Pub Date : 2026-02-01Epub Date: 2025-11-07DOI: 10.1016/j.jaridenv.2025.105515
Lawrence E. Steyn , Kathryn S. Williams , Gareth K.H. Mann , Anita Wilkinson , Greg Distiller
Knowledge of leopard (Panthera pardus) persistence over time in mixed-use landscapes is limited, particularly in semi-arid regions of southern Africa. This study aimed to estimate leopard population changes over time and to investigate possible drivers affecting density, using three camera trap surveys (2012, 2017, 2022), in the Little Karoo, Western Cape, South Africa. To our knowledge, this is the only multi-session spatial capture-recapture (SCR) analysis conducted in a semi-arid southern Africa environment encompassing both protected and non-protected areas. The best-performing density model indicated that the leopard population remained stable with a density of 0.92 leopards per 100 km2 (95 % CI: 0.74–1.16) over the study period. Terrain ruggedness was an important driver of leopard density, indicating that rugged elevated areas are key leopard habitat within the region. This study shows that a charismatic species can survive in a mixed-use landscape abundant with anthropogenic threats. It further serves to highlight the value of multi-session SCR modelling in developing targeted conservation efforts.
关于豹（Panthera pardus）在混合用途景观中持续存在的知识有限，特别是在非洲南部半干旱地区。本研究旨在估计豹子种群随时间的变化，并调查影响密度的可能驱动因素，使用三次相机陷阱调查（2012年，2017年，2022年），在南非西开普省的小卡鲁。据我们所知，这是唯一一个在半干旱的南部非洲环境中进行的多时段空间捕获-再捕获（SCR）分析，包括受保护和非受保护的地区。最优密度模型表明，在研究期间，豹子种群保持稳定，密度为0.92只/ 100 km2 （95% CI: 0.74 ~ 1.16）。地形起伏度是豹密度的重要驱动因素，表明地形起伏的高架地区是该地区豹的主要栖息地。这项研究表明，一个有魅力的物种可以在一个充满人为威胁的混合用途景观中生存。它进一步强调了多阶段SCR模型在制定有针对性的保护工作中的价值。
{"title":"Tails Through Time: Leopard population dynamics in the Little Karoo","authors":"Lawrence E. Steyn , Kathryn S. Williams , Gareth K.H. Mann , Anita Wilkinson , Greg Distiller","doi":"10.1016/j.jaridenv.2025.105515","DOIUrl":"10.1016/j.jaridenv.2025.105515","url":null,"abstract":"<div><div>Knowledge of leopard (<em>Panthera pardus</em>) persistence over time in mixed-use landscapes is limited, particularly in semi-arid regions of southern Africa. This study aimed to estimate leopard population changes over time and to investigate possible drivers affecting density, using three camera trap surveys (2012, 2017, 2022), in the Little Karoo, Western Cape, South Africa. To our knowledge, this is the only multi-session spatial capture-recapture (SCR) analysis conducted in a semi-arid southern Africa environment encompassing both protected and non-protected areas. The best-performing density model indicated that the leopard population remained stable with a density of 0.92 leopards per 100 km<sup>2</sup> (95 % CI: 0.74–1.16) over the study period. Terrain ruggedness was an important driver of leopard density, indicating that rugged elevated areas are key leopard habitat within the region. This study shows that a charismatic species can survive in a mixed-use landscape abundant with anthropogenic threats. It further serves to highlight the value of multi-session SCR modelling in developing targeted conservation efforts.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"232 ","pages":"Article 105515"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145736468","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}
High-altitude freshwater lakes and their associated fish communities in Morocco's Middle Atlas are undergoing an unprecedented ecological collapse, driven by compounded hydrological stress arising from both anthropogenic pressures and climate change. Using multi-temporal Sentinel-2 imagery (2017–2024) and the Normalised Difference Water Index (NDWI), we quantified surface water changes across eight lakes. Six lakes (Dayet Ifrah, Hachlaf, Aoua, Afennourir, Afourgagh, and Tamda) experienced complete desiccation, while Aguelmam Azegza and Sidi Ali lost 52 % and 34 % of their surface water, respectively. These severe hydrological regressions are attributed to the combined effects of climate warming, regional rainfall deficits, and intensifying heatwaves, compounded by unsustainable land use and water overexploitation. Ichthyological surveys revealed local extinctions in desiccated lakes. The ecological consequences extend beyond biodiversity loss, as key ecosystem services, including fisheries, lake-based tourism, the conservation value of Ramsar wetlands, and freshwater provision, have been severely disrupted, with socio-economic repercussions for local communities.
