Pub Date : 2026-01-12DOI: 10.1016/j.jaridenv.2026.105549
Ivania B. Santos , Helder F.P. Araujo , Edgar E. Santo-Silva
In seasonal tropical dry forests, warmer and drier climate conditions projected for the coming decades may reduce the distribution ranges of many woody plants, threatening biodiversity maintenance. Using ecological niche modelling for 70 endemic woody plant species of the Brazilian Caatinga, we assessed how climate change may affect structural and phylogenetic dimensions of assemblages that evolved exclusively within this ecosystem. Models were run for the current period, 2041–2060, and 2081–2100 under two greenhouse gas emission scenarios. By 2100, at least 70 % of species are projected to lose suitable habitat, and up to 11 % may become globally extinct under the pessimistic scenario. The effects of climate change are consistent across both narrow- and wide-range species. Species richness, phylogenetic diversity, and phylogenetic structure are projected to decline across the Caatinga. The number of phylogenetically clustered assemblages is expected to increase by 85–237 %, depending on the phylogenetic metric and climate scenario, whereas the number of overdispersed assemblages is expected to decline. Overall, the impacts of climate change on Caatinga biodiversity may be more severe than previously reported, with the ecosystem projected to host impoverished assemblages of endemic woody plants and lose substantial evolutionary history by the end of this century.
{"title":"Climate change threatens species richness and phylogenetic diversity of endemic woody plants in Caatinga dry forest","authors":"Ivania B. Santos , Helder F.P. Araujo , Edgar E. Santo-Silva","doi":"10.1016/j.jaridenv.2026.105549","DOIUrl":"10.1016/j.jaridenv.2026.105549","url":null,"abstract":"<div><div>In seasonal tropical dry forests, warmer and drier climate conditions projected for the coming decades may reduce the distribution ranges of many woody plants, threatening biodiversity maintenance. Using ecological niche modelling for 70 endemic woody plant species of the Brazilian Caatinga, we assessed how climate change may affect structural and phylogenetic dimensions of assemblages that evolved exclusively within this ecosystem. Models were run for the current period, 2041–2060, and 2081–2100 under two greenhouse gas emission scenarios. By 2100, at least 70 % of species are projected to lose suitable habitat, and up to 11 % may become globally extinct under the pessimistic scenario. The effects of climate change are consistent across both narrow- and wide-range species. Species richness, phylogenetic diversity, and phylogenetic structure are projected to decline across the Caatinga. The number of phylogenetically clustered assemblages is expected to increase by 85–237 %, depending on the phylogenetic metric and climate scenario, whereas the number of overdispersed assemblages is expected to decline. Overall, the impacts of climate change on Caatinga biodiversity may be more severe than previously reported, with the ecosystem projected to host impoverished assemblages of endemic woody plants and lose substantial evolutionary history by the end of this century.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"233 ","pages":"Article 105549"},"PeriodicalIF":2.5,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145976656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2026-01-05DOI: 10.1016/j.jaridenv.2025.105548
Margareta Lakušić , Myrto Roumelioti , Fulvio Licata , Marcello Bilancioni , Diogo F. Ferreira , Leili Khalatbari , Vidak Lakušić , André Vicente Liz , Raquel N. de Oliveira , Bárbara Santos , Yuri Simone , László Patkó , Ayman Abdulkarem , Benjamin P.Y-H. Lee , Magdy El-Bana , Ahmed Al-Ansari , Omar Al-Attas , José Carlos Brito
Body colouration is involved in multiple aspects of species ecology and behaviour. Melanism, a common colour polymorphism, has been associated with camouflage and thermoregulation, particularly in diverse, high-altitude habitats of arid regions. This study reports the first case of melanism in the lacertid Acanthodactylus boskianus, two scorpions, Leiurus haenggii and Compsobuthus manzonii, and the first records of brown-black melanistic colouration in three rodent species, Acomys dimidiatus, Meriones crassus, and Sekeetamys calurus, in the dark lava fields (harrat) of north-western Saudi Arabia. Additionally, it expands observations of melanism in the endemic colubrid Rhynchocalamus hejazicus and provides the first documented records of brown-black melanistic Acomys russatus for the region, consistent with earlier predictions. These observations suggest that colour polymorphism may serve a cryptic function through background matching in both diurnal and nocturnal species, but other roles of melanism should be further investigated. Despite their extent, lava fields in arid regions remain poorly studied due to their remoteness and limited accessibility, yet they offer unique opportunities to investigate phenotypic evolution in arid ecosystems.
