scholarly journals Vegetation Classification and Habitat Types of Gambella National Park

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Gatluak Rolkier ◽  
Kumelachew Yeshitela

Gambella National Park has a diverse set of habitat types which Ethiopia shares with its neighbor, South Sudan, and the park is considered as one of the top wildlife areas of Ethiopia. The objectives of this research were to determine vegetation types and identify habitat types on recent satellite imageries. The method used for vegetation data collection was transects lines. PC-ORD software was used for analyzed vegetation data while Rapid Eye image 5 m resolution 2012 was analyzed by ArcGIS version 10.1 to classify the habitats map of Gambella National Park. The cluster analysis classified the Gambella National Park into 6 vegetation communities, and the relative abundance and relative frequency were used for naming vegetation community types. However, the satellite image had classified the Gambella National Park into 5 major habitat types.

Diversity ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 456
Author(s):  
Dionísio Virgílio Roque ◽  
Thomas Göttert ◽  
Valério António Macandza ◽  
Ulrich Zeller

This study is the first systematic assessment of large herbivore (LH) communities in Limpopo National Park (LNP) in Mozambique, an area where most LH species were extinct until the early 2000s. We investigate whether LH community parameters are linked with the availability of habitat types or the distance between sampling sites and the origin of LH resettlement. We placed camera traps in five habitat types in resettled and not-resettled areas to compare species richness, relative abundance index, grazers–browsers–mixed feeder ratio and naïve occupancy of 15 LH species. While the richness decreased along the distance gradient of LH resettlement, relative abundance index strongly responded to habitat features. Among habitat types, the browsers ratio oscillated, while from resettled to not-resettled areas, the ratio increased. Most species showed a wider distribution range among habitat types. The associations of most LH community parameters with habitat types rather than distance to initial release, together with the species-specific and guild-specific response patterns of LH, suggest LNP to already be in an intermediate stage of restoration. Our results highlight the importance of post-release monitoring of reintroduced wildlife as a tool to assess the success of ecological restoration initiatives in transboundary conservation areas.


2020 ◽  
Author(s):  
Julie Evans ◽  
Kendra Sikes ◽  
Jamie Ratchford

Vegetation inventory and mapping is a process to document the composition, distribution and abundance of vegetation types across the landscape. The National Park Service’s (NPS) Inventory and Monitoring (I&M) program has determined vegetation inventory and mapping to be an important resource for parks; it is one of 12 baseline inventories of natural resources to be completed for all 270 national parks within the NPS I&M program. The Mojave Desert Network Inventory & Monitoring (MOJN I&M) began its process of vegetation inventory in 2009 for four park units as follows: Lake Mead National Recreation Area (LAKE), Mojave National Preserve (MOJA), Castle Mountains National Monument (CAMO), and Death Valley National Park (DEVA). Mapping is a multi-step and multi-year process involving skills and interactions of several parties, including NPS, with a field ecology team, a classification team, and a mapping team. This process allows for compiling existing vegetation data, collecting new data to fill in gaps, and analyzing the data to develop a classification that then informs the mapping. The final products of this process include a vegetation classification, ecological descriptions and field keys of the vegetation types, and geospatial vegetation maps based on the classification. In this report, we present the narrative and results of the sampling and classification effort. In three other associated reports (Evens et al. 2020a, 2020b, 2020c) are the ecological descriptions and field keys. The resulting products of the vegetation mapping efforts are, or will be, presented in separate reports: mapping at LAKE was completed in 2016, mapping at MOJA and CAMO will be completed in 2020, and mapping at DEVA will occur in 2021. The California Native Plant Society (CNPS) and NatureServe, the classification team, have completed the vegetation classification for these four park units, with field keys and descriptions of the vegetation types developed at the alliance level per the U.S. National Vegetation Classification (USNVC). We have compiled approximately 9,000 existing and new vegetation data records into digital databases in Microsoft Access. The resulting classification and descriptions include approximately 105 alliances and landform types, and over 240 associations. CNPS also has assisted the mapping teams during map reconnaissance visits, follow-up on interpreting vegetation patterns, and general support for the geospatial vegetation maps being produced. A variety of alliances and associations occur in the four park units. Per park, the classification represents approximately 50 alliances at LAKE, 65 at MOJA and CAMO, and 85 at DEVA. Several riparian alliances or associations that are somewhat rare (ranked globally as G3) include shrublands of Pluchea sericea, meadow associations with Distichlis spicata and Juncus cooperi, and woodland associations of Salix laevigata and Prosopis pubescens along playas, streams, and springs. Other rare to somewhat rare types (G2 to G3) include shrubland stands with Eriogonum heermannii, Buddleja utahensis, Mortonia utahensis, and Salvia funerea on rocky calcareous slopes that occur sporadically in LAKE to MOJA and DEVA. Types that are globally rare (G1) include the associations of Swallenia alexandrae on sand dunes and Hecastocleis shockleyi on rocky calcareous slopes in DEVA. Two USNVC vegetation groups hold the highest number of alliances: 1) Warm Semi-Desert Shrub & Herb Dry Wash & Colluvial Slope Group (G541) has nine alliances, and 2) Mojave Mid-Elevation Mixed Desert Scrub Group (G296) has thirteen alliances. These two groups contribute significantly to the diversity of vegetation along alluvial washes and mid-elevation transition zones.


