Tae-Bok Ryu

Although the rare plant Cotoneaster integerrimus is distributed across Eurasia, ecological information on its isolated populations at the easternmost range limit in Korea has been entirely lacking. This study was conducted to (1) characterize the environmental characteristics of the habitat of Korean C. integerrimus populations and (2) predict potential habitats via a simple species distribution model (SDM) based on ridge logistic regression and presence–background data, providing a foundation for effective conservation strategies. To this end, we analyzed habitat type, topography, and light conditions through field surveys and combined these data with an SDM fitted to six known occurrences on limestone ridges. Results revealed a clear ecological divergence; the Korean population is biased toward partial shade and north-facing slopes within the forest understory, in contrast to European populations inhabiting open, rocky sites. This distribution pattern is interpreted as a local adaptive strategy that reduces exposure to hot and humid summer conditions. Furthermore, a unique morphological trait not reported in European populations was identified: dense persistent hairs that remain until seed maturity. The SDM analysis showed moderate discrimination (training AUC = 0.784) and indicated that high elevation and ridge topography (Topographical Position Index, TPI) acted as key habitat factors, whereas annual mean temperature was the strongest limiting factor. Mapping the upper decile (top 10%) of predicted suitability within the limestone belt highlighted a small, spatially restricted set of high-elevation ridges as candidate microrefugia and survey priorities. This study suggests that the Korean C. integerrimus population may have undergone local adaptation due to isolation. Furthermore, this population is considered both a Geographical Peripheral Population (GPP) and a glacial relict, and is assessed to be vulnerable to climate change. Given that the SDM is based on only six occurrences and shows variable performance among spatial folds, all spatial predictions and variable effects should be regarded as exploratory and spatially conservative rather than as definitive habitat projections. These findings, therefore, support the urgent need to establish in situ and ex situ conservation strategies that preserve this geographically peripheral population as an irreplaceable component of the species’ genetic diversity.

Conserving near-shore island endemics requires workflows that are robust to small, spatially clustered samples and that translate Species Distribution Model (SDM) into regulation-ready actions. We formalize a transferable SDM-to-action blueprint—(i) cluster-aware spatial holdout (leave-one-cluster-out, LOCO), (ii) conservative, high-specificity binarization paired with simple ecological filters, and (iii) explicit area-band uncertainty—and apply it to the Ulleungdo (Republic of Korea) endemic Scrophularia takesimensis. We combined 2008–2024 field records with a 5 m resolution MaxEnt model (linear–quadratic features; regularization RM = 1.40) using 28 unique presences versus 744 background points sampled within an accessible coastal belt (300 m from shore). Under LOCO, the model generalized well (AUC = 0.984 ± 0.014; partial AUC at specificity of at least 0.90 = 0.935; RelRMSE = 0.107) and mapped a narrow near-shore suitability belt with a continuous northern–northeastern core and fragmented southern–eastern satellites. To obtain a regulation-ready map, we converted continuous suitability to binary using a cutoff that achieved specificity of at least 0.98 under spatial holdout (threshold: 0.472; baseline: 300 m) and applied two ecological filters (retain areas within 90 m of shoreline; remove patches < 75 m²), yielding a CORE of 1.148 km² that captured 71.4% of recent records with zero leakage beyond the belt after post-processing. Accessible-mask sensitivity (masks of 300, 450, and 600 m) bounded the post-processed CORE to 0.930–1.593 km² (coverage: 0.607–0.789), which we carry forward as a planning area band. We translate these results into a tiered plan: protect the near-shore core, reconnect the fragmented southern and eastern stretches, and survey the highest-ranked coastal segments. Beyond this case, the blueprint generalizes to other small-n near-shore endemics, offering a transparent path from the SDM to policy while clarifying that, given static predictors, inferences concern present-day suitability rather than climate change forecasting.