Journal of Arid Environments最新文献_第2页

Inhibition or stimulation: effect of high temperature on the seed germination and vigor, and impacts on seedling growth of Sapindus saponaria L 抑制或刺激：高温对皂荚种子萌发和活力的影响及对幼苗生长的影响

IF 2.5 3区环境科学与生态学 Q2 ECOLOGY

Journal of Arid Environments

Pub Date : 2025-12-22 DOI: 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.

高温是影响种子库持久性和限制种子补充的关键环境因素，特别是阻碍干旱和半干旱生态系统的更新动态。考虑到全球气候变化，了解种子如何应对这些条件对于生态系统的恢复力及其自然再生能力至关重要。摘要本研究研究了在Caatinga生态系统中发现的Sapindus saponaria L.对种子库形成的影响，研究了高温对Sapindus saponaria L.萌发和早期生长的影响。将种子暴露在高温（70°C）下15、45、60和90分钟，对应于半干旱区太阳辐照峰值期间土壤表面温度和暴露时间的估计。对种子萌发、幼苗生长和活力进行了评价。将皂角草种子在高温下适当暴露45和60分钟，提高了种子的萌发和活力。幼苗表现出更强的活力和营养生长。适度的高温暴露可以优化皂角草的萌发和早期幼苗活力，并有可能在温暖环境中促进新个体的招募。

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引用次数: 0

Remote sensing-based modeling of soil organic carbon in wet meadow and sagebrush ecosystems in semi-arid landscapes 半干旱区湿草甸和山艾草生态系统土壤有机碳遥感模拟

IF 2.5 3区环境科学与生态学 Q2 ECOLOGY

Journal of Arid Environments

Pub Date : 2025-12-22 DOI: 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。

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引用次数: 0

Modeling dust storms using machine learning and deep learning techniques 使用机器学习和深度学习技术模拟沙尘暴

IF 2.5 3区环境科学与生态学 Q2 ECOLOGY

Journal of Arid Environments

Pub Date : 2025-12-18 DOI: 10.1016/j.jaridenv.2025.105542

Mohammad Kazemi , Marzieh Rezaei , Sedigheh Mousaei , Narges Kariminejad

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.

沙尘暴给干旱地区带来了重大的环境和健康挑战，需要为有效的缓解战略建立准确的模型。本研究采用了13种机器学习（ml）和深度学习（dl）模型来识别粉尘易发区域，并评估各种环境驱动因素对沙尘暴的影响。以气溶胶光学深度（AOD）为目标变量，对蒸散发（ET）、气温、地表温度、植被指数、平均降水（Pr）、土壤湿度和6个干旱指数（标准化降水指数（SPI）、植被健康指数（VHI）、植被状况指数（VCI）、温度状况指数（TCI）、土壤植被指数（SVI）和帕尔默干旱严重程度指数（PDSI））进行分析。分析表明，基于树的机器学习在本研究区域的表现优于人工学习，这可能与区域规模和数据集特征有关。随机森林（Random Forest， RF）是最突出的模型，在回归（R2 > 0.96, RMSE = 0.01, MAE = 0.01）和分类任务（临界成功指数= 0.70，召回率= 0.76）中都取得了优异的准确性，在尘源空间检测中，偏差值为1.038，总体准确率为85%。其中，人工神经网络（ANN）作为一种可靠的替代方法表现出竞争力。变量重要性分析发现，温度、降水和ET是影响最大的预测因子，其次是土壤湿度和PDSI。研究结果为沙尘敏感性制图提供了一个良好的框架，并突出了基于树的模型分析在区域尺度沙尘模拟中的优势。

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引用次数: 0

Fire resilience and altered competitive dynamics of the endangered forb Pectis imberbis show potential for prescribed fire as a conservation tool 火恢复力和改变竞争动态的濒危草本植物柏树显示了规定火作为保护工具的潜力

IF 2.5 3区环境科学与生态学 Q2 ECOLOGY

Journal of Arid Environments

Pub Date : 2025-12-18 DOI: 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.

