Modeling Landscape Level Forest Disturbance-Conservation Implications

2021 ◽  
pp. 67-83
Author(s):  
Mukunda Dev Behera
Oryx ◽  
2004 ◽  
Vol 38 (4) ◽  
pp. 404-409 ◽  
Author(s):  
Mwangi Githiru ◽  
Luc Lens

Fragmentation of forests adversely affects forest-dependent biota, and conservation biologists strive to develop a good understanding of how species respond to changes associated with habitat attrition in order to establish the best conservation strategies. The spatial structure of populations persisting in fragmented landscapes governs their response to habitat fragmentation, and hence dictates the remedial actions that will be most effective for species and habitat conservation. The Taita Hills forests of Kenya are an example of a highly fragmented Afrotropical forest ecosystem embedded in a human-dominated landscape. The spatial structure of the white-starred robin Pogonocichla stellata populations living in indigenous forests across this landscape was examined. Due to its forest dependence and widespread occurrence, the robin was used as a model species to help formulate general conservation guidelines for forest-dependent species and their habitats within this landscape. Results from demographic, genetic and behavioural work point to a mixed spatial structure with elements of patchy population dynamics on a fine scale, and a core-satellite or source-pseudo-sink system on a broader scale. In particular, the findings underscore (1) the importance of dispersal, (2) the importance of small patches, (3) the importance of the largest patch, and (4) the processes underlying problems associated with forest disturbance. We examine the conservation implications of this information, and report on activities already initiated or planned, in line with these findings, for the Taita Hills.


10.1596/25764 ◽  
2016 ◽  
Author(s):  
Andrew Martin Tarter ◽  
Katie Kennedy Freeman ◽  
Klas Sander

2003 ◽  
Author(s):  
Michael A. Larson ◽  
William D. Dijak ◽  
Frank R. III Thompson ◽  
Joshua J. Millspaugh

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Prayuth Sudathip ◽  
Suravadee Kitchakarn ◽  
Jui A. Shah ◽  
Donal Bisanzio ◽  
Felicity Young ◽  
...  

Abstract Background Thailand’s success in reducing malaria burden is built on the efficient “1-3-7” strategy applied to the surveillance system. The strategy is based on rapid case notification within 1 day, case investigation within 3 days, and targeted foci response to reduce the spread of Plasmodium spp. within 7 days. Autochthonous transmission is still occurring in the country, threatening the goal of reaching malaria-free status by 2024. This study aimed to assess the effectiveness of the 1-3-7 strategy and identify factors associated with presence of active foci. Methods Data from the national malaria information system were extracted from fiscal years 2013 to 2019; after data cleaning, the final dataset included 81,012 foci. A Cox’s proportional hazards model was built to investigate factors linked with the probability of becoming an active focus from 2015 to 2019 among foci that changed status from non-active to active focus during the study period. We performed a model selection technique based on the Akaike Information Criteria (AIC). Results The number of yearly active foci decreased from 2227 to 2013 to 700 in 2019 (68.5 %), and the number of autochthonous cases declined from 17,553 to 3,787 (78.4 %). The best Cox’s hazard model showed that foci in which vector control interventions were required were 18 % more likely to become an active focus. Increasing compliance with the 1-3-7 strategy had a protective effect, with a 22 % risk reduction among foci with over 80 % adherence to 1-3-7 timeliness protocols. Other factors associated with likelihood to become or remain an active focus include previous classification as an active focus, presence of Plasmodium falciparum infections, level of forest disturbance, and location in border provinces. Conclusions These results identified factors that favored regression of non-active foci to active foci during the study period. The model and relative risk map align with the national malaria program’s district stratification and shows strong spatial heterogeneity, with high probability to record active foci in border provinces. The results of the study may be useful for honing Thailand’s program to eliminate malaria and for other countries aiming to accelerate malaria elimination.


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