Our findings underscore the role of Middle Atlas lakes as climate sentinels and highlight the need to integrate satellite-based hydrological monitoring with field-based ecological assessments. Urgent adaptive ecohydrological strategies are required to prevent further biodiversity loss and ensure long-term socio-ecological resilience in North Africa's montane environments.
摩洛哥中部阿特拉斯的高海拔淡水湖及其相关鱼类群落正在经历前所未有的生态崩溃，这是由人为压力和气候变化引起的复合水文压力造成的。利用2017-2024年的Sentinel-2多时相影像和Normalised Difference Water Index (NDWI)，我们量化了8个湖泊的地表水变化。六个湖泊（Dayet Ifrah、Hachlaf、Aoua、Afennourir、Afourgagh和Tamda）完全干涸，而Aguelmam Azegza和Sidi Ali分别损失了52%和34%的地表水。这些严重的水文退化可归因于气候变暖、区域降雨不足和热浪加剧的综合影响，再加上不可持续的土地利用和水资源过度开发。鱼类学调查揭示了干涸湖泊的局部灭绝。其生态后果不仅限于生物多样性的丧失，重要的生态系统服务，包括渔业、湖泊旅游、拉姆萨尔湿地的保护价值和淡水供应，都受到严重破坏，对当地社区产生了社会经济影响。我们的研究结果强调了阿特拉斯中部湖泊作为气候哨兵的作用，并强调了将基于卫星的水文监测与基于野外的生态评估相结合的必要性。迫切需要采取适应性生态水文战略，以防止生物多样性进一步丧失，并确保北非山区环境的长期社会生态复原力。
{"title":"Accelerating collapse of freshwater ecosystems and fish communities in North Africa's Middle Atlas under combined climatic and anthropogenic pressures","authors":"Yassine Baladia , Abderrafea Elbahi , Nezha Laadel , Abdelkhalek Zraouti , Jaouad Abou Oualid","doi":"10.1016/j.jaridenv.2025.105517","DOIUrl":"10.1016/j.jaridenv.2025.105517","url":null,"abstract":"<div><div>High-altitude freshwater lakes and their associated fish communities in Morocco's Middle Atlas are undergoing an unprecedented ecological collapse, driven by compounded hydrological stress arising from both anthropogenic pressures and climate change. Using multi-temporal Sentinel-2 imagery (2017–2024) and the Normalised Difference Water Index (NDWI), we quantified surface water changes across eight lakes. Six lakes (Dayet Ifrah, Hachlaf, Aoua, Afennourir, Afourgagh, and Tamda) experienced complete desiccation, while Aguelmam Azegza and Sidi Ali lost 52 % and 34 % of their surface water, respectively. These severe hydrological regressions are attributed to the combined effects of climate warming, regional rainfall deficits, and intensifying heatwaves, compounded by unsustainable land use and water overexploitation. Ichthyological surveys revealed local extinctions in desiccated lakes. The ecological consequences extend beyond biodiversity loss, as key ecosystem services, including fisheries, lake-based tourism, the conservation value of Ramsar wetlands, and freshwater provision, have been severely disrupted, with socio-economic repercussions for local communities.</div><div>Our findings underscore the role of Middle Atlas lakes as climate sentinels and highlight the need to integrate satellite-based hydrological monitoring with field-based ecological assessments. Urgent adaptive ecohydrological strategies are required to prevent further biodiversity loss and ensure long-term socio-ecological resilience in North Africa's montane environments.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"232 ","pages":"Article 105517"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145519518","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 : 2026-02-01Epub Date: 2025-11-29DOI: 10.1016/j.jaridenv.2025.105530
Jianyang Shi, Minxia Liu, Siyi Cheng, Jing Yuan
The Yellow River Basin is an important ecologically vulnerable region in China. The response of vegetation growth to climate change and drought stress in this region requires urgent clarification. This study aims to investigate the differential inhibitory effects of drought on carbon uptake across 15 ecosystems and to examine the mechanisms underlying these changes. In our analyses, we used multiple methods, including trend analysis, structural equation modeling (SEM), and ridge regression, and integrated multi-source remote sensing data, including the Standardized Precipitation Evapotranspiration Index (SPEI), precipitation (Prec), and temperature (Ta). The results indicate that: (1) Grassland GPP showed widespread declines in the middle and lower reaches, suggesting that grasslands were the most sensitive to drought stress. (2) Grasslands primarily exhibited lagged responses of 4 months, whereas croplands responded with shorter, 1-month lags. In contrast, Forests showed cumulative responses over 10–12 months. Additionally, high-resilience croplands were expanding along the Henan–Shandong axis. Forest resilience was lowest in the semi-arid northwest region and in Ningxia across the basin. (3) Prec was identified as the primary positive driver of basin-wide GPP. Grassland GPP was directly regulated by Prec, whereas cropland GPP was mainly limited by photosynthetically active radiation (PAR), although soil moisture (SM) could mitigate drought stress. In forest ecosystems, vapor pressure deficit (VPD) was the key limiting factor, and elevated Ta intensified the negative effects of drought by reducing SM. This research will contribute to strengthening future ecosystem management and mitigating the threats of climate change to ecosystems.