旱地管理者面临着平衡规定的火灾使用和稀有物种保护的两难境地。在半干旱的草原和林地，管理者通常避免焚烧有受威胁植物的栖息地，尽管火灾可能会减少来自入侵草的竞争，并支持原生植物的生存。在亚利桑那州东南部的马德兰天空群岛，干旱、改变的火灾制度和非本地物种的入侵正在改变低海拔的草原和林地，这些地方是濒临灭绝的牧草，山核桃的家园。这些压力源以复杂的方式相互作用，但对像云杉这样的稀有物种的累积效应仍然知之甚少。我们进行了全因子温室试验，以测试火、干旱和竞争对云杉的影响。植物从种内和种间竞争者的种子中生长，然后暴露于火和干旱中。39周后，我们测量了地上和地下的生物量。种间竞争和干旱减少了生物量，但燃烧似乎改善了种间竞争的负面影响。尽管干旱和种内竞争延缓了再生，但火灾后果木的再生依然强劲，即使是在干旱和竞争条件下。我们的研究结果表明，在支持诸如入侵物种控制等更广泛的目标的同时，规定火可能提供一种安全有效的方法来管理云杉栖息地。

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引用次数: 0

Small rodent assemblage variation across a mountain gradient in an arid region of northwestern Argentina 阿根廷西北部干旱地区小啮齿动物群落在山区梯度上的变化

IF 2.5 3区环境科学与生态学 Q2 ECOLOGY

Journal of Arid Environments

Pub Date : 2025-12-16 DOI: 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.

里奥哈省在生物多样性知识方面是最被忽视的省份之一，特别是对贝拉斯科山脉哺乳动物的研究已经减少到几篇文章。本文旨在研究贝拉斯科山小兽类的丰富度和分布，以及在一定的环境梯度下影响其组合的环境因素。用谢尔曼式陷阱对9330个陷阱夜进行取样。为分析组合变化，基于若干特征建立了环境梯度，划分了沟谷、灌丛和岩田3种环境类型。利用希尔斯数计算α和β多样性，并评价物种丰富度与环境变量的相关性。小哺乳动物物种丰富度在灌丛环境中最高，在梯度极值处呈递减趋势，在石质地环境中最低。丰富度主要与样点平均海拔的变化有关。这是理解小型啮齿动物物种与贝拉斯科山脉干旱山区环境变化之间关系的初步方法。

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引用次数: 0

The invasion by Neltuma spp. changes herbaceous vegetation communities in Northern Tanzania Neltuma的入侵改变了坦桑尼亚北部的草本植被群落

IF 2.5 3区环境科学与生态学 Q2 ECOLOGY

Journal of Arid Environments

Pub Date : 2025-12-10 DOI: 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.

关于Neltuma sp .对草本物种的影响的信息有限。本研究评估了Neltuma spp.对坦桑尼亚北部旱地草本物种的影响，在入侵和未入侵地区建立了250个采样样方。利用广义线性混合模型（Generalized Linear Mixed Models）对各样方的草本物种组成、丰度、基础盖度和多样性进行比较。采用非度量的多维尺度分析和指标物种分析，分别对入侵区和非入侵区有显著相关性的物种进行可视化分析。结果表明，入侵区草本物种丰度、基础盖度和多样性显著低于未入侵区（p < 0.001）。土壤湿度对草本植物有显著的正向影响（p < 0.05）。物种组成在入侵区和非入侵区之间存在显著差异。毛柳Digitaria velutina， Eragrostis superba, Eriochloa fatmensis, Pennisetum mezianum， Indigofera apriceps为未入侵区，黄花蓟马（Tragia insuavis）为入侵区。来自未被入侵地区的指示物种提供了重要的社会经济效益。Neltuma的持续传播威胁到这些利益的可持续性，呼吁有针对性的管理，以遏制其传播并保护受影响旱地的生态系统功能。

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引用次数: 0

Quantifying the accuracy of cos(SZA)-based upscaling from instantaneous to daily GPP: Implications for improving satellite-based SIF and GPP retrievals 基于cos（SZA）的从瞬时到每日GPP升级的精度量化：对改进卫星SIF和GPP检索的意义

IF 2.5 3区环境科学与生态学 Q2 ECOLOGY

Journal of Arid Environments

Pub Date : 2025-12-09 DOI: 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.

生态系统碳固定的准确量化对于碳核算和气候治理至关重要。然而，遥感观测的有限时间覆盖给植被碳汇估算带来了很大的不确定性。因此，在推断瞬时到每日初级生产总值（GPP）时，识别错误及其驱动因素至关重要。利用中国主要生态系统28个涡动相关通量站点的观测数据，估算了6个当地时间（07:30-17:30，间隔2 h）的瞬时GPP。然后使用余弦太阳天顶角[cos(SZA)]为基础的升级方法从这些瞬时估计中导出每日GPP。结合三重配置和原位测量的混合分析框架被应用于评估这些每日估计的准确性。结果表明：(1)外推误差表现出较强的日相位依赖性，在中午附近最小（R≈0.83,RMSE≈1.26 gC m−2 d−1），而在早晨和傍晚显著增大（R≈0.61,RMSE≈2.34 gC m−2 d−1），反映了光合作用对光合有效辐射的非线性响应；(2)草地的误差始终低于森林和其他高产生态系统，生态系统对精度的影响显著；(3)正午附近，光合作用午间抑制导致系统性低估（大多数在±20%，−356.3至52.7 tC km−2 yr−1），而早晨和晚上的估计显示低估和高估，偏差更大（高达−1249.8至929.9 tC km−2 yr−1，通常为±50%）。与以往的研究局限于单个时间段或生态系统的定性分析相比，本研究系统地表征了GPP外推中依赖于日和生态系统的误差模式，阐明了基于cos（SZA）的升级限制。研究结果强调了在太阳正午附近安排卫星立交桥的重要性，并将生态异质性和压力因素整合到算法中，以提高准确性并支持可靠的碳汇评估。

