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Riparian woodlands are hotspots of productivity and biodiversity on dryland landscapes, yet riparian tree species are also extremely vulnerable to catastrophic hydraulic damage caused by hydroclimatic change. Root zone water subsidies from shallow groundwater facilitate the high levels of productivity seen in riparian woodlands. Shallow groundwater provides a persistent source of root zone soil moisture that is somewhat decoupled from the local precipitation regime. As a result, riparian tree species are able to avoid water stress and maximize productivity throughout the prolonged summer dry seasons that are common in the southwestern United States. Groundwater declines caused by extreme drought conditions threaten the health and function of dryland riparian woodlands. If groundwater elevations drop below the root zones of riparian tree species, it is likely that riparian woodlands will experience widespread stress and mortality. However, the sensitivity of riparian tree species to changes in root zone water availability remains poorly constrained. This dissertation combines remote sensing, flux tower measurements, and ecological modeling to examine vegetation cover, evapotranspiration, and photosynthesis in riparian woodlands under changing environmental conditions. It also identifies critical physiological thresholds that are needed to maintain ecosystem structure and function under anthropogenic climate change.In the first chapter, I combine remote sensing data with measurements from groundwater monitoring wells to identify critical groundwater thresholds that are needed to maintain the health and function of riparian woodlands. The analysis examines the Santa Clara River in southern California, which experienced widespread groundwater declines during an extreme drought from 2012 to 2019. Spectral mixture analysis was used to estimate the fractional cover of green vegetation and non-photosynthetic vegetation (i.e., dead and woody plant material) in six riparian woodlands. The groundwater depth was characterized for each woodland using data from groundwater monitoring wells. The analysis revealed that riparian woodlands experience substantial decreases in green vegetation cover and substantial increases in dead/woody vegetation cover when the depth to groundwater exceeds ca. 5 m. The analysis also revealed a coherent spatial and temporal trend of riparian woodland mortality that proceeded downstream over six years and mirrored trends in groundwater elevation over space and time. The findings reveal that riparian woodlands depend on shallow groundwater access to maintain health and function, and that they experience substantial stress and mortality when they lose access to root zone water subsidies from shallow groundwater aquifers.In the second chapter, I develop a novel theoretical model to predict leaf temperature as a function of evapotranspiration. The model reveals that the difference between leaf temperature and air temperature varies as a linear function of the evaporative fraction. The model also reveals that leaf temperature converges to air temperature when the evaporative fraction equals one. The model predictions were validated using flux tower measurements from a riparian woodland and an upland savanna in southeastern Arizona. The flux tower measurements reveal that evaporative cooling reduced leaf temperature by ca. 1-5 °C in the middle of the growing season. Evaporative cooling also resulted in a ca. 15% reduction in leaf respiration. The impact of evaporative cooling on leaf carbon cycling represents a novel connection between plant water and carbon cycles via leaf energy balance that has received little attention in literature.In the third chapter, I develop a novel modeling framework to predict the vertical profiles of radiation and wind speed within forest canopies based on known physical principles. The predictions are then used to estimate the vertical profiles of leaf temperature and net photosynthesis for five flux tower sites spanning a large latitudinal gradient in North and South America. The model predictions reveal that leaf temperature decreases exponentially downward through forest canopies, and that the difference between top-of-canopy leaf temperature and bottom-of-canopy leaf temperature can exceed 7 °C. Unexpectedly, in many forest biomes, the highest levels of net photosynthesis often occur in the middle of the canopy. The analysis helps uncover the mechanistic basis for this behavior. The analysis also identifies the combinations of environmental conditions that result in critical leaf temperatures that cause irreversible damage to leaf photosynthetic infrastructure. Two different data sets provide evidence of trait coordination between leaf size and stomatal conductance to avoid critical leaf temperatures across global forest biomes.

Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. In this paper, we present projections of future fire probability for the southcentral USA using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM). Future fire probability is projected to both increase and decrease across the study region of Oklahoma, New Mexico, and Texas. Among all end-of-century projections, change in fire probabilities (CFPs) range from − 51 to + 240%. Greatest absolute increases in fire probability are shown for areas within the range of approximately 75 to 160 cm mean annual precipitation (MAP), regardless of climate model. Although fire is likely to become more frequent across the southcentral USA, spatial patterns may remain similar unless significant increases in precipitation occur, whereby more extensive areas with increased fire probability are predicted. Perhaps one of the most important results is illumination of climate changes where fire probability response (+, −) may deviate (i.e., tipping points). Fire regimes of southcentral US ecosystems occur in a geographic transition zone from reactant- to reaction-limited conditions, potentially making them uniquely responsive to different scenarios of temperature and precipitation changes. Identification and description of these conditions may help anticipate fire regime changes that will affect human health, agriculture, species conservation, and nutrient and water cycling.

Transpiration from the Amazon rainforest generates an essential water source at a global and local scale. However, changes in rainforest function with climate change can disrupt this process, causing significant reductions in precipitation across Amazonia, and potentially at a global scale. We report the only study of forest transpiration following a long-term (>10 year) experimental drought treatment in Amazonian forest. After 15 years of receiving half the normal rainfall, drought-related tree mortality caused total forest transpiration to decrease by 30%. However, the surviving droughted trees maintained or increased transpiration because of reduced competition for water and increased light availability, which is consistent with increased growth rates. Consequently, the amount of water supplied as rainfall reaching the soil and directly recycled as transpiration increased to 100%. This value was 25% greater than for adjacent non-droughted forest. If these drought conditions were accompanied by a modest increase in temperature (e.g. 1.5°C), water demand would exceed supply, making the forest more prone to increased tree mortality. This article is protected by copyright. All rights reserved.

To improve predictions of the future of ecosystems in a changing world, it is necessary to consider fine-scale processes. We propose that for the Mediterranean region (a hotspot of climate change and biodiversity), there are three local processes that have often been overlooked in predictive models and that are key to understanding vegetation changes: rural abandonment that increases wildlands, population changes that boost fire ignitions, and coastal degradation that enhances drought. These processes are not directly driven by global warming and act in different directions (greening and browning). The current balance is still toward greening, because land abandonment is buffering the browning drivers; however, it is likely to switch with increasing warming. The challenge is to mitigate the browning processes. Given that climatic warming is not directly driving these processes, local management can make a difference in reducing the overall impact on the landscape and society

The Meridiani Planum region on Mars is rich in minerals derived from evaporation, but lacks a topography consistent with standing water. Do the deposits stem from upwelling groundwater early in the planet's history?

