Cost-distance analysis of mesopredators as a tool for avian habitat restoration on a naturally fragmented landscape

2015 ◽  
Vol 79 (2) ◽  
pp. 220-234 ◽  
Author(s):  
John H. Porter ◽  
Raymond D. Dueser ◽  
Nancy D. Moncrief
Keyword(s):  
Habitat Restoration ◽  
Fragmented Landscape ◽  
Distance Analysis ◽  
Cost Distance

Diet of the squirrel glider in a fragmented landscape near Mackay, central Queensland

2009 ◽  
Vol 57 (5) ◽  
pp. 295 ◽  
Author(s):  
Tina Ball ◽  
Eddie Adams ◽  
Ross L. Goldingay
Keyword(s):  
Tree Species ◽  
Habitat Restoration ◽  
Species Differences ◽  
Geographic Range ◽  
Diet Analysis ◽  
Fragmented Landscape ◽  
Main Food ◽  
Faecal Samples ◽  
Sap Feeding ◽  
Squirrel Glider

We investigated the diet of the squirrel glider (Petaurus norfolcensis) from within a highly fragmented landscape in the northern (tropical) part of its geographic range where information was absent. We analysed 86 faecal samples of 53 gliders from 11 locations and obtained 97 observations of 10 gliders feeding at two locations. Pollen of Eucalyptus/Corymbia was present in 70% and Melaleuca in 20% of faecal samples. Indicators of sap feeding were present in 44% of samples and seeds were present in 14% of samples. Invertebrates, mostly moth larvae, were present in 54% of samples. Observations of gliders feeding revealed that the main food types were invertebrates (36% of observations), nectar and pollen (27% of observations) and sap (26% of observations) of five tree species. Differences in the use of the major food types revealed by the two methods of diet analysis partly reflect site-based differences. Qualitatively, the diet was similar to that described in southern Australia, with confirmation that sap may be important at some locations. Our results reveal the contribution that different tree species make to the diet, which should be used to guide habitat restoration for the squirrel glider in this fragmented landscape.

scholarly journals Olive Landscape Affects Bactrocera Oleae Abundance, Movement and Damage

2021 ◽  
Author(s):  
Marta Quero Ortega ◽  
Natalia Moreno ◽  
Cristina E. Fernández ◽  
Susana Pascual
Keyword(s):  
Landscape Structure ◽  
Fruit Fly ◽  
Bactrocera Oleae ◽  
Olive Fruit Fly ◽  
Olive Grove ◽  
Olive Fruit ◽  
Distance Analysis ◽  
Cost Distance ◽  
Olive Groves ◽  
The Relationship

Abstract The olive fruit fly, Bactrocera oleae (Rossi) (Diptera: Tephritidae), is a key pest of olive groves. Because of its economic importance and problems associated with chemical control, new approaches to reduce the damage caused by this pest and a deeper knowledge of the biology of the insect and the relationship of landscape structure to different biological parameters are needed. B. oleae can fly long distances and its ability to move within the landscape can determine the damage caused to olive groves. This work evaluates the effect of landscape structure on olive fruit fly abundance, movements and damage at three times of year—spring, early autumn and late autumn—in central Spain. This area is less dominated by olive groves than southern Spain, where the relationship between olive grove area and B. oleae abundance is already known. A cost-distance analysis is used to evaluate the landscape effect on the movement of the fly along the crop cycle. The olive grove area is the landscape composition factor with the greatest effect on the parameters studied, with a decrease in B. oleae abundance in a more complex landscape during spring and early autumn. The cost-distance analysis shows that the olive fruit fly moves mainly in spring, and amongst olive groves. There is no evidence that land uses other than olive groves serve as a summer refuge for B.oleae in the studied landscape context. Olive grove area and land use diversity index had significant effects on olive damage in more than one year.

Least cost distance analysis for spatial interpolation

2011 ◽  
Vol 37 (2) ◽  
pp. 272-276 ◽  
Author(s):  
Jonathan A. Greenberg ◽  
Carlos Rueda ◽  
Erin L. Hestir ◽  
Maria J. Santos ◽  
Susan L. Ustin
Keyword(s):  
Spatial Interpolation ◽  
Distance Analysis ◽  
Cost Distance

scholarly journals Does the accessibility of a farmer predict the delivery of extension services? Evidence from Rwanda

2021 ◽  
pp. 003072702110538
Author(s):  
Michel Kabirigi
Keyword(s):  
Typical Case ◽  
Extension Agents ◽  
Suitable Model ◽  
Extension Services ◽  
Distance Analysis ◽  
Cost Distance ◽  
Study Support ◽  
Management Advisory ◽  
Significant Factors ◽  
Banana Xanthomonas Wilt

