Agriculture is the primary driver of tree cover loss across the Forestière region of the Republic of Guinea, Africa

Abstract Biodiversity hotspots are conservation priority areas that feature exceptionally high levels of species endemism and high levels of habitat loss. The Guinean Forests of West Africa hotspot, home to a quarter of all the mammal species of Africa, has experienced high levels of forest loss within its protected areas. Here, we analyzed tree cover loss and its proximate drivers within Guinée Forestière, a high biodiversity region within the Guinean Forests of West Africa hotspot, both inside and outside protected areas. Using Landsat analysis ready data and a regionally calibrated, annual forest change detection model, we mapped tree cover loss occurring across this region from 2000 to 2018. We quantified the area of tree cover loss and identified proximate drivers using a statistical sample of reference data. The total tree cover loss in Guinée Forestière between years 2000 and 2018 was 10,907 km2 (SE 889 km2), which consists of approximately 25% of the region’s total land area. Of this total loss, 364 km2 (SE 91 km2) occurred within protected areas of high biodiversity value. Tree cover loss was not consistent across high biodiversity areas and did not appear to be related to protected area classification. Smallholder agriculture (subsistence and cash crop farming) was the primary driver of tree cover loss across Guinée Forestière. This research provides multitemporal spatial data on tree cover dynamics that is required for effective implementation of sustainable management and biodiversity conservation strategies within the broader socioecological landscape of Guinée Forestière. We also highlight important limitations to consider and address when using remote sensing to automate change detection across landscapes.

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Identifying priority areas for the conservation of antelopes in the Republic of Guinea, West Africa, using the complementarity approach

Oryx ◽

10.1017/s0030605311000391 ◽

2012 ◽

Vol 46 (2) ◽

pp. 253-259 ◽

Cited By ~ 4

Author(s):

David Brugière

Keyword(s):

West Africa ◽

Protected Areas ◽

Protected Area ◽

Conservation Strategies ◽

Area Network ◽

Mammal Species ◽

Protected Area Network ◽

Republic Of Guinea ◽

Complementarity Approach ◽

The Republic

AbstractThe Republic of Guinea has one of the highest diversities of mammal species in West Africa. However, its protected area network is poorly developed and little quantitative information has been available to help guide national conservation strategies. I therefore examined the distribution of antelopes and related species (families Bovidae and Tragulidae) across 17 sites, including four protected areas, to determine how the existing protected area network contributes to the conservation of antelope species and where action should best be focused for the conservation of this group. A total of 21 species of antelope have been recorded in the 17 sites; four of these species are absent from the four protected areas. An iterative heuristic complementarity approach was used to determine an irreplaceability index, which accounts for both species richness and species rarity, for each of the sites. The Kankan Faunal Reserve and Nimba Strict Nature Reserve have the second and fourth highest irreplaceability indices, respectively. The two other protected areas have moderate to very low irreplaceability indices, showing that they protect species widespread throughout the 17 sites. The Ziama Forest has the highest index (because it contains a high number of species and of globally threatened species), highlighting the significance of this site. I discuss the importance of the other sites and the threats affecting antelopes in Guinea, and make recommendations to improve the study and conservation of antelope species in the country.

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Forest change detection based on sub-pixel tree cover estimates using Landsat-OLI and Sentinel 2 data

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/507/1/012011 ◽

2020 ◽

Vol 507 ◽

pp. 012011

Author(s):

T Khovratovich ◽

S Bartalev ◽

A Kashnitskii ◽

I Balashov ◽

A Ivanova

Keyword(s):

Change Detection ◽

Tree Cover ◽

Forest Change ◽

Sentinel 2

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APPLICATION GIS AND WEBGIS TECHNOLOGY FOR BIODIVERSITY INFORMATION MANAGEMENT A CASE STUDY IN XUAN LIEN NATURE RESERVE

Vietnam Journal of Science and Technology ◽

10.15625/0866-708x/54/4/7356 ◽

2016 ◽

Vol 54 (4) ◽

pp. 460

Author(s):

Ha Quy Quynh ◽

Dang Huy Phuong ◽

Nguyen Tien Phuong

Keyword(s):

