Projected distribution patterns of Alpinia officinarum in China under future climate scenarios: insights from optimized Maxent and Biomod2 models

Frontiers in Plant Science, Journal Year: 2025, Volume and Issue: 16

Published: Feb. 10, 2025

Alpinia officinarum , commonly known as Galangal, is not only widely used a medicinal plant but also holds significant ornamental value in horticulture and landscape design due to its unique structure floral aesthetics China. This study evaluates the impact of current future climate change scenarios (ssp126, ssp245, ssp370, ssp585) on suitable habitats for A. A total 73 reliable distribution points were collected, 11 key environmental variables selected. The ENMeval package was optimize Maxent model, potential areas predicted combination with Biomod2. results show that optimized model accurately Under low emission (ssp126 ssp245), habitat area increased expanded towards higher latitudes. However, under high (ssp370 ssp585), significantly decreased, species range shrinking by approximately 3.7% 19.8%, respectively. Through Multivariate similarity surface (MESS) most dissimilar variable (MoD) analyses revealed variability scenarios, especially ssp585, led large-scale contraction rising temperatures unstable precipitation patterns. Changes center suitability location showed ’s located Guangxi, gradually shifts northwest, while this shift becomes more pronounced. These findings provide scientific basis conservation germplasm resources management strategies response change.

Language: Английский

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Predicting climate-driven shift of the East Mediterranean endemic Cynara cornigera Lindl

Frontiers in Plant Science, Journal Year: 2025, Volume and Issue: 16

Published: Feb. 20, 2025

Climate change poses significant challenges to the distribution of endemics in Mediterranean region. Assessing impact climate on patterns is critical importance for understanding dynamics these terrestrial ecosystems under uncertainty future changes. The population size Cynara cornigera has declined significantly over previous century across its geographical This decline linked how ongoing affecting natural resources like water and capacity foraging sites. In fact, it distributed 3 fragmented locations Egypt (Wadi Hashem (5 individuals), Wadi Um Rakham (20 Burg El-Arab (4 individuals)). this study, we examined C. cornigera's response predicted next few decades (2020-2040 2061-2080) using species models (SDMs). Our analysis involved inclusion bioclimatic variables, SDM modeling process that incorporated five algorithms: generalized linear model (GLM), Random Forest (RF), Boosted Regression Trees (BRT), Support Vector Machines (SVM), Generalized Additive Model (GAM). ensemble obtained high accuracy performance outcomes with a mean AUC 0.95 TSS 0.85 overall model. Notably, RF GLM algorithms outperformed other algorithms, underscoring their efficacy predicting Analysis relative variables revealed Precipitation wettest month (Bio13) (88.3%), warmest quarter (Bio18) (30%), driest (Bio14) (22%) as primary drivers shaping potential cornigera. findings spatial variations habitat suitability, highest observed Egypt, (especially Arishian sub sector), Palestine, Morocco, Northern Cyprus, different islands Sea Crete. Furthermore, our range would drop by more than 25% during decades. Surprisingly, area (SSP 126 scenario) 2061 2080 showed there increase suitable habitats area. It suitability along coastal strip Spain, Sardinia, Algeria, Tunisia, Libya, Lebanon, Aegean islands.

Language: Английский

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Can Ensemble Techniques and Large-Scale Fire Datasets Improve Predictions of Forest Fire Probability Due to Climate Change?—A Case Study from the Republic of Korea

Forests, Journal Year: 2024, Volume and Issue: 15(3), P. 503 - 503

Published: March 8, 2024

The frequency of forest fires worldwide has increased recently due to climate change, leading severe and widespread damage. In this study, we investigate potential changes in the fire susceptibility areas South Korea arising from change. We constructed a dataset large-scale past decade employed it machine learning models that integrate climatic, socioeconomic, environmental variables assess risk fires. According results these models, eastern region is identified as highly vulnerable during baseline period, while western classified relatively safe. However, future, certain along coast are predicted become more susceptible Consequently, change continues, domestic expected increase, need for proactive prevention measures careful management. This study contributes understanding occurrences under diverse scenarios.

Language: Английский

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Modeling of the Potential Distribution Areas Suitable for Olive (Olea europaea L.) in Türkiye from a Climate Change Perspective

Agriculture, Journal Year: 2024, Volume and Issue: 14(9), P. 1629 - 1629

Published: Sept. 17, 2024

Türkiye is one of the first regions where olives were domesticated, and reflect country’s millennia-old agricultural cultural heritage. Moreover, leading nations in olive oil production terms quality diversity. This study aims to determine current future distribution areas olives, which important for Türkiye’s socio-economic structure. For this purpose, 19 different bioclimatic variables, such as annual mean temperature (Bio1), seasonality (Bio4), precipitation (Bio12), have been used. The RCP4.5 RCP8.5 emission scenarios CCSM4 model used projections (2050 2070). MaxEnt software, uses principle maximum entropy, was employed habitat olives. Currently future, it understood that Mediterranean, Aegean, Marmara, Black Sea coastlines with potential suitability However, indicate species may shift from south north higher elevations future. Analyses Aegean Region most sensitive area a significant portion habitats Marmara will remain unaffected by climate change.