Koedoe ◽  
2016 ◽  
Vol 58 (1) ◽  
Author(s):  
Francesco Martini ◽  
Robert Cunliffe ◽  
Alessio Farcomeni ◽  
Michele De Sanctis ◽  
Giacomo D'Ammando ◽  
...  

Within the framework of the Great Limpopo Transfrontier Conservation Area (GLTFCA), the purpose of this study was to produce a classification of the woody vegetation of the Gonarezhou National Park, Zimbabwe, and a map of its potential distribution. Cover-abundance data of woody species were collected in 330 georeferenced relevés across the Park. These data were used to produce two matrices: the first one using the cover-abundance values as collected in five height layers and the second one based on merging the layers into a single cover value for each species. Automatic classifications were produced for both matrices to determine the optimal number of vegetation types. The two classification approaches both produced 14 types belonging to three macro-groups: mopane, miombo and alluvial woodlands. The results of the two classifications were compared looking at the constant, dominant and diagnostic species of each type. The classification based on separate layers was considered more effective and retained. A high-resolution map of the potential distribution of vegetation types for the whole study area was produced using Random Forest. In the model, the relationship between bioclimatic and topographic variables, known to be correlated to vegetation types, and the classified relevés was used. Identified vegetation types were compared with those of other national parks within the GLTFCA, and an evaluation of the main threats and pressures was conducted.Conservation implications: Vegetation classification and mapping are useful tools for multiple purposes including: surveying and monitoring plant and animal populations, communities and their habitats, and development of management and conservation strategies. Filling the knowledge gap for the Gonarezhou National Park provides a basis for standardised and homogeneous vegetation classification and mapping for the entire Great Limpopo Transfrontier Conservation Area.


Koedoe ◽  
2016 ◽  
Vol 58 (1) ◽  
Author(s):  
Francesco Martini ◽  
Robert Cunliffe ◽  
Alessio Farcomeni ◽  
Michele De Sanctis ◽  
Giacomo D'Ammando ◽  
...  