{"title":"Melanism in scorpions, reptiles and rodents inhabiting the volcanic fields of north-western Saudi Arabia","authors":"Margareta Lakušić , Myrto Roumelioti , Fulvio Licata , Marcello Bilancioni , Diogo F. Ferreira , Leili Khalatbari , Vidak Lakušić , André Vicente Liz , Raquel N. de Oliveira , Bárbara Santos , Yuri Simone , László Patkó , Ayman Abdulkarem , Benjamin P.Y-H. Lee , Magdy El-Bana , Ahmed Al-Ansari , Omar Al-Attas , José Carlos Brito","doi":"10.1016/j.jaridenv.2025.105548","DOIUrl":"10.1016/j.jaridenv.2025.105548","url":null,"abstract":"<div><div>Body colouration is involved in multiple aspects of species ecology and behaviour. Melanism, a common colour polymorphism, has been associated with camouflage and thermoregulation, particularly in diverse, high-altitude habitats of arid regions. This study reports the first case of melanism in the lacertid <em>Acanthodactylus boskianus</em>, two scorpions, <em>Leiurus haenggii</em> and <em>Compsobuthus manzonii</em>, and the first records of brown-black melanistic colouration in three rodent species, <em>Acomys dimidiatus</em>, <em>Meriones crassus</em>, and <em>Sekeetamys calurus</em>, in the dark lava fields (<em>harrat</em>) of north-western Saudi Arabia. Additionally, it expands observations of melanism in the endemic colubrid <em>Rhynchocalamus hejazicus</em> and provides the first documented records of brown-black melanistic <em>Acomys russatus</em> for the region, consistent with earlier predictions. These observations suggest that colour polymorphism may serve a cryptic function through background matching in both diurnal and nocturnal species, but other roles of melanism should be further investigated. Despite their extent, lava fields in arid regions remain poorly studied due to their remoteness and limited accessibility, yet they offer unique opportunities to investigate phenotypic evolution in arid ecosystems.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"233 ","pages":"Article 105548"},"PeriodicalIF":2.5,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145939030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-26DOI: 10.1016/j.jaridenv.2025.105547
Robert G. Delaney, Andrew M. Folkard, James D. Whyatt
Remote sensing plays a pivotal role in water harvesting studies by enabling the collection and interpretation of spatial data across extensive regions. This paper examines 290 peer-reviewed articles to assess the adoption and utilisation of remote sensing in water harvesting research. Findings reveal that remote sensing is widely used, with around 92 % of studies published in 2023 incorporating such data. The most frequently used include digital elevation models (DEMs) such as SRTM (91 studies) and ASTER GDEM (60 studies), multi-spectral datasets like Landsat (117 studies), and climatic products such as TRMM (20 studies). DEMs are predominantly used for hydrological modelling, while multi-spectral imagery sources facilitate land use and land cover (LULC) mapping, often through bespoke classification rather than the use of pre-existing global datasets. Despite the critical role of rainfall in water harvesting, the adoption of satellite-derived climatic data remains limited, with researchers often relying on in situ measurements. This review highlights the advantages of extracting multiple thematic layers from a single remote sensing source to ensure consistency in resolution and coverage. Additionally, data fusion techniques are increasingly important for integrating disparate datasets, though challenges remain in reconciling differing spatial and temporal resolutions. This review demonstrates the increasing reliance on remote sensing in water harvesting research while identifying gaps, such as the underutilization of high-resolution climatic imagery sources and products. Evidence-based recommendations are provided to guide future research, including the selection of appropriate DEMs, the adoption of satellite-derived rainfall data, and the optimisation of multi-source data fusion. The findings highlight the need for researchers to adopt a more systematic approach in documenting and detailing the remote sensing sources and products used, to enhance their utility in water harvesting applications.