{"title":"Response of gross primary productivity of vegetation to meteorological drought in the Yellow River Basin","authors":"Jianyang Shi, Minxia Liu, Siyi Cheng, Jing Yuan","doi":"10.1016/j.jaridenv.2025.105530","DOIUrl":"10.1016/j.jaridenv.2025.105530","url":null,"abstract":"<div><div>The Yellow River Basin is an important ecologically vulnerable region in China. The response of vegetation growth to climate change and drought stress in this region requires urgent clarification. This study aims to investigate the differential inhibitory effects of drought on carbon uptake across 15 ecosystems and to examine the mechanisms underlying these changes. In our analyses, we used multiple methods, including trend analysis, structural equation modeling (SEM), and ridge regression, and integrated multi-source remote sensing data, including the Standardized Precipitation Evapotranspiration Index (SPEI), precipitation (Prec), and temperature (Ta). The results indicate that: (1) Grassland GPP showed widespread declines in the middle and lower reaches, suggesting that grasslands were the most sensitive to drought stress. (2) Grasslands primarily exhibited lagged responses of 4 months, whereas croplands responded with shorter, 1-month lags. In contrast, Forests showed cumulative responses over 10–12 months. Additionally, high-resilience croplands were expanding along the Henan–Shandong axis. Forest resilience was lowest in the semi-arid northwest region and in Ningxia across the basin. (3) Prec was identified as the primary positive driver of basin-wide GPP. Grassland GPP was directly regulated by Prec, whereas cropland GPP was mainly limited by photosynthetically active radiation (PAR), although soil moisture (SM) could mitigate drought stress. In forest ecosystems, vapor pressure deficit (VPD) was the key limiting factor, and elevated Ta intensified the negative effects of drought by reducing SM. This research will contribute to strengthening future ecosystem management and mitigating the threats of climate change to ecosystems.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"232 ","pages":"Article 105530"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145617945","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}
Climate change is closely linked to agricultural production and water resource utilization,and rationally assessing crop water productivity (WP) under future climate conditions is crucial for the Hetao Irrigation District (HID) in Inner Mongolia, China to adapt to climate change. However, quantitative analyses exploring the response of the WP to future climate change by coupling the Statistical Downscaling Model (SDSM) and distributed SWAP-WOFOST model at the regional scale remain scarce. In this study, the SDSM was constructed, calibrated and validated to predict and analyze the future major meteorological elements. Temporal and spatial distributions of yields and WP for the three crops in the future scenarios were simulated and analyzed by model coupling. To improve crop WP, the planting structure of the three crops was adjusted by the “Z-score normalization” method for future climate conditions. The results showed that temperature and precipitation will exhibit considerable fluctuations in the future, with increases up to 3.53 °C in maximum temperature, 2.53 °C in minimum temperature, and 75.7 % in precipitation, while variations in relative humidity and solar radiation remain minor. Under both Representative Concentration Pathway (RCP) scenarios, yields and WP declined over time, with reductions of 32.5 %–53.4 % (yield) and 34.0 %–49.3 % (WP) by the 2050s, with RCP8.5 exhibiting greater declines. Adjusted planting structures improved sunflower WP by 3.7 %–6.3 % in the 2030s and 2050s, spring wheat yield by 2.4 %–3.1 % in the 2030s, and spring maize by 6.1 %–9.1 % in the 2050s. The findings provide quantitative references for irrigation districts to address future climate challenges. Keywords: SDSM; Distributed SWAP-WOFOST model; Climate change; Hetao Irrigation District; Water productivity; Planting structure zoning.
