Habitat potential modelling and the effect of climate change on the current and future distribution of three Thymus species in Iran using MaxEnt

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Feb. 13, 2024

Abstract Over the course of a few decades, climate change has caused rapid and alarming reshaping species habitats, resulting in mass extinction, particularly among sensitive species. In order to investigate effects on distribution assess habitat suitability, researchers have developed models (SDMs) that estimate present future distribution. West Asia, thyme such as T. fedtschenkoi , pubescens transcaucasicus are rich thymol carvacrol, commonly used herbal tea, spice, flavoring agents, medicinal plants. This study aims model these Thymus Iran using MaxEnt under two representative concentration pathways (RCP 4.5 RCP 8.5) for years 2050 2070. The objective is identify crucial bioclimatic (n = 5), edaphic 1), topographic 3) variables influence their predict how might various scenarios. findings reveal most significant variable affecting T . altitude, while soil organic carbon content primary factor influencing modeling demonstrates excellent performance, indicated by all area curve (AUC) values exceeding 0.9. Based projections, it expected three will experience negative changes coming years. These results can serve valuable tool developing adaptive management strategies aimed at enhancing protection sustainable utilization context global change. Special attention should be given conserving due loss future.

Language: Английский

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An integrated GEE and machine learning framework for detecting ecological stability under land use/land cover changes

Global Ecology and Conservation, Journal Year: 2024, Volume and Issue: 53, P. e03010 - e03010

Published: May 27, 2024

Ecological stability (ES) is recognized as a crucial factor for sustainable development at global and regional scales. However, the importance of this was not considered significant. Hence, main aim study to introduce new approach that focuses on detecting ES over Maharloo watershed in Iran. To achieve goal, we extracted land use cover (LULC) data from Google Earth Engine (GEE) platform by applying random forest (RF) machine learning method, which obtained Kappa statistics 0.85, 0.86, 0.87 years 2002, 2013, 2023, respectively. We identified both stable unstable regions based LULC changes employed them using forecast ES. The most important predictors ecological were elevation, soil organic carbon index, precipitation, salinity. results research revealed certain areas within have experienced instability recent years, with gardens showing highest percentage (60.65%) among all land-use categories. performance validation our model suggest are reliable (AUC = 0.86). This offers detailed maps trends, offering valuable insights decision makers support landscape conservation restoration efforts. Overall, findings contribute more comprehensive understanding dynamics provide efforts other regions.

Language: Английский

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The influence of climate change on the future distribution of two Thymus species in Iran: MaxEnt model-based prediction

BMC Plant Biology, Journal Year: 2024, Volume and Issue: 24(1)

Published: April 11, 2024

Abstract Within a few decades, the species habitat was reshaped at an alarming rate followed by climate change, leading to mass extinction, especially for sensitive species. Species distribution models (SDMs), which estimate both present and future distribution, have been extensively developed investigate impacts of change on assess suitability. In West Asia essential oils T. daenensis kotschyanus include high amounts thymol carvacrol are commonly used as herbal tea, spice, flavoring agents medicinal plants. Therefore, this study aimed model these Thymus in Iran using MaxEnt under two representative concentration pathways (RCP 4.5 RCP 8.5) years 2050 2070. The findings revealed that mean temperature warmest quarter (bio10) most significant variable affecting . case , slope percentage primary influencing factor. modeling also demonstrated excellent performance, indicated all Area Under Curve (AUC) values exceeding 0.9. Moreover, based projections, mentioned expected undergo negative area changes coming years. These results can serve valuable achievement developing adaptive management strategies enhancing protection sustainable utilization context global change.