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引用次数: 0

Strength in numbers: Group size enhances individual survival and colony longevity in Damaraland mole-rats Fukomys damarensis 数量优势：群体规模可提高达马拉地鼠的个体存活率和群体寿命

IF 2.5 3区环境科学与生态学 Q2 ECOLOGY

Journal of Arid Environments

Pub Date : 2025-12-09 DOI: 10.1016/j.jaridenv.2025.105540

Paul Juan Jacobs , Daniel William Hart , Jennifer U.M. Jarvis , Nigel Charles Bennett

Cooperative behaviour presents an evolutionary paradox because although dispersal may increase direct fitness, many individuals forego reproduction to assist others. In arid-dwelling subterranean mammals, the high energetic costs of underground foraging, together with scarce and patchily distributed food resources are thought to have favoured the evolution of group living and cooperative breeding. These social systems are believed to enhance foraging efficiency and improve the survival prospects of individuals and groups. Using a longitudinal dataset from a wild population of Damaraland mole-rats (Fukomys damarensis) in arid central Namibia, we examine how group size predicts survival and persistence at both the individual and group levels. Our findings show that larger groups confer significant apparent survival benefits, that is the probability that an individual survives and remains available for recapture or resighting, reflecting both true survival and site fidelity, and also enhance colony persistence relative to solitary animals or pairs. We further demonstrate that these very small social-unit states are inherently unstable as without increases in group size, they are unlikely to persist within the population for extended periods. Larger groups clearly enhance survival, making remaining in the natal colony more beneficial than dispersing in an arid environment where dispersal is highly risky.

合作行为呈现出一种进化悖论，因为尽管分散可能增加直接适应性，但许多个体为了帮助其他个体而放弃繁殖。在干旱地区生活的地下哺乳动物中，地下觅食的高能量消耗，加上食物资源的稀缺和分布不均，被认为有利于群体生活和合作繁殖的进化。这些社会系统被认为可以提高觅食效率，改善个体和群体的生存前景。利用来自纳米比亚中部干旱地区的达马拉兰鼹鼠（Fukomys damarensis）野生种群的纵向数据集，我们研究了群体大小如何在个体和群体水平上预测生存和持久性。我们的研究结果表明，较大的群体具有明显的生存优势，即个体存活的可能性，并且仍然可以重新捕获或重新安置，这反映了真实的生存和地点保真度，并且相对于孤独的动物或成对的动物，也增强了群体的持久性。我们进一步证明，这些非常小的社会单位状态本质上是不稳定的，因为没有群体规模的增加，它们不太可能在人群中持续很长一段时间。更大的群体显然提高了生存能力，留在出生的群体比分散在干旱的环境中更有利，因为在干旱的环境中分散是非常危险的。

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引用次数: 0

Using spatial water balance to regionalize long-term mean streamflow in a data-scarce Brazilian semi-arid basin 利用空间水平衡对数据稀缺的巴西半干旱盆地长期平均流量进行区划

IF 2.5 3区环境科学与生态学 Q2 ECOLOGY

Journal of Arid Environments

Pub Date : 2025-12-05 DOI: 10.1016/j.jaridenv.2025.105528

Arthur Kolling Neto , Rayssa Balieiro Ribeiro , Fernando Falco Pruski

The use of spatial data can enable the estimation of water availability in semi-arid regions with limited monitoring. This study evaluated regionalization models of long-term mean streamflow in the Paraguaçu river basin, Bahia state, using explanatory variables derived from measured data and spatial products of precipitation and actual evapotranspiration from TerraClimate. The potential model was fitted using multiple regression and evaluated through statistical, physical, and risk analyses. Long-term mean streamflow (Q_mlt) was estimated by univariate potential regionalization in hydrologically homogeneous sub-basins of the Paraguaçu river, comparing predictors based on drainage area (A), equivalent precipitation (Peq), and water balance (WB = P−AET) derived from observed data and spatial products (TerraClimate). Leave-one-station-out (LOSO) validation and a physical–hydrological verification via runoff coefficient along the river network indicated that A tends to overestimate flows in semiarid sectors; Peq improves the fit but ignores evapotranspiration losses; the spatial WB achieved the best overall performance and greater physical consistency. The model with entirely spatial WB showed the best results and the lowest hydrological risk for extrapolation. The approach, using open data and tools, is reproducible and useful for management in regions with sparse monitoring.