{"title":"Remote sensing imagery and products used in water harvesting studies: a review","authors":"Robert G. Delaney, Andrew M. Folkard, James D. Whyatt","doi":"10.1016/j.jaridenv.2025.105547","DOIUrl":"10.1016/j.jaridenv.2025.105547","url":null,"abstract":"<div><div>Remote sensing plays a pivotal role in water harvesting studies by enabling the collection and interpretation of spatial data across extensive regions. This paper examines 290 peer-reviewed articles to assess the adoption and utilisation of remote sensing in water harvesting research. Findings reveal that remote sensing is widely used, with around 92 % of studies published in 2023 incorporating such data. The most frequently used include digital elevation models (DEMs) such as SRTM (91 studies) and ASTER GDEM (60 studies), multi-spectral datasets like Landsat (117 studies), and climatic products such as TRMM (20 studies). DEMs are predominantly used for hydrological modelling, while multi-spectral imagery sources facilitate land use and land cover (LULC) mapping, often through bespoke classification rather than the use of pre-existing global datasets. Despite the critical role of rainfall in water harvesting, the adoption of satellite-derived climatic data remains limited, with researchers often relying on <em>in situ</em> measurements. This review highlights the advantages of extracting multiple thematic layers from a single remote sensing source to ensure consistency in resolution and coverage. Additionally, data fusion techniques are increasingly important for integrating disparate datasets, though challenges remain in reconciling differing spatial and temporal resolutions. This review demonstrates the increasing reliance on remote sensing in water harvesting research while identifying gaps, such as the underutilization of high-resolution climatic imagery sources and products. Evidence-based recommendations are provided to guide future research, including the selection of appropriate DEMs, the adoption of satellite-derived rainfall data, and the optimisation of multi-source data fusion. The findings highlight the need for researchers to adopt a more systematic approach in documenting and detailing the remote sensing sources and products used, to enhance their utility in water harvesting applications.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"233 ","pages":"Article 105547"},"PeriodicalIF":2.5,"publicationDate":"2025-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840462","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-22DOI: 10.1016/j.jaridenv.2025.105543
José Laurindo dos Santos Júnior , Guilherme Alcântara Matos , Elizamar Ciríaco da Silva
High temperature is a critical environmental factor that impacts seed bank persistence and limits recruitment, particularly hindering regeneration dynamics in arid and semi-arid ecosystems. Given global climate change, understanding how seeds respond to such conditions is crucial for ecosystem resilience and its capacity for natural regeneration. This study investigated how temporal exposure to high temperatures affects the germination and early growth of Sapindus saponaria L., a species found in the Caatinga ecosystem that contributes to seed bank formation. Seeds were exposed to high temperatures (70 °C) for 15, 45, 60, and 90 min, corresponding to the estimated soil surface temperatures and exposition times recorded during the peak solar irradiance period in semi-arid regions. Seed germination, seedling growth, and vigor were evaluated. Exposure of S. saponaria seeds to high temperatures for moderate durations (45 and 60 min) improved germination and seed vigor. Furthermore, seedlings exhibited greater vigor and vegetative growth. Moderate exposure to high temperatures may optimize germination and early seedling vigor in S. saponaria, potentially enhancing the recruitment of new individuals in warm environments.
{"title":"Inhibition or stimulation: effect of high temperature on the seed germination and vigor, and impacts on seedling growth of Sapindus saponaria L","authors":"José Laurindo dos Santos Júnior , Guilherme Alcântara Matos , Elizamar Ciríaco da Silva","doi":"10.1016/j.jaridenv.2025.105543","DOIUrl":"10.1016/j.jaridenv.2025.105543","url":null,"abstract":"<div><div>High temperature is a critical environmental factor that impacts seed bank persistence and limits recruitment, particularly hindering regeneration dynamics in arid and semi-arid ecosystems. Given global climate change, understanding how seeds respond to such conditions is crucial for ecosystem resilience and its capacity for natural regeneration. This study investigated how temporal exposure to high temperatures affects the germination and early growth of <em>Sapindus saponaria</em> L., a species found in the Caatinga ecosystem that contributes to seed bank formation. Seeds were exposed to high temperatures (70 °C) for 15, 45, 60, and 90 min, corresponding to the estimated soil surface temperatures and exposition times recorded during the peak solar irradiance period in semi-arid regions. Seed germination, seedling growth, and vigor were evaluated. Exposure of <em>S. saponaria</em> seeds to high temperatures for moderate durations (45 and 60 min) improved germination and seed vigor. Furthermore, seedlings exhibited greater vigor and vegetative growth. Moderate exposure to high temperatures may optimize germination and early seedling vigor in <em>S. saponaria</em>, potentially enhancing the recruitment of new individuals in warm environments.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"233 ","pages":"Article 105543"},"PeriodicalIF":2.5,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840461","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-22DOI: 10.1016/j.jaridenv.2025.105545