{"title":"Assessing the impact of climate change on crop water productivity: Historical simulations and future projections for the Hetao Irrigation District","authors":"Jing Xue , Hanxiao Bian , Junfeng Chen , Lihong Cui","doi":"10.1016/j.jaridenv.2025.105525","DOIUrl":"10.1016/j.jaridenv.2025.105525","url":null,"abstract":"<div><div>Climate change is closely linked to agricultural production and water resource utilization,and rationally assessing crop water productivity (WP) under future climate conditions is crucial for the Hetao Irrigation District (HID) in Inner Mongolia, China to adapt to climate change. However, quantitative analyses exploring the response of the WP to future climate change by coupling the Statistical Downscaling Model (SDSM) and distributed SWAP-WOFOST model at the regional scale remain scarce. In this study, the SDSM was constructed, calibrated and validated to predict and analyze the future major meteorological elements. Temporal and spatial distributions of yields and WP for the three crops in the future scenarios were simulated and analyzed by model coupling. To improve crop WP, the planting structure of the three crops was adjusted by the “Z-score normalization” method for future climate conditions. The results showed that temperature and precipitation will exhibit considerable fluctuations in the future, with increases up to 3.53 °C in maximum temperature, 2.53 °C in minimum temperature, and 75.7 % in precipitation, while variations in relative humidity and solar radiation remain minor. Under both Representative Concentration Pathway (RCP) scenarios, yields and WP declined over time, with reductions of 32.5 %–53.4 % (yield) and 34.0 %–49.3 % (WP) by the 2050s, with RCP8.5 exhibiting greater declines. Adjusted planting structures improved sunflower WP by 3.7 %–6.3 % in the 2030s and 2050s, spring wheat yield by 2.4 %–3.1 % in the 2030s, and spring maize by 6.1 %–9.1 % in the 2050s. The findings provide quantitative references for irrigation districts to address future climate challenges. <strong>Keywords</strong>: SDSM; Distributed SWAP-WOFOST model; Climate change; Hetao Irrigation District; Water productivity; Planting structure zoning.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"232 ","pages":"Article 105525"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145571731","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 : 2026-02-01Epub Date: 2026-01-20DOI: 10.1016/j.jaridenv.2026.105553
Jia Qu , Qi Liu , Dongwei Gui , Yunfei Liu , Xinlong Feng , Sameh Kotb Abd-Elmabod , Haolin Wang , Jianping Zhao , Mengtao Ci
Forestation plays a pivotal role in arid regions to mitigate climate change and land degradation. However, conventional tree planting initiatives frequently fail to emulate the ecological services provided by natural forests, and may threaten natural environments. Here, we integrated Variational Inference into a one-dimensional convolutional neural network (1DCNN) to facilitate near-natural forestation planning with uncertainty quantification in arid regions. The model was compared with machine learning approaches and exemplarily applied in the lower Tarim River Basin (LTRB), which is one of the largest inland basins around the world and has carried out long-term restoration actions. The results demonstrated that: 1) The Variational 1DCNN outperformed conventional models by up to 13.1 % in accuracy, and avoiding the overestimation of the forestation area (106–142 %) observed in traditional approaches. 2) The locations of potential afforestation areas with low uncertainty in LTRB are highly consistent with the actual situation and are primarily distributed near river channels. 3) Hydrological and topographical factors exerted a great influence on the uncertainty in potential forestation simulations. The near-natural forestation model developed here exhibits satisfactory performance in forestation opportunity prediction, and uncertainty quantification can enhance sustainable forestation planning in arid regions.