Protected Areas ◽

National Parks ◽

Spatial Data ◽

Nature Reserve ◽

Biological Database ◽

Biodiversity Data ◽

Mammal Species ◽

Zonation Map ◽

The Status ◽

Biodiversity Database

Resource management in National parks (NP), Nature reserve (NR) aim to hold the status of biological resources of the area [4]. Up to now, Vietnam has established 31 NP and about 100 NR. Most of NR, NP was completed build biological database [4]. The traditional information sharing method has showed the limitations, causing many difficulties for the users, particularly when exploring the map information. WebGIS technology developed quickly with the functions included: internet access, query spatial data in the Internet, which has promoted the possibility aid, consult spatial data, link between tables and map [1, 5, 7]. Biodiversity Database of Xuan Lien NR was built based on tables and maps. The table database is designed as relational data, including the information and records. With animals is Class - Order - Family – Species and plants is Plant - Phylum - Family - Species. The code of the species included 4 parts. One part of character and 3 parts of numbers. The database are the records of 1142 plant species, 55 mammal species, 190 birds, 38 reptiles and 35 amphibians species. The map database include base map, zonation map, infrastructure maps, vegetation and distribution map of species in protected areas. Display Biodiversity data of NR by MapServer, showing base map, zonation map, infrastructure maps, vegetation and habitat map. Using the combined technologies of Remote Sensing, GIS and WebGIS to manage, display, sharing biodiversity data of NR promotion optimization capabilities in data analyses and combined tables with map. This technology may apply for management biodiversity database of all protected areas in Vietnam.

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Non-protected areas demanding equitable conservation strategies as of protected areas in the Central Himalayan region

PLoS ONE ◽

10.1371/journal.pone.0255082 ◽

2021 ◽

Vol 16 (8) ◽

pp. e0255082

Author(s):

Avantika Thapa ◽

Pujan Kumar Pradhan ◽

Bheem Dutt Joshi ◽

Tanoy Mukherjee ◽

Mukesh Thakur ◽

...

Keyword(s):

Species Richness ◽

Protected Areas ◽

Protected Area ◽

Mammalian Species ◽

Capture Rate ◽

Canopy Cover ◽

Camera Traps ◽

Conservation Strategies ◽

Mammal Species ◽

Manis Pentadactyla

The present study aims to explore the mammalian diversity of Darjeeling district using camera traps along with questionnaire survey in protected area (PA) and non- protected area (Non-PA). We also attempted to understand the influence of habitat variables on mammalian species richness using the generalized linear mixed models (GLMM). A total of 30 mammal species were recorded of which 21 species were detected through camera trapping with the most abundant records of barking deer (Muntiacus muntjak) and least of the elusive Chinese pangolin (Manis pentadactyla) and red panda (Ailurus fulgens). Additionally, melanistic forms of four mammals were also recorded. The mammalian species richness, their capture rate and naïve occupancy did not differ significantly among the PA and Non-PA. The GLMM revealed that the proportions of oak and bamboo in the forest, percentage canopy cover and camera trap operational days (wAICc = 0.145, wBIC = 0.603) were significant predictors of species richness in the study. We suggest Non-PA forest of Darjeeling should be given equal conservation importance as to the PA. Landscape based conservation planning will be imperative for achieving long term conservation goals in the study area.

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Forest change within and outside protected areas in the Dominican Republic, 2000-2016

10.1101/558346 ◽

2019 ◽

Cited By ~ 2

Author(s):

John D. Lloyd ◽

Yolanda M. León

Keyword(s):

Dominican Republic ◽

Protected Areas ◽

Large Scale ◽

Cloud Forest ◽

Tree Cover ◽

Forest Loss ◽

Forest Change ◽

Broadleaf Forest ◽

Deforestation Rates ◽

Pinus Occidentalis

AbstractWe used Landsat-based estimates of tree cover change to document the loss and gain of forest in the Dominican Republic between 2000 and 2016. Overall, 2,795 km2 of forest were lost, with forest gain occurring on only 393 km2, yielding a net loss of 2,402 km2 of forest, a decline of 11.1% or 0.7% per year. Deforestation occurred in all of the major forest types in the country, and ranged from a 13% decline in the area of semi-moist broadleaf forest to a 5.9% loss of cloud forest, mostly attributed to agriculture. Fire was a significant driver of forest loss only in Hispaniolan pine (Pinus occidentalis) forests and, to a lesser extent, in adjacent cloud forest. Deforestation rates were lower within protected areas, especially in dry and semi-moist broadleaf forests at lower elevations. Protected areas had a smaller, and generally negligible, effect on rates of forest loss in pine forest and cloud forest, largely due to the effects of several large wildfires. Overall, rates of deforestation in the Dominican Republic were higher than regional averages from across the Neotropics and appeared to have accelerated during the later years of our study period. Stemming deforestation will likely require enforcement of prohibitions on large-scale agricultural production within protected areas and development of alternatives to short-cycle, shifting agriculture.