Etinosa Igunbor , Jennie DeMarco , Philip Crossley
Restored wet meadows and sagebrush in the western United States present unique challenges for soil organic carbon (SOC) prediction due to their topographic complexity and ecological heterogeneity. While remote sensing (RS) and machine learning (ML) have shown promise in SOC modeling, the influence of RS temporal averaging and terrain data (TD) on model performance remains poorly understood in these landscapes. This study compares four commonly used SOC prediction models; random forest (RF), generalized additive model (GAM), partial least squares regression (PLSR), and stepwise linear regression (SLR), using averaged RS-derived data alone and in combination with TD and evaluates how different RS averaging periods affect prediction accuracy. These models were applied to RS metrics averaging over 1-day, 3-year, and 5-year periods, in combination with TD covariates (slope, aspect, topographic position index, elevation). The GAM model using NDVI, GSI, and CI performed best (Sapinero 1-day, R2 = 0.44; Wolf Creek 3-year, R2 = 0.29), with accuracy improving when TD was included (Sapinero 5-year, R2 = 0.48; Wolf Creek 1-day, R2 = 0.49). We found that GAMs offer a more robust SOC prediction performance, particularly in complex, restored landscapes, particularly when longer-term averaged RS data is used. Hence, our results highlight that remote sensing can be a low cost and accurate tool for estimating SOC in sagebrush and wet meadow ecosystems within the arid ecosystems.
美国西部恢复的湿草甸和山艾树由于其地形复杂性和生态异质性，对土壤有机碳（SOC）预测提出了独特的挑战。虽然遥感（RS）和机器学习（ML）在SOC建模中显示出前景，但在这些景观中，RS时间平均和地形数据（TD）对模型性能的影响仍然知之甚少。本研究比较了四种常用的有机碳预测模型；随机森林（RF）、广义加性模型（GAM）、偏最小二乘回归（PLSR）和逐步线性回归（SLR），分别使用RS平均数据单独和结合TD，并评估不同RS平均周期对预测精度的影响。这些模型结合TD协变量（坡度、坡向、地形位置指数、高程），应用于1天、3年和5年期间的RS指标均值。采用NDVI、GSI和CI的GAM模型表现最佳（Sapinero 1天，R2 = 0.44； Wolf Creek 3年，R2 = 0.29），当纳入TD时准确性提高（Sapinero 5年，R2 = 0.48； Wolf Creek 1天，R2 = 0.49）。我们发现GAMs提供了更强大的SOC预测性能，特别是在复杂的恢复景观中，特别是当使用长期平均RS数据时。因此，我们的研究结果表明，在干旱生态系统中，遥感可以作为一种低成本和准确的工具来估算山艾树和湿草甸生态系统的有机碳。
{"title":"Remote sensing-based modeling of soil organic carbon in wet meadow and sagebrush ecosystems in semi-arid landscapes","authors":"Etinosa Igunbor , Jennie DeMarco , Philip Crossley","doi":"10.1016/j.jaridenv.2025.105545","DOIUrl":"10.1016/j.jaridenv.2025.105545","url":null,"abstract":"<div><div>Restored wet meadows and sagebrush in the western United States present unique challenges for soil organic carbon (SOC) prediction due to their topographic complexity and ecological heterogeneity. While remote sensing (RS) and machine learning (ML) have shown promise in SOC modeling, the influence of RS temporal averaging and terrain data (TD) on model performance remains poorly understood in these landscapes. This study compares four commonly used SOC prediction models; random forest (RF), generalized additive model (GAM), partial least squares regression (PLSR), and stepwise linear regression (SLR), using averaged RS-derived data alone and in combination with TD and evaluates how different RS averaging periods affect prediction accuracy. These models were applied to RS metrics averaging over 1-day, 3-year, and 5-year periods, in combination with TD covariates (slope, aspect, topographic position index, elevation). The GAM model using NDVI, GSI, and CI performed best (Sapinero 1-day, R<sup>2</sup> = 0.44; Wolf Creek 3-year, R<sup>2</sup> = 0.29), with accuracy improving when TD was included (Sapinero 5-year, R<sup>2</sup> = 0.48; Wolf Creek 1-day, R<sup>2</sup> = 0.49). We found that GAMs offer a more robust SOC prediction performance, particularly in complex, restored landscapes, particularly when longer-term averaged RS data is used. Hence, our results highlight that remote sensing can be a low cost and accurate tool for estimating SOC in sagebrush and wet meadow ecosystems within the arid ecosystems.