{"title":"Quantifying uncertainty for near-natural forestation in arid regions","authors":"Jia Qu , Qi Liu , Dongwei Gui , Yunfei Liu , Xinlong Feng , Sameh Kotb Abd-Elmabod , Haolin Wang , Jianping Zhao , Mengtao Ci","doi":"10.1016/j.jaridenv.2026.105553","DOIUrl":"10.1016/j.jaridenv.2026.105553","url":null,"abstract":"<div><div>Forestation plays a pivotal role in arid regions to mitigate climate change and land degradation. However, conventional tree planting initiatives frequently fail to emulate the ecological services provided by natural forests, and may threaten natural environments. Here, we integrated Variational Inference into a one-dimensional convolutional neural network (1DCNN) to facilitate near-natural forestation planning with uncertainty quantification in arid regions. The model was compared with machine learning approaches and exemplarily applied in the lower Tarim River Basin (LTRB), which is one of the largest inland basins around the world and has carried out long-term restoration actions. The results demonstrated that: 1) The Variational 1DCNN outperformed conventional models by up to 13.1 % in accuracy, and avoiding the overestimation of the forestation area (106–142 %) observed in traditional approaches. 2) The locations of potential afforestation areas with low uncertainty in LTRB are highly consistent with the actual situation and are primarily distributed near river channels. 3) Hydrological and topographical factors exerted a great influence on the uncertainty in potential forestation simulations. The near-natural forestation model developed here exhibits satisfactory performance in forestation opportunity prediction, and uncertainty quantification can enhance sustainable forestation planning in arid regions.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"233 ","pages":"Article 105553"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038017","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 : 2026-02-01Epub Date: 2026-01-22DOI: 10.1016/j.jaridenv.2026.105551
Esayas Embaye Kidane
This study aimed to assess the impact of armed conflict on human-primate conflict, primate conservation, and community perceptions in Hugumburda dry Afromontane Forest, northern Ethiopia. The study was conducted in between November 2024 and February 2025. A mixed-methods research approach was adopted to select 275 villagers to examine the impact of armed conflict on primate conservation, human-primate conflict, community perceptions of primate conservation, and potential scenarios for primate conservation. Respondents were reported monkeys and baboons raided 16 crop species, with wheat (Triticum aestivum) was the most vulnerable. A total of 792.05 quintals of crops, valued at US$40,346.43 were lost due to baboon and monkey raids. 47 % of respondents reported an increase in crop damage since the outbreak of the armed conflict. Displacement of primates (49.09 %), and weakened traditional conservation practices (48.73 %) were identified as the major impacts of armed conflict on primate conservation. The majority of respondents (Perception Index = 80.90) supported primate conservation through the establishment of buffer zones. Crop guarding (Relative Ranking Index = 0.31) remained the most commonly reported crop-raiding mitigation measures. The findings demonstrate that armed conflict multiplies both economic losses and ecological risks, underscoring the urgency of integrating post-conflict recovery with sustainable conservation strategies.