Language: Английский

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Predicting Current and Future Habitat Suitability of an Endemic Species Using Data-Fusion Approach: Responses to Climate Change

Rangeland Ecology & Management, Journal Year: 2024, Volume and Issue: 94, P. 149 - 162

Published: April 5, 2024

Language: Английский

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Modeling the effects of climate change scenarios on the potential distribution of Vespa crabro Linnaeus, 1758 (Hymenoptera: Vespidae) in a Mediterranean biodiversity hotspot

Ecological Informatics, Journal Year: 2025, Volume and Issue: unknown, P. 103006 - 103006

Published: Jan. 1, 2025

Language: Английский

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Impact of climate change on the future distribution of three Ferulago species in Iran using the MaxEnt model

Integrated Environmental Assessment and Management, Journal Year: 2024, Volume and Issue: 20(4), P. 1046 - 1059

Published: Feb. 9, 2024

Abstract The decline of habitats supporting medicinal plants is a consequence climate change and human activities. In the Middle East, Ferulago angulata , carduchorum phialocarpa are widely recognized for their culinary, medicinal, economic value. Therefore, this study models these species in Iran using MaxEnt model under two representative concentration pathways (RCP4.5 RCP8.5) 2050 2070. objective was to identify most important bioclimatic ( n = 6), edaphic 4), topographic 3) variables influencing distribution predict changes various scenarios. Findings reveal slope percentage as significant variable F. while solar radiation primary . modeling demonstrated good excellent performance, indicated by all area curve values exceeding 0.85. Projections suggest negative (i.e., predictions RCP4.5 2070 indicate −34.0% −37.8% −0.3% −6.2% ; additionally, RCP 8.5 show −39.0% −52.2% −1.33% −9.8% ), potential habitat increase 23.4% 11.2%, 64.4% 42.1%) anticipated. These insights guide adaptive management strategies, emphasizing conservation sustainable use amid global change. Special attention should be paid due anticipated loss. Integr Environ Assess Manag 2024;20:1046–1059. © 2024 SETAC

Language: Английский

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Machine learning-driven habitat suitability modeling of Suaeda aegyptiaca for sustainable industrial cultivation in saline regions

Industrial Crops and Products, Journal Year: 2025, Volume and Issue: 225, P. 120427 - 120427

Published: Jan. 11, 2025

Language: Английский

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Advancements in ecological niche models for forest adaptation to climate change: a comprehensive review

Biological reviews/Biological reviews of the Cambridge Philosophical Society, Journal Year: 2025, Volume and Issue: unknown

Published: April 3, 2025

ABSTRACT Climate change poses significant challenges to the health and functions of forest ecosystems. Ecological niche models have emerged as crucial tools for understanding impact climate on forests at population, species, ecosystem levels. These also play a pivotal role in developing adaptive conservation management strategies. Recent advancements model development led enhanced prediction accuracy broadened applications models, driven using high‐quality data, improved algorithms, application landscape genomic information. In this review, we start by elucidating concept rationale behind context forestry adaptation change. We then provide an overview occurrence‐based, trait‐based, genomics‐based contributing more comprehensive species responses addition, summarize findings from 338 studies highlight progress made tree including data sources, future scenarios used diverse applications. To assist researchers practitioners, exemplar set accompanying source code tutorial, demonstrating integration population genetics into models. This paper aims concise yet continuous refinements serving valuable resource effectively addressing posed changing climate.

Language: Английский

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Modelling the Distribution of Great Hornbill [Buceros Bicornis (Linnaeus, 1758)] in Nepal: Insights for Conservation Planning Using Ensemble Species Distribution Models

Published: Jan. 1, 2025

Language: Английский

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Future of Three Endemic Woody Species of Colutea (Fabaceae) in a Changing Climate in Iran

Ecology and Evolution, Journal Year: 2025, Volume and Issue: 15(5)

Published: May 1, 2025

ABSTRACT Woody plants offer valuable services to ecosystems, including providing useful products, stabilizing and mitigating climate pollution effects. However, they face significant abiotic biotic stresses, with change being the most critical challenge. It is essential understand that reducing populations of woody species, particularly those found only in a specific area, can have severe irreversible effects on entire ecosystem. Therefore, exploring potential influence distribution endemic species an appealing subject for conservation researchers. This study investigates how affects three genus Colutea Iran. The MaxEnt model was used analyze data, results showed effective predicting impact (AUC ≥ 0.9). C. persica significantly affected by solar radiation, Precipitation Wettest Month, sand, silt content. porphyrogamma 's impacted Mean Temperature Coldest Quarter, Driest Cation Exchange Capacity, while triphylla Seasonality, Isothermality. According findings, these expected decrease 2050s 2070s due change, based RCP4.5 RCP8.5 scenarios. These findings be developing strategies manage impacts species.

Language: Английский

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