To determine whether a farmer’s accessibility predicts the delivery of extension services, this study used banana Xanthomonas wilt (BXW) disease-management advisory as a typical case with which to collect extension-delivery information from 690 farmers, distinguished by their respective accessibility. Cost–distance analysis was applied to define each farmer’s accessibility. The results revealed that a farmer’s accessibility does not predict extension delivery to that farmer in all forms of the examined extension parameters. Significant factors contributing to the delivery of extension services included BXW incidence and membership in Twigire Muhinzi groups. Given the results of this paper, I argue that the nature of the advisory and the type of farmers’ networks are more predictive factors than physical proximity. The findings of this study support the argument that the group-based extension approach is more effective; therefore, the Twigire Muhinzi initiative is recommended as a suitable model for delivering agricultural advisory services. The absence of a significant association between extension delivery and distance (accessibility) suggests that extension agents do not follow the first-reached, first-served rule but instead follow the problem-solving-based approach.

scholarly journals Reintroduction or natural colonization? Using cost-distance analysis to inform decisions about Rodrigues Island Fody and Warbler reintroductions

2017 ◽  
Vol 21 (2) ◽  
pp. 110-119 ◽  
Author(s):  
O. A. M. Davies ◽  
A. E. Huggins ◽  
J. A. Begue ◽  
J. J. Groombridge ◽  
C. Jones ◽  
...  
Keyword(s):  
Distance Analysis ◽  
Cost Distance

scholarly journals Olive Landscape Affects Bactrocera oleae Abundance, Movement and Infestation

Agronomy ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 4
Author(s):  
Marta Ortega ◽  
Natalia Moreno ◽  
Cristina E. Fernández ◽  
Susana Pascual
Keyword(s):  
Landscape Structure ◽  
Diversity Index ◽  
Bactrocera Oleae ◽  
Biological Knowledge ◽  
Olive Fruit Fly ◽  
Land Uses ◽  
Landscape Complexity ◽  
Distance Analysis ◽  
Cost Distance ◽  
Olive Groves

The economic importance of Bactrocera oleae (Rossi) and the problems associated with insecticides make necessary new management approaches, including deeper biological knowledge and its relationship with landscape structure. Landscape complexity reduces B. oleae abundance in late summer–autumn in areas of high dominance of olive groves, but the effect of landscape structure in spring and in areas less dominated by olive groves has not been studied. It is also unknown whether the insect disperses from olive groves, using other land uses as a refugee in summer. This work evaluates the effect of landscape structure on olive fruit fly abundance and movement in spring and autumn, and infestation in autumn, in central Spain, an area where the olive crop does not dominate the landscape. A cost–distance analysis is used to evaluate the movement of the fly, especially trying to know whether the insects move away from olive groves in summer. The results indicate that B. oleae abundance is consistently lower in complex landscapes with high scrubland area (CAS), patch richness (PR) and Simpson landscape diversity index (SIEI), and low olive grove area (CAO). The cost–distance analysis shows that the fly moves mainly in spring, and amongst olive groves, but there is no evidence that land uses other than olive groves serve as a summer refuge. Olive fly infestation decreased with decreasing CAO and increasing CAS and SIEI, accordingly with the effect of landscape on abundance. Thus, mixing olive groves with other land uses, which are not a source of flies, can help improve control of this important pest.

scholarly journals Methods of Measuring Spatial Accessibility to Health Care in Uganda

2021 ◽  
pp. 77-90
Author(s):  
Paul Ouma ◽  
Peter M. Macharia ◽  
Emelda Okiro ◽  
Victor Alegana
Keyword(s):  
Health Care ◽  
Travel Time ◽  
Access To Health Care ◽  
Spatial Accessibility ◽  
Weather Patterns ◽  
Distance Analysis ◽  
Cost Distance ◽  
Access To Health ◽  
Sub Saharan ◽  
Population Ratio

AbstractEnsuring everyone has access to health care regardless of demographic, geographic and social economic status is a key component of universal health coverage. In sub-Saharan Africa, where populations are often sparsely distributed and services scarcely available, reducing distances or travel time to facilities is key in ensuring access to health care. This chapter traces the key concepts in measuring spatial accessibility by reviewing six methods—Provider-to-population ratio, Euclidean distance, gravity models, kernel density, network analysis and cost distance analysis—that can be used to model spatial accessibility. The advantages and disadvantages of using each of these models are also laid out, with the aim of choosing a model that can be used to capture spatial access. Using an example from Uganda, a cost distance analysis is used to model travel time to the nearest primary health care facility. The model adjusts for differences in land use, weather patterns and elevation while also excluding barriers such as water bodies and protected areas in the analysis. Results show that the proportion of population within 1-h travel times for the 13 regions in the country varies from 64.6% to 96.7% in the dry period and from 61.1% to 96.3% in the wet period. The model proposed can thus be used to highlight disparities in spatial accessibility, but as we demonstrate, care needs to be taken in accurate assembly of data and interpreting results in the context of the limitations.

HABITAT RESTORATION

1994 ◽  
Vol 12 (2) ◽  
pp. 215.2-215
Keyword(s):  
Habitat Restoration
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