DOI: 10.5061/dryad.pvmcvdnvs
title: In-situ and ex-situ conservation priorities and distribution of lentil wild relatives under climate change: A modeling approach

description: Lentil wild relatives are an important source of desirable traits that can
 be used for improving the productivity and resilience of cultivated
 lentil. Yet, our understanding of their habitat suitability and associated
 environmental factors remains limited. This study aimed to assess climate
 change's impact on the potential distribution of six wild lentil
 species (Lens culinaris subsp. orientalis, Lens culinaris subsp.
 tomentosus, Lens culinaris subsp. odemensis, Lens ervoides, Lens lamottei,
 and Lens nigricans) under various climate scenarios and assess their risk
 of extinction and determine their in-situ and ex-situ conservation status.
 We used a species distribution modeling approach with MaxEnt to assess the
 present and future potential distribution of wild lentil species.
 Extinction risk was evaluated based on IUCN criterion B, and the
 conservation status was assessed using the GapAnalysis method. The
 precipitation of the coldest quarter (bio19) and the min temperature of
 the coldest month (bio6) were found as the most important variables
 influencing the distribution of wild lentil species. Final Conservation
 Score (FCS) ranged from 17.85 and 37.55, highlighting three wild lentil
 species (Lens ervoides, Lens nigricans, and Lens culinaris subsp.
 tomentosus) with high priority (HP) for conservation and medium priority
 (MP) for the remaining species. Lens culinaris subsp. tomentosus is
 categorized as a vulnerable species, while the other five species are of
 least concern or near threatened. Synthesis and applications: This study
 underscores the urgent need for policy development to safeguard the
 diversity of lentil wild relatives in the face of climate change. The
 identified vulnerability of Lens culinaris subsp. tomentosus, among
 others, needs prompt and proactive conservation actions. Key management
 practices include the establishment and expansion of protected areas,
 habitat restoration, and the promotion of sustainable land use practices.
 The integration of effective in-situ and ex-situ conservation strategies,
 along with ecological management practices, is essential. These measures,
 not only, enhance biodiversity conservation but also improve the
 resilience of agricultural ecosystems. Such an approach is pivotal in
 shaping effective conservation management practices for lentil wild
 relatives, promoting a sustainable agricultural system, and ensuring food
 security in an evolving climate scenario. 
description: # README for Dataset: In-situ and ex-situ conservation priorities and
 distribution of lentil wild relatives under climate change: A modeling
 approach ## General Information * **Dataset Title**: In-situ and ex-situ
 conservation priorities and distribution of lentil wild relatives under
 climate change: A modeling approach Authors: Salma Rouichi, Michel Edmond
 Ghanem and Moez Amri Date of Submission: 27/09/2024 Corresponding Author:
 Moez Amri, [moez.amri@um6p.ma](mailto:moez.amri@um6p.ma) This dataset
 contains occurrence records, model settings, and variable selection
 details used in modeling the distribution and conservation priorities of
 lentil wild relatives (Lens genus) under climate change scenarios. The
 data support the findings described in the associated research article.
 --- ## Data Files Description The dataset consists of three sheets
 organized into a single Excel file. Below is a detailed description of
 each: 1. **Sheet: Occurrences** * **Description**: This sheet contains
 records of species occurrences, with corresponding latitude, longitude,
 and occurrence type (G: Geographic; M: Modeled). * **Columns**: * **SN**:
 Serial number of the occurrence record. * **Species**: Scientific name of
 the species (e.g., *Lens ervoides*). * **Latitude**: Latitude coordinate
 of the occurrence. * **Longitude**: Longitude coordinate of the
 occurrence. * **Type**: Type of occurrence data, Records that are
 currently kept in germplasm collections were scored "G", and
 other records from herbarium and field observation data were scored as
 "H". 2. **Sheet: Number of Occurrences and Modeling Settings** *
 **Description**: Provides information about the number of species used for
 modeling after thinning, the number of training and testing occurrences,
 and evaluation metrics (AUC scores) for the MaxEnt modeling settings. *
 **Columns**: * **Species**: Scientific name of the species used for
 modeling. * **Training AUC**: Area Under the Curve (AUC) score for the
 training data. * **Test AUC**: AUC score for the testing data. * **AUC
 Standard Deviation**: Standard deviation of AUC across replicates. *
 **Mean AUC**: Mean AUC score across replicates. 3. **Sheet: Variable
 Selection** * **Description**: Lists environmental predictors used in the
 modeling process, including their codes, units, Variance Inflation Factor
 (VIF) values, and whether they were included in the final model. *
 **Columns**: * **Code**: Abbreviation for the environmental predictor. *
 **Environmental Variable**: Full name of the variable. * **Unit**:
 Measurement unit (e.g., °C). * **VIF**: Variance Inflation Factor value,
 indicating multicollinearity * **Included in Model**: Whether the variable
 was included (Yes/No). --- ## Data Sources and Licenses The dataset
 integrates occurrence data from the following sources: * **GBIF**:
 [https://www.gbif.org/](https://www.gbif.org/) * **Genesys**:
 [https://www.genesys-pgr.org/](https://www.genesys-pgr.org/) *
 **WorldClim**:
 [https://www.worldclim.org/data/bioclim.html](https://www.worldclim.org/data/bioclim.html) The dataset integrates occurrence data from the following **GBIF downloads**, with proper attribution as required under the **CC-BY 4.0 license**: * GBIF.Org User. (2022a). Occurrence Download (p. 3654) [Darwin Core Archive]. [object Object]. [https://doi.org/10.15468/DL.GMSVD2](https://doi.org/10.15468/DL.GMSVD2) * GBIF.Org User. (2022b). Occurrence Download (p. 3980) [Darwin Core Archive]. [object Object]. [https://doi.org/10.15468/DL.PEKZHD](https://doi.org/10.15468/DL.PEKZHD) * GBIF.Org User. (2022c). Occurrence Download (p. 0) [Darwin Core Archive]. [object Object]. [https://doi.org/10.15468/DL.F5BWWS](https://doi.org/10.15468/DL.F5BWWS) * GBIF.Org User. (2022d). Occurrence Download (p. 63227) [Darwin Core Archive]. [object Object]. [https://doi.org/10.15468/DL.FTZYGX](https://doi.org/10.15468/DL.FTZYGX) * GBIF.Org User. (2022e). Occurrence Download (p. 75278) [Darwin Core Archive]. [object Object]. [https://doi.org/10.15468/DL.QPQH32](https://doi.org/10.15468/DL.QPQH32) * GBIF.Org User. (2022f). Occurrence Download (p. 147332) [Darwin Core Archive]. [object Object]. [https://doi.org/10.15468/DL.SENDS5](https://doi.org/10.15468/DL.SENDS5) All other environmental data are sourced from **WorldClim** and are available under open-use licenses. --- ## Usage Notes * This dataset is made available under the CC0 1.0 Universal (CC0 1.0) Public Domain Dedication. Users are free to distribute, remix, adapt, and build upon this dataset, without restriction. * Proper use of this dataset requires understanding of MaxEnt modeling and the environmental predictors employed in ecological niche modeling. --- Contact Information For any inquiries related to the dataset, please contact: Moez Amri [moez.amri@um6p.ma](mailto:moez.amri@um6p.ma)