{"title":"Bullets and wildlife: Navigating the conservation and economic determinants of human-nonhuman primate conflict in armed conflict Tigray, northern Ethiopia","authors":"Esayas Embaye Kidane","doi":"10.1016/j.jaridenv.2026.105551","DOIUrl":"10.1016/j.jaridenv.2026.105551","url":null,"abstract":"<div><div>This study aimed to assess the impact of armed conflict on human-primate conflict, primate conservation, and community perceptions in Hugumburda dry Afromontane Forest, northern Ethiopia. The study was conducted in between November 2024 and February 2025. A mixed-methods research approach was adopted to select 275 villagers to examine the impact of armed conflict on primate conservation, human-primate conflict, community perceptions of primate conservation, and potential scenarios for primate conservation. Respondents were reported monkeys and baboons raided 16 crop species, with wheat (<em>Triticum aestivum</em>) was the most vulnerable. A total of 792.05 quintals of crops, valued at US$40,346.43 were lost due to baboon and monkey raids. 47 % of respondents reported an increase in crop damage since the outbreak of the armed conflict. Displacement of primates (49.09 %), and weakened traditional conservation practices (48.73 %) were identified as the major impacts of armed conflict on primate conservation. The majority of respondents (Perception Index = 80.90) supported primate conservation through the establishment of buffer zones. Crop guarding (Relative Ranking Index = 0.31) remained the most commonly reported crop-raiding mitigation measures. The findings demonstrate that armed conflict multiplies both economic losses and ecological risks, underscoring the urgency of integrating post-conflict recovery with sustainable conservation strategies.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"233 ","pages":"Article 105551"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038018","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 : 2026-02-01Epub 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":"2026-02-01","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}
The Araba Valley, spanning southeastern Israel and southwestern Jordan, was a major center of copper mining and smelting in antiquity. Located deep in the arid deserts of the southern Levant, the region retains one of the best-preserved archaeological records of metallurgical activity in the world. Copper production was concentrated in four principal industrial hubs: the Faynan region and Wadi Abu Khushayba in the eastern Araba, and the Timna Valley and Nahal Amram in the southwest. Beyond these well-known centers, the valley also contains a number of isolated mining sites that have received little scholarly attention. This study seeks to clarify the spatial organization and technological variability of copper mining in the Araba Valley, with particular emphasis on evaluating evidence for decentralized production beyond the major industrial complexes. We present detailed documentation of 14 mining sites with excavated volumes ranging from tens to thousands of cubic meters. Most of these mines are isolated, located at considerable distances from the principal production centers, and vary from small surface pits to extensive underground workings. Despite their peripheral locations, these mines likely played an important role in the regional copper industry, reflecting flexible, locally managed exploitation strategies and underscoring the significance of independent mining initiatives within the broader metallurgical landscape of the Araba Valley. More broadly, this study provides essential baseline data for understanding ancient copper production networks spanning the Mediterranean and beyond, from the Chalcolithic through the Late Islamic period.