Language: Английский

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Predictive sustainability analysis of installed commercial solar energy parks: a temporal and spatial machine learning assessment

Arabian Journal of Geosciences, Journal Year: 2025, Volume and Issue: 18(2)

Published: Jan. 31, 2025

Language: Английский

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Climate Change Reduces and Shifts Suitable Habitats of Uapaca Kirkiana Müll. Arg. To Higher Altitudes in Malawi

Published: Jan. 1, 2025

Language: Английский

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Unveiling Wheat’s Future Amidst Climate Change in the Central Ethiopia Region

Agriculture, Journal Year: 2024, Volume and Issue: 14(8), P. 1408 - 1408

Published: Aug. 20, 2024

Quantifying how climatic change affects wheat production, and accurately predicting its potential distributions in the face of future climate, are highly important for ensuring food security Ethiopia. This study leverages advanced machine learning algorithms including Random Forest, Maxent, Boosted Regression Tree, Generalised Linear Model alongside an ensemble approach to predict shifts habitat suitability Central Ethiopia Region over upcoming decades. An extensive dataset consisting 19 bioclimatic variables (Bio1–Bio19), elevation, solar radiation, topographic positioning index was refined by excluding collinear predictors increase model accuracy. The analysis revealed that precipitation wettest month, minimum temperature coldest seasonality, quarter most influential factors, which collectively account a significant proportion changes. projections up 100% regions currently classified as moderately or suitable could become unsuitable 2050, 2070, 2090, illustrating dramatic decline production. Generally, cultivation will depend heavily on developing varieties can thrive under altered conditions; thus, immediate informed action is needed safeguard region.

Language: Английский

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Effect of climate change on the habitat suitability of the relict species Zelkova carpinifolia Spach using ensembled species distribution modelling

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

Published: Nov. 14, 2024

Zelkova carpinifolia is a Tertiary relict tree distributed in Hyrcanian and Colchic forests. Most of its habitat has been destroyed the last century. This study aimed to model potentially suitable areas for from past future. The Last Glacial Maximum (LGM) Future (2061–2080) models include 19 bioclimatic variables CCSM4 global circulation Pearson correlation coefficient was used assess collinearity between ten were selected distribution modelling. Habitat suitability estimated using Biodiversity Modelling (BIOMOD) ensemble modelling method by combining results algorithm R package "biomod2". area under curve (AUC) receiver operating characteristic (ROC) true skills statistics (TSS) calculated evaluate performance models. contributions environmental separately each model. According obtained, most effective variable species temperature seasonality (Bio4). revealed that survived refuge western Asia during LGM. These have remained largely unchanged even expanded. future predict habitats will narrow forests south Caspian Sea more conditions be found around Caucasus. Given increasing destruction these valuable plant due human activities expected negative impacts climate change future, it important develop policies strategies protection carpinifolia's habitat, creation nature reserves, sustainability.

Language: Английский

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Modeling a hot, dry future: Substantial range reductions in suitable environment projected under climate change for a semiarid riparian predator guild

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(5), P. e0302981 - e0302981

Published: May 6, 2024

An understanding of species-environmental relationships is invaluable for effective conservation and management under anthropogenic climate change, especially biodiversity hotspots such as riparian habitats. Species distribution models (SDMs) assess present which can project potential suitable environments through space time. environmental factors associated with distributions guide strategies a changing climate. We generated 260 ensemble SDMs five species Thamnophis gartersnakes (n = 347)—an important predator guild—in semiarid biogeographically diverse region impact from change (Arizona, United States). modeled projected changes to environment 12 future scenarios per species, including the most least optimistic greenhouse gas emission pathways, 2100. found that likely advanced northward since turn 20 th century overwinter temperature seasonal precipitation best explained distributions. Future ranges are decrease by ca. -37.1% on average. already threatened extinction or those warm trailing-edge populations face greatest loss environment, near complete environment. suggest an upward advance around montane areas some low mid-elevation may create pressures ascend. The here be used identify safe zones prioritize refuges, applicable critical habitat designations. By bounding pathway extremes to, we reduce SDM uncertainties provide valuable information help practitioners mitigate climate-induced threats species. Implementing informed actions paramount sustaining in aridland systems warms dries.

Language: Английский

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Population genomics and distribution modeling revealed the history and suggested a possible future of the endemic Agave aurea (Asparagaceae) complex in the Baja California Peninsula

Ecology and Evolution, Journal Year: 2024, Volume and Issue: 14(7)

Published: July 1, 2024

are an outstanding arid-adapted group of species that provide a unique chance to study the influence multiple potential factors (i.e., geological and ecological) on plant population structure diversification in heterogeneous environment Baja California Peninsula. However, relatively little is known about phylogeography endemic agave this region. Herein, we used over 10,000 single-nucleotide polymorphisms (SNPs) spatial data from

Language: Английский

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