation, slope, aspect, distance from coastline, and anthropogenic footprint) found at known Aleutian shield fern locations into a Geographical Information System (GIS) model to create a habitat suitability map for the entirety of the Andreaonof Islands. A total of 18 islands contained 489.26 km2 of highly suitable and moderately suitable habitat when weighting each factor equally. This study reports a habitat suitability map for the endangered Aleutian shield fern using topographical characteristics, which can be used to assist current and future recovery efforts for the species.

scholarly journals Environmental requirements for three sea pen species: relevance to distribution and conservation

2014 ◽  
Vol 72 (2) ◽  
pp. 576-586 ◽  
Author(s):  
C. Greathead ◽  
J. M. González-Irusta ◽  
J. Clarke ◽  
P. Boulcott ◽  
L. Blackadder ◽  
...  
Keyword(s):  
Protected Areas ◽  
Marine Protected Areas ◽  
Habitat Suitability ◽  
Environmental Variables ◽  
Suitable Habitat ◽  
Habitat Suitability Index ◽  
Suitability Index ◽  
Environmental Requirements ◽  
Adequacy Criterion ◽  
Suitable Area

Abstract The aim is to determine the environmental requirements, estimate the extent of suitable habitat for three sea pen species, and assess the implications for marine protected areas (MPAs). The sea pen Funiculina quadrangularis and the habitat associated with two further sea pen species, Virgularia mirabilis and Pennatula phosphorea, are of key conservation importance and are recommended for protection within MPAs. This study models their potential distributions using the MAXimum ENTropy algorithm and assesses these in relation to five possible marine protected areas (pMPAs) proposed for Scottish waters. Metrics relevant to assessing the efficacy of MPAs are also presented. Four environmental variables of prime importance for predicting the presence of all three species of sea pen were identified: mud, minimum salinity, depth, and gravel. The habitat suitability index increased with mud content. The modelled distribution of F. quadrangularis indicated a deeper distribution than V. mirabilis or P. phosphorea and was not present in sediment with gravel content above 30%. Pennatula phosphorea had the smallest area of suitable habitat, while V. mirabilis had the largest. The percentage predicted suitable area for each species that was encompassed by the five pMPAs ranged from 11% for F. quadrangularis to 15% for P. phosphorea. Some of the largest areas predicted as suitable for F. quadrangularis lay outside the pMPAs. The model results indicated differences in the environmental requirements of the three species of sea pen that can be linked to the autecology of each species. Patch sizes, calculated from a binary output of the model, were used to estimate the degree of habitat fragmentation, thereby giving a partial assessment of the adequacy criterion for these pMPAs. The results suggest that potential MPAs within the study area cover sizeable areas of potential sea pen habitat. However, further areas suitable for F. quadrangularis could be considered.

scholarly journals Environmental, climatic and host population risk factors of human cystic echinococcosis in southwest of Iran

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Mohammad Amin Ghatee ◽  
Koorosh Nikaein ◽  
Walter Robert Taylor ◽  
Mehdi Karamian ◽  
Hasan Alidadi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Environmental Factors ◽  
Cystic Echinococcosis ◽  
Geographical Information Systems ◽  
Urban Setting ◽  
Geographical Information ◽  
Annual Rainfall ◽  
Fars Province ◽  
Susceptible Population ◽  
Close Proximity

Abstract Background Cystic echinococcosis (CE), a worldwide zoonotic disease, is affected by various biological and environmental factors. We investigated dog/livestock populations, climatic and environmental factors influencing the distribution of human CE cases in Fars province, southwest Iran. Methods We mapped the addresses of 266 hospitalised CE patients (2004–2014) and studied the effects of different temperature models, mean annual rainfall and humidity, number of frosty days, slope, latitude, land covers, close proximity to nomads travel routes, livestock and dog densities on the occurrence of CE using geographical information systems approach. Data were analyzed by logistic regression. Results In the multivariate model predicting CE, living in an urban setting and densities of cattle and dogs were the most important CE predictors, sequentially. Dry (rained) farm, density of camel and sheep, close proximity to nomads travel routes, humidity, and slope also were considered as the determinants of CE distribution, when analyzed independently. Slope had a negative correlation with CE while temperature, frost days and latitude were not associated with CE. Conclusions In our study, an urban setting was the most important risk factor and likely due to a combination of the high density of key life cycle hosts, dogs and livestock, a large human susceptible population and the high number of abattoirs. Farmland and humidity were highly suggestive risk factors and these conditions support the increased survival of Echinococcus granulosus eggs in the soil. These findings support the development of strategies for control of disease. More research is needed test optimal interventions.