阿拉巴河谷横跨以色列东南部和约旦西南部，是古代铜矿开采和冶炼的主要中心。该地区位于黎凡特南部干旱的沙漠深处，是世界上保存最完好的冶金活动考古记录之一。铜生产集中在四个主要工业中心：阿拉伯东部的Faynan地区和Wadi Abu Khushayba，以及西南部的Timna山谷和Nahal Amram。除了这些著名的中心，山谷中还有一些孤立的矿区，这些矿区很少受到学术界的关注。本研究旨在澄清阿拉巴河谷铜矿开采的空间组织和技术变异性，特别强调评价主要工业综合体以外分散生产的证据。我们提供了14个采矿地点的详细文件，挖掘量从数万立方米到数千立方米不等。这些矿山大多是孤立的，距离主要生产中心相当远，从小型的地表矿坑到广泛的地下矿坑不等。这些矿山虽然处于外围位置，但可能在区域铜工业中发挥了重要作用，反映了当地管理的灵活开采战略，并强调了在阿拉巴河谷更广泛的冶金景观中独立采矿倡议的重要性。更广泛地说，这项研究为了解从铜器时代到伊斯兰晚期跨越地中海及其他地区的古代铜生产网络提供了必要的基线数据。
{"title":"Copper mines in the Araba Valley (SE Israel & SW Jordan): Spatial distribution, site typology and new discoveries","authors":"Boaz Langford , Ilya Kutuzov , Amos Frumkin , Erez Ben-Yosef","doi":"10.1016/j.jaridenv.2026.105557","DOIUrl":"10.1016/j.jaridenv.2026.105557","url":null,"abstract":"<div><div>The Araba Valley, spanning southeastern Israel and southwestern Jordan, was a major center of copper mining and smelting in antiquity. Located deep in the arid deserts of the southern Levant, the region retains one of the best-preserved archaeological records of metallurgical activity in the world. Copper production was concentrated in four principal industrial hubs: the Faynan region and Wadi Abu Khushayba in the eastern Araba, and the Timna Valley and Nahal Amram in the southwest. Beyond these well-known centers, the valley also contains a number of isolated mining sites that have received little scholarly attention. This study seeks to clarify the spatial organization and technological variability of copper mining in the Araba Valley, with particular emphasis on evaluating evidence for decentralized production beyond the major industrial complexes. We present detailed documentation of 14 mining sites with excavated volumes ranging from tens to thousands of cubic meters. Most of these mines are isolated, located at considerable distances from the principal production centers, and vary from small surface pits to extensive underground workings. Despite their peripheral locations, these mines likely played an important role in the regional copper industry, reflecting flexible, locally managed exploitation strategies and underscoring the significance of independent mining initiatives within the broader metallurgical landscape of the Araba Valley. More broadly, this study provides essential baseline data for understanding ancient copper production networks spanning the Mediterranean and beyond, from the Chalcolithic through the Late Islamic period.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"233 ","pages":"Article 105557"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077607","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}
Efficient use of nitrogen and water is vital for sustaining crop production in arid regions. A field experiment was conducted to assess the effects of arbuscular mycorrhizal fungi (AMF) inoculation (inoculated vs. non-inoculated), three irrigation water regimes (IWR; 50%, 75%, and 100% of crop requirement), and five nitrogen rates (0, 46, 92, 138, and 184 kg/ha) on tef (Eragrostis tef). AMF, IWR, and N significantly influenced grain nitrogen, zinc, iron, and selenium uptake, grain protein content (GPC), agronomic use efficiency (AUE), physiological use efficiency (PUE), apparent recovery efficiency (ARE), and water use efficiency (WUE), while site and season were not significant (P > 0.05). Under 100% IWR with AMF inoculation, and 184 kg/ha N recorded increases of 793% in grain N, 468% in Zn, 502% in Fe, 488% in Se, 131% in GPC, and 583% in WUE compared to the lowest input treatment. Importantly, AMF inoculation with 92 kg/ha N optimized AUE (37.2 kg/kg) and PUE (83.3 kg/kg), representing increases of 233% and 93% relative to non-inoculated controls. Integrating AMF with 92 kg/ha N inputs enhances nutrient acquisition, protein content, and water productivity, providing a sustainable pathway to improve crop performance in resource-limited arid environments.