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Effectiveness of Protected Areas in Conserving the Highly Hunted Mammal Species as Bushmeat in Southern Benin

The Open Ecology Journal ◽

10.2174/1874213001811010014 ◽

2018 ◽

Vol 11 (1) ◽

pp. 14-24

Author(s):

Chabi A.M.S. Djagoun ◽

Etotépé A. Sogbohossou ◽

Barthélémy Kassa ◽

Christian B. Ahouandjinou ◽

Hugues A. Akpona ◽

...

Keyword(s):

Protected Areas ◽

Habitat Degradation ◽

Habitat Type ◽

Cell System ◽

Anthropogenic Factors ◽

Mammal Species ◽

Occupancy Model ◽

Habitat Occupancy ◽

Anthropogenic Habitat ◽

Lama Forest

Background: The habitat degradation together with fragmentation and illegal hunting represent a major threat for biodiversity conservation in Lama protected areas. Method: We used a combination of questionnaire survey with local communities for ranking the hunted mammal species as bushmeat and track surveys in gridded-cell system of 500x500 m2 (n=268) to assess at what extend the management design, the anthropogenic factors and habitat type affect the occupancy model of those mammal species. Results: Twenty mammal species have been predominantly reported by the local inhabitants to consume bushmeat species and 5 of them have been identified as the most preferable as hunted game mammals. The selection of the preferred habitat among the swampy forest, the dense forest, the tree plantations and cropland for the prioritized game species varies between species but looks similar when grouping in different orders. Some bushmeat species were found to select the more secure habitat (natural forest); suggesting the zoning system in the Lama forest can passively protect those species. However, some species such as T. swinderianus although highly hunted showed preference to anthropogenic habitat, avoiding the well secured core zone in Lama Forest. Conclusion: Our findings highlighted the importance of the zoning system with different management objectives in the habitat occupancy model of the highly hunted wildlife species.

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Geospatial information informs bonobo conservation efforts

10.1093/oso/9780198728511.003.0017 ◽

2018 ◽

Author(s):

Janet Nackoney ◽

Jena Hickey ◽

David Williams ◽

Charly Facheux ◽

Takeshi Furuichi ◽

...

Keyword(s):

Spatial Data ◽

Pan Paniscus ◽

Democratic Republic Of Congo ◽

Conservation Strategies ◽

Suitable Habitat ◽

Community Based ◽

Geospatial Information ◽

République Démocratique Du Congo ◽

Nous Montrons ◽

Dynamic Conservation

The endangered bonobo (Pan paniscus), endemic to the Democratic Republic of Congo (DRC), is threatened by hunting and habitat loss. Two recent wars and ongoing conflicts in the DRC greatly challenge conservation efforts. This chapter demonstrates how spatial data and maps are used for monitoring threats and prioritizing locations to safeguard bonobo habitat, including identifying areas of highest conservation value to bonobos and collaboratively mapping community-based natural resource management (CBNRM) zones for reducing deforestation in key corridor areas. We also highlight the development of a range-wide model that analysed a variety of biotic and abiotic variables in conjunction with bonobo nest data to map suitable habitat. Approximately 28 per cent of the range was predicted suitable; of that, about 27.5 per cent was located in official protected areas. These examples highlight the importance of employing spatial data and models to support the development of dynamic conservation strategies that will help strengthen bonobo protection. Le bonobo en voie de disparition (Pan paniscus), endémique à la République Démocratique du Congo (DRC), est menacé par la chasse et la perte de l’habitat. Deux guerres récentes et les conflits en cours dans le DRC menacent les efforts de conservation. Ici, nous montrons comment les données spatiales et les cartes sont utilisées pour surveiller les menaces et prioriser les espaces pour protéger l’habitat bonobo, inclut identifier les zones de plus haute valeur de conservation aux bonobos. En plus, la déforestation est réduite par une cartographie collaborative communale de gestion de ressources dans les zones de couloirs essentiels. Nous soulignons le développement d’un modèle de toute la gamme qui a analysé un variété de variables biotiques et abiotiques en conjonction avec les données de nid bonobo pour tracer la carte d’un habitat adéquat. Environ 28 per cent de la gamme est prédit adéquat; de cela, environ 27.5 per cent est dans une zone officiellement protégée. Ces exemples soulignent l’importance d’utiliser les données spatiales et les modèles pour soutenir le développement de stratégies de conservations dynamiques qui aideront à renforcer la protection des bonobos.