Within the framework of the Great Limpopo Transfrontier Conservation Area (GLTFCA), the purpose of this study was to produce a classification of the woody vegetation of the Gonarezhou National Park, Zimbabwe, and a map of its potential distribution. Cover-abundance data of woody species were collected in 330 georeferenced relevés across the Park. These data were used to produce two matrices: the first one using the cover-abundance values as collected in five height layers and the second one based on merging the layers into a single cover value for each species. Automatic classifications were produced for both matrices to determine the optimal number of vegetation types. The two classification approaches both produced 14 types belonging to three macro-groups: mopane, miombo and alluvial woodlands. The results of the two classifications were compared looking at the constant, dominant and diagnostic species of each type. The classification based on separate layers was considered more effective and retained. A high-resolution map of the potential distribution of vegetation types for the whole study area was produced using Random Forest. In the model, the relationship between bioclimatic and topographic variables, known to be correlated to vegetation types, and the classified relevés was used. Identified vegetation types were compared with those of other national parks within the GLTFCA, and an evaluation of the main threats and pressures was conducted.Conservation implications: Vegetation classification and mapping are useful tools for multiple purposes including: surveying and monitoring plant and animal populations, communities and their habitats, and development of management and conservation strategies. Filling the knowledge gap for the Gonarezhou National Park provides a basis for standardised and homogeneous vegetation classification and mapping for the entire Great Limpopo Transfrontier Conservation Area.


Koedoe ◽  
2016 ◽  
Vol 58 (1) ◽  
Author(s):  
Francesco Martini ◽  
Robert Cunliffe ◽  
Alessio Farcomeni ◽  
Michele De Sanctis ◽  
Giacomo D'Ammando ◽  
...  

Within the framework of the Great Limpopo Transfrontier Conservation Area (GLTFCA), the purpose of this study was to produce a classification of the woody vegetation of the Gonarezhou National Park, Zimbabwe, and a map of its potential distribution. Cover-abundance data of woody species were collected in 330 georeferenced relevés across the Park. These data were used to produce two matrices: the first one using the cover-abundance values as collected in five height layers and the second one based on merging the layers into a single cover value for each species. Automatic classifications were produced for both matrices to determine the optimal number of vegetation types. The two classification approaches both produced 14 types belonging to three macro-groups: mopane, miombo and alluvial woodlands. The results of the two classifications were compared looking at the constant, dominant and diagnostic species of each type. The classification based on separate layers was considered more effective and retained. A high-resolution map of the potential distribution of vegetation types for the whole study area was produced using Random Forest. In the model, the relationship between bioclimatic and topographic variables, known to be correlated to vegetation types, and the classified relevés was used. Identified vegetation types were compared with those of other national parks within the GLTFCA, and an evaluation of the main threats and pressures was conducted.Conservation implications: Vegetation classification and mapping are useful tools for multiple purposes including: surveying and monitoring plant and animal populations, communities and their habitats, and development of management and conservation strategies. Filling the knowledge gap for the Gonarezhou National Park provides a basis for standardised and homogeneous vegetation classification and mapping for the entire Great Limpopo Transfrontier Conservation Area.


2001 ◽  
pp. 99-106 ◽  
Author(s):  
Yu. N. Neshatayev

If one processes a huge amount of data when es­tabli­shing the vegetation classification, it appears necessary to use the uniform algorithms of analysis. Such goals as distinguishing the reliable community types (associations or other syntaxa) involve the operational reduction of either the species list, or (more seldom) the sample plot set. This is especially useful for the analysis of multi­specific communities of meadows, steppes, or another types of markedly continuous polydominant vegetation with «fuzzy» structure of the herb layer.


2015 ◽  
pp. 125-138 ◽  
Author(s):  
I. V. Goncharenko

In this article we proposed a new method of non-hierarchical cluster analysis using k-nearest-neighbor graph and discussed it with respect to vegetation classification. The method of k-nearest neighbor (k-NN) classification was originally developed in 1951 (Fix, Hodges, 1951). Later a term “k-NN graph” and a few algorithms of k-NN clustering appeared (Cover, Hart, 1967; Brito et al., 1997). In biology k-NN is used in analysis of protein structures and genome sequences. Most of k-NN clustering algorithms build «excessive» graph firstly, so called hypergraph, and then truncate it to subgraphs, just partitioning and coarsening hypergraph. We developed other strategy, the “upward” clustering in forming (assembling consequentially) one cluster after the other. Until today graph-based cluster analysis has not been considered concerning classification of vegetation datasets.


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