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"233 ","pages":"Article 105545"},"PeriodicalIF":2.5,"publicationDate":"2025-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145840463","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dust storms pose significant environmental and health challenges in arid regions, necessitating accurate modeling for effective mitigation strategies. This study employed thirteen machine learning (MLs) and deep learning (DLs) models to identify dust-prone areas and evaluate the impact of various environmental drivers on dust storms. A set of variables, including evapotranspiration (ET), air temperature, land surface temperature, vegetation indices, mean precipitation (Pr), soil moisture, and six drought indices (Standardized Precipitation Index (SPI), Vegetation Health Index (VHI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Soil Vegetation Index (SVI), and Palmer Drought Severity Index (PDSI)), was analyzed using Aerosol Optical Depth (AOD) as the target variable. The analysis revealed that tree-based MLs outperformed DLs in this study area, potentially due to the regional scale and dataset characteristics. Random Forest (RF) emerged as the most outstanding model, achieving exceptional accuracy in both regression (R2 > 0.96, RMSE = 0.01, MAE = 0.01) and classification tasks (Critical Success Index = 0.70, Recall = 0.76), along with a Bias value of 1.038 and 85 % overall accuracy in spatial detection of dust sources. Among DLs, Artificial Neural Network (ANN) showed competitive performance as a reliable alternative. Variable importance analysis identified temperature, precipitation, and ET as the most influential predictors, followed by soil moisture and PDSI. The findings provide a good framework for dust susceptibility mapping and highlight the advantage of tree-based MLs for dust modeling in regional-scale studies.
{"title":"Modeling dust storms using machine learning and deep learning techniques","authors":"Mohammad Kazemi , Marzieh Rezaei , Sedigheh Mousaei , Narges Kariminejad","doi":"10.1016/j.jaridenv.2025.105542","DOIUrl":"10.1016/j.jaridenv.2025.105542","url":null,"abstract":"<div><div>Dust storms pose significant environmental and health challenges in arid regions, necessitating accurate modeling for effective mitigation strategies. This study employed thirteen machine learning (MLs) and deep learning (DLs) models to identify dust-prone areas and evaluate the impact of various environmental drivers on dust storms. A set of variables, including evapotranspiration (ET), air temperature, land surface temperature, vegetation indices, mean precipitation (Pr), soil moisture, and six drought indices (Standardized Precipitation Index (SPI), Vegetation Health Index (VHI), Vegetation Condition Index (VCI), Temperature Condition Index (TCI), Soil Vegetation Index (SVI), and Palmer Drought Severity Index (PDSI)), was analyzed using Aerosol Optical Depth (AOD) as the target variable. The analysis revealed that tree-based MLs outperformed DLs in this study area, potentially due to the regional scale and dataset characteristics. Random Forest (RF) emerged as the most outstanding model, achieving exceptional accuracy in both regression (R<sup>2</sup> > 0.96, RMSE = 0.01, MAE = 0.01) and classification tasks (Critical Success Index = 0.70, Recall = 0.76), along with a Bias value of 1.038 and 85 % overall accuracy in spatial detection of dust sources. Among DLs, Artificial Neural Network (ANN) showed competitive performance as a reliable alternative. Variable importance analysis identified temperature, precipitation, and ET as the most influential predictors, followed by soil moisture and PDSI. The findings provide a good framework for dust susceptibility mapping and highlight the advantage of tree-based MLs for dust modeling in regional-scale studies.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"233 ","pages":"Article 105542"},"PeriodicalIF":2.5,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145798286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-18DOI: 10.1016/j.jaridenv.2025.105546
Mia Brann , Karen Haubensak , Catherine Gehring , Sara Souther
Dryland managers face a dilemma balancing prescribed fire use with rare species conservation. In semi-arid grasslands and woodlands, managers often avoid burning habitats with threatened plants, though fire may reduce competition from invasive grasses and support native persistence. In the Madrean Sky Islands of southeastern Arizona, drought, altered fire regimes, and non-native species encroachment are transforming lower elevation grasslands and woodlands, home to the endangered forb, Pectis imberbis. These stressors interact in complex ways, yet cumulative effects on rare species like P. imberbis remain poorly understood. We conducted a fully factorial greenhouse experiment to test how fire, drought, and competition affect P. imberbis. Plants were grown from seed with intra- and interspecific competitors, then exposed to fire and drought. After 39 weeks, we measured above- and belowground biomass. Interspecific competition and drought reduced biomass, but burning appeared to ameliorate interspecific competition's negative effects. Pectis imberbis resprouted robustly after fire—even under drought and competition—though drought and intraspecific competition delayed resprouting. Our findings indicate prescribed fire may provide a safe and effective way to manage P. imberbis habitat while supporting broader goals such as invasive species control.
