In-situ and ex-situ conservation priorities and distribution of lentil wild relatives under climate change: A modeling approach
Data files
Nov 22, 2024 version files 19.01 KB
-
README.md
4.93 KB
-
Supporting_information_-_Supplementary_data.xlsx
14.08 KB
Abstract
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.
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
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:
- 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".
- 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.
- 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/
- Genesys: https://www.genesys-pgr.org/
- WorldClim: 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
- GBIF.Org User. (2022b). Occurrence Download (p. 3980) [Darwin Core Archive]. [object Object]. 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
- GBIF.Org User. (2022d). Occurrence Download (p. 63227) [Darwin Core Archive]. [object Object]. 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
- GBIF.Org User. (2022f). Occurrence Download (p. 147332) [Darwin Core Archive]. [object Object]. 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