{"title":"Mycorrhizal symbiosis in Eragrostis tef enhances nutrient uptake and efficiency under soil and water stress in semi-arid regions","authors":"Kidu Gebremeskel , Emiru Birhane , Mitiku Haile , Solomon Habtu , Zerihun Tadele , Solomon Chanyalew , Kbebew Assefa","doi":"10.1016/j.jaridenv.2025.105503","DOIUrl":"10.1016/j.jaridenv.2025.105503","url":null,"abstract":"<div><div>Efficient use of nitrogen and water is vital for sustaining crop production in arid regions. A field experiment was conducted to assess the effects of arbuscular mycorrhizal fungi (AMF) inoculation (inoculated vs. non-inoculated), three irrigation water regimes (IWR; 50%, 75%, and 100% of crop requirement), and five nitrogen rates (0, 46, 92, 138, and 184 kg/ha) on tef (<em>Eragrostis tef</em>). AMF, IWR, and N significantly influenced grain nitrogen, zinc, iron, and selenium uptake, grain protein content (GPC), agronomic use efficiency (AUE), physiological use efficiency (PUE), apparent recovery efficiency (ARE), and water use efficiency (WUE), while site and season were not significant (P > 0.05). Under 100% IWR with AMF inoculation, and 184 kg/ha N recorded increases of 793% in grain N, 468% in Zn, 502% in Fe, 488% in Se, 131% in GPC, and 583% in WUE compared to the lowest input treatment. Importantly, AMF inoculation with 92 kg/ha N optimized AUE (37.2 kg/kg) and PUE (83.3 kg/kg), representing increases of 233% and 93% relative to non-inoculated controls. Integrating AMF with 92 kg/ha N inputs enhances nutrient acquisition, protein content, and water productivity, providing a sustainable pathway to improve crop performance in resource-limited arid environments.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"232 ","pages":"Article 105503"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145320414","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 : 2026-02-01Epub Date: 2025-10-14DOI: 10.1016/j.jaridenv.2025.105504
Francisca Soares Araújo , Fernanda Kelly Gomes Silva , Fernando Roberto Martins , Jean-Francois Mas , Marie-Pierre Ledru , Maria Virginia Oliveira Silva , Carlos Eduardo Carvalho , Daniel Pontes Oliveira , Bruno Sousa Menezes
Several models explain succession in secondary forests, but none are universally accepted. Classical models suggest species replacement, while newer ones propose that early species may persist throughout succession. To better understand how species composition and groups change over time in the Caatinga, we analyzed the structure and organization of plant communities in 13 fragments aged between 7 and 52+ years. We sampled the woody component within a 10 × 100 m plot, recording species richness, abundance, and floristic composition. Species richness increased throughout succession, but most species (66 %) found in the early stages (7–15 yr) persisted across the chronosequence, including in the old-growth forest. Communities' age did not affect soil properties, suggesting no abiotic improvement during succession. However, species composition varied with vegetation age (F = 54.7; df = 11; p-value = 0.003). Changes in the abundance of dominant species and the gradual accumulation of rare species have explained this variation. We concluded that the Caatinga follows an alternative succession model that integrates elements from different theoretical frameworks. Due to its open physiognomy and sparse canopy, shade tolerance is not key for succession. Instead, early species remain dominant across all stages, while rarer species accumulate over time.
{"title":"Secondary succession in the Caatinga is composed of species that persist throughout all chronosequence","authors":"Francisca Soares Araújo , Fernanda Kelly Gomes Silva , Fernando Roberto Martins , Jean-Francois Mas , Marie-Pierre Ledru , Maria Virginia Oliveira Silva , Carlos Eduardo Carvalho , Daniel Pontes Oliveira , Bruno Sousa Menezes","doi":"10.1016/j.jaridenv.2025.105504","DOIUrl":"10.1016/j.jaridenv.2025.105504","url":null,"abstract":"<div><div>Several models explain succession in secondary forests, but none are universally accepted. Classical models suggest species replacement, while newer ones propose that early species may persist throughout succession. To better understand how species composition and groups change over time in the Caatinga, we analyzed the structure and organization of plant communities in 13 fragments aged between 7 and 52+ years. We sampled the woody component within a 10 × 100 m plot, recording species richness, abundance, and floristic composition. Species richness increased throughout succession, but most species (66 %) found in the early stages (7–15 yr) persisted across the chronosequence, including in the old-growth forest. Communities' age did not affect soil properties, suggesting no abiotic improvement during succession. However, species composition varied with vegetation age (F = 54.7; df = 11; p-value = 0.003). Changes in the abundance of dominant species and the gradual accumulation of rare species have explained this variation. We concluded that the Caatinga follows an alternative succession model that integrates elements from different theoretical frameworks. Due to its open physiognomy and sparse canopy, shade tolerance is not key for succession. Instead, early species remain dominant across all stages, while rarer species accumulate over time.</div></div>","PeriodicalId":51080,"journal":{"name":"Journal of Arid Environments","volume":"232 ","pages":"Article 105504"},"PeriodicalIF":2.5,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145320415","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号