{"title":"Fire resilience and altered competitive dynamics of the endangered forb Pectis imberbis show potential for prescribed fire as a conservation tool","authors":"Mia Brann , Karen Haubensak , Catherine Gehring , Sara Souther","doi":"10.1016/j.jaridenv.2025.105546","DOIUrl":"10.1016/j.jaridenv.2025.105546","url":null,"abstract":"<div><div>Dryland managers face a dilemma balancing prescribed fire use with rare species conservation. In semi-arid grasslands and woodlands, managers often avoid burning habitats with threatened plants, though fire may reduce competition from invasive grasses and support native persistence. In the Madrean Sky Islands of southeastern Arizona, drought, altered fire regimes, and non-native species encroachment are transforming lower elevation grasslands and woodlands, home to the endangered forb, <em>Pectis imberbis</em>. These stressors interact in complex ways, yet cumulative effects on rare species like <em>P. imberbis</em> remain poorly understood. We conducted a fully factorial greenhouse experiment to test how fire, drought, and competition affect <em>P. imberbis</em>. Plants were grown from seed with intra- and interspecific competitors, then exposed to fire and drought. After 39 weeks, we measured above- and belowground biomass. Interspecific competition and drought reduced biomass, but burning appeared to ameliorate interspecific competition's negative effects. <em>Pectis imberbis</em> resprouted robustly after fire—even under drought and competition—though drought and intraspecific competition delayed resprouting. Our findings indicate prescribed fire may provide a safe and effective way to manage <em>P. imberbis</em> habitat while supporting broader goals such as invasive species control.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"233 ","pages":"Article 105546"},"PeriodicalIF":2.5,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145798285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-16DOI: 10.1016/j.jaridenv.2025.105544
Thamara Fariñas-Torres , Eliana F. Burgos , Maria A. Chemisquy
The province of La Rioja is one of the most neglected regarding the knowledge of its biological diversity, and particularly the study of the mammals in the Sierra de Velasco has been reduced to a few articles. This paper aims to study the richness and distribution of the small mammals of the Sierra de Velasco and the environmental factors that influence the assemblage in an environmental gradient. Samplings were made with Sherman-like traps for 9330 trap nights. For the analysis of assemblage variation, an environmental gradient was established based on several characteristics, and three types of environments were delimited: Ravines, Shrublands, and Rocky fields. Alpha and beta diversity were calculated using Hills numbers, and species richness correlation with environmental variables associations was evaluated. Small mammal species richness was up to seven and was higher in the shrublands environment decreasing towards the extremes of the gradient, with the lowest richness found in the rocky fields’ environment. The richness was mainly correlated to variations in the average elevation of the sampling sites. This is an initial approach to understanding the relationships between small rodent species and environmental variations present in the arid mountains of the Sierra de Velasco.
