Mapping species distribution and estimating population abundance of dominant forest tree species in Ghana: implications for conservation prioritization
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F25%3A103687" target="_blank" >RIV/60460709:41320/25:103687 - isvavai.cz</a>
Výsledek na webu
<a href="https://www.sciencedirect.com/science/article/pii/S2666719325002456?pes=vor&utm_source=clarivate&getft_integrator=clarivate" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2666719325002456?pes=vor&utm_source=clarivate&getft_integrator=clarivate</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.tfp.2025.101019" target="_blank" >10.1016/j.tfp.2025.101019</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
Mapping species distribution and estimating population abundance of dominant forest tree species in Ghana: implications for conservation prioritization
Popis výsledku v původním jazyce
Understanding the spatial distribution and abundance of tree species is critical for the conservation of biodiversity in Ghana's rapidly declining forests. This study applied Species Distribution Models (SDMs) to assess habitat suitability, abundance patterns, species richness, and conservation gaps of three dominant tree species, Napoleonaea leonensis, Myrianthus serratus, and Penianthus patulinervis, within the semi-deciduous and evergreen humid forest zones of Ghana. Tree occurrence records were compiled from the Global Biodiversity Information Facility (GBIF) database and used as input data for the modeling. Environmental variables, including bioclimatic variables, land cover, topography, and soil properties, were obtained from various online platforms. Habitat suitability was modeled for all three dominant species using the MaxEnt algorithm after correlation and Variable Inflation Factor (VIF) filtering to minimize collinearity. Zero-inflated Poisson (ZIP) models were used to estimate the abundance, while species richness was derived from stack suitability and abundance predictions. MaxEnt suitability models performed strongly across species. Area under Curve (AUC) ranged 0.93-0.96 for Myrianthus serratus and Napoleonaea leonensis. Threshold-based metrics were also high (Kappa: Napoleonaea leonensis 0.72, Myrianthus serratus 0.74, Penianthus patulinervis 0.82; True Skill Statistics (TSS): Napoleonaea leonensis 0.76, Myrianthus serratus 0.85, Penianthus patulinervis 0.85). Abundance models showed good explanatory power (Pseudo-R2: Napoleonaea leonensis 0.283, Myrianthus serratus 0.475, Penianthus patulinervis 0.632; Akaike Information Criterion (AIC) 484.14, 335.73, and 185.87, respectively). Species richness indicated stronger values inside Protected Area (PAs) than outside (mean richness 0.102 inside vs. 0.019 outside). The composite conservation index delineated 23,536,682 ha of hotspot areas with 6,984,6670 ha (30 %) within PAs, highlighting protection gaps in unprotected forest areas. By integrating suitability, abundance, and richness, this study provides an evidence-based framework to guide prioritization and strengthen forest management activities in Ghana.
Název v anglickém jazyce
Mapping species distribution and estimating population abundance of dominant forest tree species in Ghana: implications for conservation prioritization
Popis výsledku anglicky
Understanding the spatial distribution and abundance of tree species is critical for the conservation of biodiversity in Ghana's rapidly declining forests. This study applied Species Distribution Models (SDMs) to assess habitat suitability, abundance patterns, species richness, and conservation gaps of three dominant tree species, Napoleonaea leonensis, Myrianthus serratus, and Penianthus patulinervis, within the semi-deciduous and evergreen humid forest zones of Ghana. Tree occurrence records were compiled from the Global Biodiversity Information Facility (GBIF) database and used as input data for the modeling. Environmental variables, including bioclimatic variables, land cover, topography, and soil properties, were obtained from various online platforms. Habitat suitability was modeled for all three dominant species using the MaxEnt algorithm after correlation and Variable Inflation Factor (VIF) filtering to minimize collinearity. Zero-inflated Poisson (ZIP) models were used to estimate the abundance, while species richness was derived from stack suitability and abundance predictions. MaxEnt suitability models performed strongly across species. Area under Curve (AUC) ranged 0.93-0.96 for Myrianthus serratus and Napoleonaea leonensis. Threshold-based metrics were also high (Kappa: Napoleonaea leonensis 0.72, Myrianthus serratus 0.74, Penianthus patulinervis 0.82; True Skill Statistics (TSS): Napoleonaea leonensis 0.76, Myrianthus serratus 0.85, Penianthus patulinervis 0.85). Abundance models showed good explanatory power (Pseudo-R2: Napoleonaea leonensis 0.283, Myrianthus serratus 0.475, Penianthus patulinervis 0.632; Akaike Information Criterion (AIC) 484.14, 335.73, and 185.87, respectively). Species richness indicated stronger values inside Protected Area (PAs) than outside (mean richness 0.102 inside vs. 0.019 outside). The composite conservation index delineated 23,536,682 ha of hotspot areas with 6,984,6670 ha (30 %) within PAs, highlighting protection gaps in unprotected forest areas. By integrating suitability, abundance, and richness, this study provides an evidence-based framework to guide prioritization and strengthen forest management activities in Ghana.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
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OECD FORD obor
40102 - Forestry
Návaznosti výsledku
Projekt
<a href="/cs/project/TH74010001" target="_blank" >TH74010001: Mapování zdravotního stavu lesů, druhů dřevin a lesních rizik pomocí inovatívnich ICT dat a přístupů</a><br>
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach
Ostatní
Rok uplatnění
2025
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
TREES FORESTS AND PEOPLE
ISSN
2666-7193
e-ISSN
2666-7193
Svazek periodika
22
Číslo periodika v rámci svazku
2025
Stát vydavatele periodika
NL - Nizozemsko
Počet stran výsledku
16
Strana od-do
1-16
Kód UT WoS článku
001578128300001
EID výsledku v databázi Scopus
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