Prioritizing conservation areas based on contributions to rarity and beta diversity in Mediterranean forest ecosystems in Türkiye

The depletion of forest biodiversity arising from insufficient conservation of resources due to wood extraction, overgrazing, fire, and land use presents a significant challenge in the Mediterranean region. It becomes crucial to identify priority conservation areas for safeguarding biodiversity. We used plant species data taken from 800 plots in the Kuyucak mountain district, a typical Mediterranean forest ecosystem in Türkiye and maps of seven potential environmental predictors: elevation, aspect, slope, head index, topographical position index, landform characteristics, and bedrock geology. To assign priority areas for the conservation, local contribution to beta diversity (LCBD) and relative contribution to total rarity (RIRR) were examined with community metrics and environmental predictors, respectively. Correlation results showed that LCBD was positively related to rare species richness but negatively related to common species richness. RIRR was significantly associated with all the community metrics. According to the results of Random Forest regression models, elevation was the most important variable of LCBD, followed by slope, heat index, and pebblestone. For RIRR, the most contributed variables were elevation, heat index, limestone, and slope, respectively. The LCBD and RIRR Random Forest regression models were extrapolated along the Kuyucak mountain district, resulting in the creation of potential distribution maps for both LCBD and RIRR. Subsequently, from these maps, two distinct conservation value maps have been developed for the Kuyucak mountain district based on four conservation priority classes (Priority Class 1, Priority Class 2, Priority Class 3, and Priority Class 4): one employing a conservation cost approach and the other applying an ecology-centered approach. The results suggest that areas with elevated values of both LCBD and RIRR values are primarily situated below 1100 m on steep valley slopes, characterized by the presence of karstic limestone and intricate terrain. Compared to other areas, prioritizing the protection of such areas can provide greater benefits in contributing to ecological uniqueness. Keywords: Community rarity, Species contributions to beta diversity, Conservation priority, Ecological uniqueness, Indicator species analysis, Machine learning

Authors

Institutions

Publication Details

Journal
Annals of Forest Research
Published
2024-12-31
DOI
https://doi.org/10.15287/afr.2024.3596
Primary Topic
Forest Insect Ecology and Management
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prioritizing conservation areas based on contributions to rarity and beta diversity in Mediterranean forest ecosystems in Türkiye

Mehmet Güvenç Negiz, Özdemir Şentürk, Kürşad Özkan, Arslan Münevver
Annals of Forest Research
Forest Insect Ecology and Management
article

Prioritizing conservation areas based on contributions to rarity and beta diversity in Mediterranean forest ecosystems in Türkiye

Mehmet Güvenç Negiz, Özdemir Şentürk, Kürşad Özkan, Arslan Münevver
article en

Abstract

The depletion of forest biodiversity arising from insufficient conservation of resources due to wood extraction, overgrazing, fire, and land use presents a significant challenge in the Mediterranean region. It becomes crucial to identify priority conservation areas for safeguarding biodiversity. We used plant species data taken from 800 plots in the Kuyucak mountain district, a typical Mediterranean forest ecosystem in Türkiye and maps of seven potential environmental predictors: elevation, aspect, slope, head index, topographical position index, landform characteristics, and bedrock geology. To assign priority areas for the conservation, local contribution to beta diversity (LCBD) and relative contribution to total rarity (RIRR) were examined with community metrics and environmental predictors, respectively. Correlation results showed that LCBD was positively related to rare species richness but negatively related to common species richness. RIRR was significantly associated with all the community metrics. According to the results of Random Forest regression models, elevation was the most important variable of LCBD, followed by slope, heat index, and pebblestone. For RIRR, the most contributed variables were elevation, heat index, limestone, and slope, respectively. The LCBD and RIRR Random Forest regression models were extrapolated along the Kuyucak mountain district, resulting in the creation of potential distribution maps for both LCBD and RIRR. Subsequently, from these maps, two distinct conservation value maps have been developed for the Kuyucak mountain district based on four conservation priority classes (Priority Class 1, Priority Class 2, Priority Class 3, and Priority Class 4): one employing a conservation cost approach and the other applying an ecology-centered approach. The results suggest that areas with elevated values of both LCBD and RIRR values are primarily situated below 1100 m on steep valley slopes, characterized by the presence of karstic limestone and intricate terrain. Compared to other areas, prioritizing the protection of such areas can provide greater benefits in contributing to ecological uniqueness. Keywords: Community rarity, Species contributions to beta diversity, Conservation priority, Ecological uniqueness, Indicator species analysis, Machine learning

Annals of Forest ResearchVol. 67(2)
Institute of Forest Ecology of the Slovak Academy of Sciences (SK), Isparta University of Applied Sciences (TR), Burdur Mehmet Akif Ersoy Üniversitesi (TR)
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu
Openalex Percentile: Top 75%
Forest Insect Ecology and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.