{"title":"Small rodent assemblage variation across a mountain gradient in an arid region of northwestern Argentina","authors":"Thamara Fariñas-Torres , Eliana F. Burgos , Maria A. Chemisquy","doi":"10.1016/j.jaridenv.2025.105544","DOIUrl":"10.1016/j.jaridenv.2025.105544","url":null,"abstract":"<div><div>The province of La Rioja is one of the most neglected regarding the knowledge of its biological diversity, and particularly the study of the mammals in the Sierra de Velasco has been reduced to a few articles. This paper aims to study the richness and distribution of the small mammals of the Sierra de Velasco and the environmental factors that influence the assemblage in an environmental gradient. Samplings were made with Sherman-like traps for 9330 trap nights. For the analysis of assemblage variation, an environmental gradient was established based on several characteristics, and three types of environments were delimited: Ravines, Shrublands, and Rocky fields. Alpha and beta diversity were calculated using Hills numbers, and species richness correlation with environmental variables associations was evaluated. Small mammal species richness was up to seven and was higher in the shrublands environment decreasing towards the extremes of the gradient, with the lowest richness found in the rocky fields’ environment. The richness was mainly correlated to variations in the average elevation of the sampling sites. This is an initial approach to understanding the relationships between small rodent species and environmental variations present in the arid mountains of the Sierra de Velasco.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"233 ","pages":"Article 105544"},"PeriodicalIF":2.5,"publicationDate":"2025-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145798287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-10DOI: 10.1016/j.jaridenv.2025.105529
Juma Ayoub Tegeje , Msafiri Yusuph Mkonda , Zarah Pattison , Charles Joseph Kilawe
There is a limited information on the effects of Neltuma spp. on herbaceous species. This study assessed the effects of Neltuma spp. on herbaceous species in the drylands of northern Tanzania in 250 sampling quadrats established in the invaded and uninvaded areas. In each quadrat, information on herbaceous species composition, abundance, basal cover, and diversity was collected and compared between the two areas using Generalized Linear Mixed Models. Non-metric Multidimensional Scaling and Indicator Species analyses were applied to visualize patterns in species composition and identify species significantly associated with invaded and uninvaded areas, respectively. Results revealed that herbaceous species abundance, basal cover, and diversity were significantly (p < 0.001) lower in invaded areas compared to uninvaded areas. Soil moisture had a significant (p < 0.05) positive effect on herbaceous species. Species composition differed substantially between invaded and uninvaded areas. Digitaria velutina, Eragrostis superba, Eriochloa fatmensis, Pennisetum mezianum, and Indigofera atriceps were indicators of uninvaded areas, while Tragia insuavis was the indicator of invaded areas. Indicator species from uninvaded areas provide important socio-economic benefits. The continuing spread of Neltuma spp. threatens the sustainability of these benefits, calling for targeted management to curb their spread and preserve ecosystem functions in affected drylands.
{"title":"The invasion by Neltuma spp. changes herbaceous vegetation communities in Northern Tanzania","authors":"Juma Ayoub Tegeje , Msafiri Yusuph Mkonda , Zarah Pattison , Charles Joseph Kilawe","doi":"10.1016/j.jaridenv.2025.105529","DOIUrl":"10.1016/j.jaridenv.2025.105529","url":null,"abstract":"<div><div>There is a limited information on the effects of <em>Neltuma</em> spp. on herbaceous species. This study assessed the effects of <em>Neltuma</em> spp<em>.</em> on herbaceous species in the drylands of northern Tanzania in 250 sampling quadrats established in the invaded and uninvaded areas. In each quadrat, information on herbaceous species composition, abundance, basal cover, and diversity was collected and compared between the two areas using Generalized Linear Mixed Models. Non-metric Multidimensional Scaling and Indicator Species analyses were applied to visualize patterns in species composition and identify species significantly associated with invaded and uninvaded areas, respectively. Results revealed that herbaceous species abundance, basal cover, and diversity were significantly (<em>p</em> < 0.001) lower in invaded areas compared to uninvaded areas. Soil moisture had a significant (<em>p</em> < 0.05) positive effect on herbaceous species. Species composition differed substantially between invaded and uninvaded areas. <em>Digitaria velutina, Eragrostis superba, Eriochloa fatmensis, Pennisetum mezianum</em>, and <em>Indigofera atriceps</em> were indicators of uninvaded areas, while <em>Tragia insuavis</em> was the indicator of invaded areas. Indicator species from uninvaded areas provide important socio-economic benefits. The continuing spread of <em>Neltuma</em> spp. threatens the sustainability of these benefits, calling for targeted management to curb their spread and preserve ecosystem functions in affected drylands.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"233 ","pages":"Article 105529"},"PeriodicalIF":2.5,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145749046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-09DOI: 10.1016/j.jaridenv.2025.105541
