Potential distribution mapping of Orchis anatolica (Boiss.) naturally distributed in Isparta province

Background and aims This study focused on modeling the potential distribution of Orchis anatolica, a species belonging to the Orchidaceae family. Methods As a result of field studies conducted between March and June from 2019 to 2022, presence data for this species were obtained from 30 sampling sites. Based on the collected data, the potential distribution of Orchis anatolica, which naturally occurs in the Isparta province, was modeled using the Maximum Entropy (MaxEnt) method. To determine the potential distribution, relationships between the presence data of the target species and 22 uncorrelated environmental variables including bioclimatic variables and base maps produced or digitized via geographic information systems were modeled and mapped using MaxEnt software. Results According to the potential distribution model generated for Orchis anatolica (training dataset AUC: 0.974, test dataset AUC: 0.953), the environmental variables most influencing the species' distribution were identified as site index (bonitet), bio10, age class, bio12, and terrain ruggedness classes. Conclusions This study investigated the relationships among the ecological characteristics, geographic distribution, and habitat features of Orchis anatolica, and produced a potential distribution map for the species in the Isparta region. It provides a valuable foundation for the conservation and sustainable use of Orchis diversity and genetic resources in Isparta province.

Authors

Institutions

Publication Details

Journal
Anadolu Orman Araştırmaları Dergisi
Published
2025-05-04
DOI
https://doi.org/10.53516/ajfr.1607853
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Potential distribution mapping of Orchis anatolica (Boiss.) naturally distributed in Isparta province

Ebru Hatice TIĞLI KAYTANLIOĞLU, Hüseyin Fakir
Anadolu Orman Araştırmaları Dergisi
Species Distribution and Climate Change
article

Potential distribution mapping of Orchis anatolica (Boiss.) naturally distributed in Isparta province

Ebru Hatice TIĞLI KAYTANLIOĞLU, Hüseyin Fakir
article en

Abstract

Background and aims This study focused on modeling the potential distribution of Orchis anatolica, a species belonging to the Orchidaceae family. Methods As a result of field studies conducted between March and June from 2019 to 2022, presence data for this species were obtained from 30 sampling sites. Based on the collected data, the potential distribution of Orchis anatolica, which naturally occurs in the Isparta province, was modeled using the Maximum Entropy (MaxEnt) method. To determine the potential distribution, relationships between the presence data of the target species and 22 uncorrelated environmental variables including bioclimatic variables and base maps produced or digitized via geographic information systems were modeled and mapped using MaxEnt software. Results According to the potential distribution model generated for Orchis anatolica (training dataset AUC: 0.974, test dataset AUC: 0.953), the environmental variables most influencing the species' distribution were identified as site index (bonitet), bio10, age class, bio12, and terrain ruggedness classes. Conclusions This study investigated the relationships among the ecological characteristics, geographic distribution, and habitat features of Orchis anatolica, and produced a potential distribution map for the species in the Isparta region. It provides a valuable foundation for the conservation and sustainable use of Orchis diversity and genetic resources in Isparta province.

Anadolu Orman Araştırmaları DergisiVol. 11(1)
Isparta University of Applied Sciences (TR)
Openalex Percentile: Top 95%
Species Distribution and Climate Change
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.