scholarly journals Environmental factor analysis of cholera in China using remote sensing and geographical information systems

2015 ◽  
Vol 144 (5) ◽  
pp. 940-951 ◽  
Author(s):  
M. XU ◽  
C. X. CAO ◽  
D. C. WANG ◽  
B. KAN ◽  
Y. F. XU ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Information Systems ◽  
Environmental Factors ◽  
Geographical Information Systems ◽  
Chlorophyll Concentration ◽  
Warning System ◽  
Sea Surface ◽  
Geographical Information ◽  
Natural Environments ◽  
Rs And Gis

SUMMARYCholera is one of a number of infectious diseases that appears to be influenced by climate, geography and other natural environments. This study analysed the environmental factors of the spatial distribution of cholera in China. It shows that temperature, precipitation, elevation, and distance to the coastline have significant impact on the distribution of cholera. It also reveals the oceanic environmental factors associated with cholera in Zhejiang, which is a coastal province of China, using both remote sensing (RS) and geographical information systems (GIS). The analysis has validated the correlation between indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local number of cholera cases based on 8-year monthly data from 2001 to 2008. The results show the number of cholera cases has been strongly affected by the variables of SST, SSH and OCC. Utilizing this information, a cholera prediction model has been established based on the oceanic and climatic environmental factors. The model indicates that RS and GIS have great potential for designing an early warning system for cholera.

scholarly journals Geographically weighted regression modelling of the spatial association between malaria cases and environmental factors in Cameroon.

2019 ◽  
Author(s):  
Marlvin Anemey Tewara ◽  
Liu Yunxia ◽  
Weiqiang Lin ◽  
Binang Helen Barong ◽  
Prisca Ngetemalah Mbah-Fongkimeh ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Spatial Variability ◽  
Least Squares ◽  
Geographically Weighted Regression ◽  
Environmental Variables ◽  
Spatial Association ◽  
Ordinary Least Squares ◽  
Geographical Information ◽  
Weighted Regression ◽  
Gwr Model

Abstract Background: Studies have illustrated the association of malaria cases with environmental factors in Cameroon but limited in addressing how these factors vary in space for timely public health interventions. Thus, we want to find the spatial variability between malaria hotspot cases and environmental predictors using Geographically weighted regression (GWR) spatial modelling technique. Methods: The global Ordinary least squares(OLS) in the modelling spatial relationships tool in ArcGIS 10.3. was used to select candidate explanatory environmental variables for a properly specified GWR model. The local GWR model used the global OLS candidate variables to examine, predict and explore the spatial variability between environmental factors and malaria hotspot cases generated from Getis-Ord Gi* statistical analysis. Results: The OLS candidate environmental variable coefficients were statistically significant ( adjusted R 2 = 22.3% and p < 0.01) for a properly specified GWR model. The GWR model identified a strong spatial association between malaria cases and rainfall, vegetation index, population density, and drought episodes in most hotspot areas and a weak correlation with aridity and proximity to water with an overall model performance of 0.243 (adjusted R 2 = 24.3%). Conclusion: The generated GWR maps suggest that for policymakers to eliminate malaria in Cameroon, there should be the creation of malaria outreach programs and further investigations in areas where the environmental variables showed strong spatial associations with malaria hotspot cases . Keywords: Geographically weighted regression, Ordinary least squares, malaria, spatial statistics, mapping, Geographical information systems.

scholarly journals Predicting habitat suitability of Selaginella adunca A.Br. ex Hieron., an endangered and endemic fern-allies of Western Himalaya

2020 ◽  
Vol 7 (3) ◽  
pp. 547-552
Author(s):  
Amber Srivastava ◽  
Keyword(s):  
Habitat Suitability ◽  
Rare Species ◽  
Ecological Niche ◽  
Habitat Type ◽  
Western Himalaya ◽  
Suitable Habitat ◽  
Anthropogenic Pressure ◽  
Niche Modelling ◽  
Maxent Model ◽  
Preferred Habitat

Selaginella adunca is a quite distinct and rare species of Selaginella found in Western Himalaya. This species is reported only from few populations occurring in India and Nepal. Since most of its reported habitats are under anthropogenic pressure, therefore for proper conservation of this species it is necessary to mark the suitable habitat for its conservation and reintroduction. The present study was aimed to find out the suitable habitat of this species through ecological niche modelling (ENM) technique using Maxent model. This will also help in relocating the species in other preferred habitat type and its reintroduction as well.

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