Fujin Xu , Junchen Long , Changchun Xu
Accurate quantification of ecosystem carbon fixation is essential for carbon accounting and climate governance. However, the limited temporal coverage of remote sensing observations introduces substantial uncertainty in vegetation carbon sink estimates. Identifying errors and their drivers when extrapolating instantaneous to daily gross primary production (GPP) is therefore critical. Here, we used observations from 28 eddy covariance flux sites across major ecosystems in China to estimate instantaneous GPP at six local times (07:30–17:30 at 2 h intervals). Daily GPP was then derived from these instantaneous estimates using a cosine solar zenith angle [cos(SZA)]-based upscaling approach. A hybrid analytical framework combining triple collocation with in situ measurements was applied to evaluate the accuracy of these daily estimates. Results indicate that (1) extrapolation errors exhibit strong diurnal phase dependence, being lowest near noon (R ≈ 0.83, RMSE ≈ 1.26 gC m−2 d−1) but significantly higher during morning and evening (R ≈ 0.61, RMSE ≈ 2.34 gC m−2 d−1), reflecting nonlinear photosynthetic responses to photosynthetically active radiation; (2) grasslands consistently show lower errors than forests and other high-productivity ecosystems, highlighting ecosystem effects on accuracy; and (3) near noon, photosynthetic midday depression causes systematic underestimation (mostly within ±20 %, −356.3 to 52.7 tC km−2 yr−1), whereas morning and evening estimates show both underestimation and overestimation with much larger deviations (up to −1249.8 to 929.9 tC km−2 yr−1, often > ±50 %). In contrast to previous studies that are limited to qualitative analyses of single time periods or ecosystems, this study systematically characterized diurnal- and ecosystem-dependent error patterns in GPP extrapolation, clarifying cos(SZA)-based upscaling limitations. Findings emphasize the importance of scheduling satellite overpasses near solar noon and integrating ecological heterogeneity and stress factors into algorithms to improve accuracy and support reliable carbon sink assessments.
{"title":"Quantifying the accuracy of cos(SZA)-based upscaling from instantaneous to daily GPP: Implications for improving satellite-based SIF and GPP retrievals","authors":"Fujin Xu , Junchen Long , Changchun Xu","doi":"10.1016/j.jaridenv.2025.105541","DOIUrl":"10.1016/j.jaridenv.2025.105541","url":null,"abstract":"<div><div>Accurate quantification of ecosystem carbon fixation is essential for carbon accounting and climate governance. However, the limited temporal coverage of remote sensing observations introduces substantial uncertainty in vegetation carbon sink estimates. Identifying errors and their drivers when extrapolating instantaneous to daily gross primary production (GPP) is therefore critical. Here, we used observations from 28 eddy covariance flux sites across major ecosystems in China to estimate instantaneous GPP at six local times (07:30–17:30 at 2 h intervals). Daily GPP was then derived from these instantaneous estimates using a cosine solar zenith angle [cos(SZA)]-based upscaling approach. A hybrid analytical framework combining triple collocation with in situ measurements was applied to evaluate the accuracy of these daily estimates. Results indicate that (1) extrapolation errors exhibit strong diurnal phase dependence, being lowest near noon (R ≈ 0.83, RMSE ≈ 1.26 gC m<sup>−2</sup> d<sup>−1</sup>) but significantly higher during morning and evening (R ≈ 0.61, RMSE ≈ 2.34 gC m<sup>−2</sup> d<sup>−1</sup>), reflecting nonlinear photosynthetic responses to photosynthetically active radiation; (2) grasslands consistently show lower errors than forests and other high-productivity ecosystems, highlighting ecosystem effects on accuracy; and (3) near noon, photosynthetic midday depression causes systematic underestimation (mostly within ±20 %, −356.3 to 52.7 tC km<sup>−2</sup> yr<sup>−1</sup>), whereas morning and evening estimates show both underestimation and overestimation with much larger deviations (up to −1249.8 to 929.9 tC km<sup>−2</sup> yr<sup>−1</sup>, often > ±50 %). In contrast to previous studies that are limited to qualitative analyses of single time periods or ecosystems, this study systematically characterized diurnal- and ecosystem-dependent error patterns in GPP extrapolation, clarifying cos(SZA)-based upscaling limitations. Findings emphasize the importance of scheduling satellite overpasses near solar noon and integrating ecological heterogeneity and stress factors into algorithms to improve accuracy and support reliable carbon sink assessments.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"233 ","pages":"Article 105541"},"PeriodicalIF":2.5,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145749047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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