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Evaluating Forest Cover and Fragmentation in Costa Rica with a Corrected Global Tree Cover Map

Remote Sensing ◽

10.3390/rs12193226 ◽

2020 ◽

Vol 12 (19) ◽

pp. 3226

Author(s):

Daniel Cunningham ◽

Paul Cunningham ◽

Matthew E. Fagan

Keyword(s):

Costa Rica ◽

Forest Cover ◽

Agricultural Land ◽

Forest Area ◽

Tree Cover ◽

Agricultural Crop ◽

Forest Change ◽

Alos Palsar ◽

Tropical Regions ◽

The Impact

Global tree cover products face challenges in accurately predicting tree cover across biophysical gradients, such as precipitation or agricultural cover. To generate a natural forest cover map for Costa Rica, biases in tree cover estimation in the most widely used tree cover product (the Global Forest Change product (GFC) were quantified and corrected, and the impact of map biases on estimates of forest cover and fragmentation was examined. First, a forest reference dataset was developed to examine how the difference between reference and GFC-predicted tree cover estimates varied along gradients of precipitation and elevation, and nonlinear statistical models were fit to predict the bias. Next, an agricultural land cover map was generated by classifying Landsat and ALOS PalSAR imagery (overall accuracy of 97%) to allow removing six common agricultural crops from estimates of tree cover. Finally, the GFC product was corrected through an integrated process using the nonlinear predictions of precipitation and elevation biases and the agricultural crop map as inputs. The accuracy of tree cover prediction increased by ≈29% over the original global forest change product (the R2 rose from 0.416 to 0.538). Using an optimized 89% tree cover threshold to create a forest/nonforest map, we found that fragmentation declined and core forest area and connectivity increased in the corrected forest cover map, especially in dry tropical forests, protected areas, and designated habitat corridors. By contrast, the core forest area decreased locally where agricultural fields were removed from estimates of natural tree cover. This research demonstrates a simple, transferable methodology to correct for observed biases in the Global Forest Change product. The use of uncorrected tree cover products may markedly over- or underestimate forest cover and fragmentation, especially in tropical regions with low precipitation, significant topography, and/or perennial agricultural production.

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Accelerate disaster risk mapping using an automated zonal change detection model for loss estimation and recovery: a flood case study

Beni-Suef University Journal of Basic and Applied Sciences ◽

10.1186/s43088-020-00082-8 ◽

2020 ◽

Vol 9 (1) ◽

Author(s):

Ali Amasha

Keyword(s):

Change Detection ◽

Satellite Images ◽

Flash Flood ◽

Disaster Risk ◽

Loss Estimation ◽

Risk Mapping ◽

Detection Model ◽

Applied Model ◽

High Resolution Satellite Images ◽

Before And After

Abstract Background The flash flood still constitutes one of the major natural meteorological disasters harmfully threatening local communities, that creates life losses and destroying infrastructures. The severity and magnitude of disasters always reflected from the size of impacts. Most of the conventional research models related to flooding vulnerability are focusing on hydro-meteorological and morphometric measurements. It, however, requires quick estimate of the flood losses and assess the severity using reliable information. An automated zonal change detection model applied, using two high-resolution satellite images dated 2009 and 2011 coupled with LU/LC GIS layer, on western El-Arish City, downstream of Wadi El-Arish basin. The model enabled to estimate the severity of a past flood incident in 2010. Results The model calculated the total changes based on the before and after satellite images based on pixel-by-pixel comparison. The estimated direct-damages nearly 32,951 m2 of the total mapped LU/LC classes; (e.g., 11,407 m2 as 3.17% of the cultivated lands; 6031 m2 as 7.22% of the built-up areas and 4040 m2 as 3.62% of the paved roads network). The estimated cost of losses, in 2010 economic prices for the selected three LU/LC classes, is nearly 25 million USD, for the cultivation fruits and olives trees, ~ 4 million USD for built-up areas and ~ 1 million USD for paved roads network. Conclusion The disasters’ damage and loss estimation process takes many detailed data, longtime, and costed as well. The applied model accelerates the disaster risk mapping that provides an informative support for loss estimation. Therefore, decision-makers and professionals need to apply this model for quick the disaster risks management and recovery.

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