利用空间数据可以在监测有限的情况下估计半干旱区的可用水量。本文利用TerraClimate降水和实际蒸散发空间产品的解释变量，对巴伊亚州巴拉圭河流域长期平均流量区划模型进行了评价。使用多元回归拟合潜在模型，并通过统计、物理和风险分析进行评估。通过比较观测数据和空间产品（TerraClimate）得出的流域面积(A)、等效降水（Peq）和水平衡（WB = P−AET）的预测因子，对巴拉圭河水文均质次流域进行了单变量潜在区划，估算了长期平均流量（Qmlt）。LOSO验证和沿河网径流系数的物理水文验证表明，a倾向于高估半干旱区的流量；Peq改善了拟合，但忽略了蒸散损失；空间WB实现了最佳的整体性能和更大的物理一致性。全空间WB模型外推效果最好，水文风险最低。该方法使用开放数据和工具，具有可重复性，对监测较少的地区的管理很有用。

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引用次数: 0

Climate-growth relationships in the introduced dominant woody tree Neltuma juliflora in Santiago Island, Cabo Verde Archipelago (Eastern Atlantic) 东大西洋佛得角群岛圣地亚哥岛引种优势木本树的气候-生长关系

IF 2.5 3区环境科学与生态学 Q2 ECOLOGY

Journal of Arid Environments

Pub Date : 2025-12-04 DOI: 10.1016/j.jaridenv.2025.105532

Daniel Semedo , Diogo C. Pavão , Lurdes Borges Silva , Guilherme Roxo , Roberto Resendes , Maria Romeiras , Mónica Moura , Luís Silva

Neltuma juliflora (syn. Prosopis juliflora) is the dominant woody species in Cabo Verde, introduced through extensive reforestation efforts to combat land degradation. Despite its ecological and socio-economic relevance, little is known about its growth dynamics and climatic sensitivity in this region. This study investigates growth ring formation and climate–growth relationships of N. juliflora on Santiago Island. We sampled 165 trees across 11 blocks, grouped into four bioclimatic zones. Tree-ring widths were measured using standard dendrochronological techniques. Generalised Linear Models (GLMs) were applied to assess the influence of climatic variables, with multicollinearity controlled using the Variance Inflation Factor (VIF). Although false rings were present, distinct growth boundaries were observed. Mean radial growth varied from 1.53 to 2.11 mm/year across bioclimatic zones. The best GLMs suggest that higher precipitation outside of the usual rainy season could negatively affect growth, while mean annual temperature could have a marginally positive effect. Significant differences in tree-ring growth rate were observed between trees sampled at the four bioclimatic areas, likely reflecting the influence of climate and elevation, and of other factors such as soil and tree density. These results highlight the ecological plasticity of N. juliflora and support its potential use in dendroclimatic research in semi-arid tropical regions. These findings have significant implications for ecosystem-based adaptation strategies and sustainable land management practices in Cabo Verde, particularly in the context of climate change and land degradation mitigation. The study underscores the need for longer chronologies and expanded geographic sampling across the archipelago in future work.

朱莉叶Neltuma juliflora（同名：朱莉叶Prosopis juliflora）是佛得角的主要木本物种，通过广泛的重新造林努力来对抗土地退化。尽管它具有生态和社会经济意义，但人们对该地区的生长动态和气候敏感性知之甚少。本文研究了圣地亚哥岛上朱莉叶属植物的生长年轮形成及其气候-生长关系。我们在11个街区取样了165棵树，分为四个生物气候带。使用标准的树木年轮技术测量树木年轮宽度。应用广义线性模型（GLMs）评估气候变量的影响，并使用方差膨胀因子（VIF）控制多重共线性。虽然存在假环，但观察到明显的生长边界。各生物气候带的平均径向生长在1.53 ~ 2.11 mm/年之间。最佳glm表明，通常雨季以外的高降水量可能对生长产生负面影响，而年平均温度可能有轻微的积极影响。四个生物气候区的树木年轮生长率存在显著差异，这可能反映了气候和海拔以及土壤和树木密度等其他因素的影响。这些结果突出了朱丽草的生态可塑性，并支持其在半干旱热带地区树木气候研究中的潜在应用。这些研究结果对佛得角基于生态系统的适应战略和可持续土地管理做法具有重大影响，特别是在气候变化和减轻土地退化的背景下。这项研究强调了在未来的工作中需要更长的年表和扩大整个群岛的地理采样。

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