The Arctic and Subarctic regions are of particular importance to the global climate change and are now experiencing a climate warming that is higher than the global average. Around 50% of the global soil carbon is stored in high latitude soils, especially in permafrost and peatland soils. Permafrost thawing, speeding up the decomposition of previously frozen soil carbon, is expected to result in strongly positive feedbacks to global warming. Meanwhile, increased air temperature may strongly impact vegetation growth and distributions in this region. Dynamic ecosystem models are powerful tools to study climate change influences on ecosystem processes and also to quantify ecosystem feedbacks to the atmosphere. However, these models often focus on the vertical transfer of carbon and water between the atmosphere, the land surface vegetation and soils. Therefore, they generally do not consider the horizontal water and soluble carbon flows between the modelled spatial units (grid cells), which could result in an incomplete estimation of water and carbon budgets, especially for climatically sensitive high latitude regions. In this thesis, we aim to overcome this limitation by implementing spatial topographical indices into a state-of-the-art dynamic ecosystem model, LPJ-GUESS, and to incorporate water and carbon (mainly dissolved organic carbon, DOC) interactions between the grid cells. Modelling approaches and algorithms developed in this thesis were applied to study the subarctic Stordalen catchment, located in northern Sweden, and to explore the potential influence on the model’s hydrological and ecological estimations. Extensive sets of observation data were used for model evaluation throughout. We proposed a distributed hydrological (DH) approach to dynamically simulate water flow from cell to cell within the catchment and compared the hydrological and ecological impacts resulting from different flow routing algorithms. The results indicate an improved accuracy of runoff estimation when using the proposed DH scheme in the Stordalen catchment. They also show that the choice of flow algorithm can have strong impacts on water and carbon flux estimations in this region. Furthermore, a complete estimation of the catchment carbon budget was assessed using our developed model. We found that the catchment is a carbon sink at present and could become a stronger sink in the near future, a result which is, however, very dependent on future atmospheric CO2 concentrations and methane (CH4) emissions from the peatlands. Additionally, the model was further extended to dynamically model soil water DOC and the lateral transport of DOC across the landscape. The modelled outputs suggest that DOC production and mineralization largely contribute to DOC fluxes and that wet fen peatland is and will be a hotspot for DOC export. In conclusion, this thesis demonstrates the feasibility of implementing topographical indices into LPJ-GUESS to describe water flows, and the importance of considering spatial heterogeneity in hydrological conditions when modelling carbon dynamics at high latitudes. Furthermore, the integration of vertical and horizontal carbon fluxes at high spatial resolutions can be used to provide more accurate estimations of a complete carbon budget and can dynamically simulate the fate of different carbon components in response to climate change. De arktiska och subarktiska regionerna är av särskild betydelse för den globala klimatförändringen, och genomgår nu en klimatuppvärmning som är högre än genomsnittshöjningen på jorden. Omkring 50 % av världens markkol är lagrat i nordliga jordar (på höga latituder), och där främst i permafrost- och torvjordar. Upptiningen av permafrost påskyndar nedbrytningen, och därmed frigöring, av tidigare fryst markkol, vilket förväntas ha kraftiga effekter på den globala uppvärmningen. Samtidigt kan en ökad lufttemperatur påtagligt påverka tillväxt och utbredning av vegetation i dessa regioner. Dynamiska ekosystemmodeller är effektiva verktyg för att studera klimatförändringars påverkan på ekosystemprocesser, inklusive kvantifiering av återkopplingar från olika ekosystem till atmosfären. Dessa modeller fokuserar emellertid främst på det vertikala utbytet av kol och vatten mellan atmosfär, landyta, vegetation och mark. Därför tar de i allmänhet inte hänsyn till de horisontella vatten- och kolflödena som förekommer mellan de modellerade rumsliga enheterna (jmf gridceller i en rasterkarta eller pixlar i en bild). Denna förenkling kan leda till en ofullständig uppskattning av vatten- och kolbudgetar, och då i synnerhet för de klimatkänsliga regionerna på de höga latituderna. Denna avhandling syftar till att reducera ovan nämnda begränsningar genom att implementera rumsliga topografiska index i den dynamiska ekosystemmodellen LPJ-GUESS, samt att inkorporera interaktioner mellan vatten och kol (huvudsakligen löst organiskt kol, DOC) över ytan (mellan gridcellerna i kartan). De modeller som utvecklats inom denna studie har implementerats i det subarktiska Stordalens avrinningsområde, beläget i norra Sverige. Där har modellernas eventuella inverkan på hydrologiska och ekologiska simuleringar analyserats och dokumenterats. För utvärdering av modellerna har omfattande observationsdata använts. Vidare föreslås en distribuerad hydrologisk (DH) metod för att dynamiskt simulera vattentransport från cell till cell inom Stordalens avrinningsområde, och jämförande studier av de hydrologiska och ekologiska effekterna beroende på olika algoritmer för modellering av vattenflöden har genomförts. Resultaten visar att den föreslagna DH-metoden kan modellera avrinningen i Stordalens avrinningsområde bättre än tidigare föreslagna metoder. Vidare kan det konstateras att valet av flödesalgoritm har en stor inverkan på modelleringen av vatten- och kolflöden i regionen. Den utvecklade metoden användes även för att utföra en fullständig uppskattning av kolbudgeten i avrinningsområdet. I denna delstudie kom det fram att upptagningsområdet idag är en kolsänka, och att det inom en snar framtid sannolikt kommer att bli en ännu starkare sänka. Detta förlopp är emellertid starkt beroende av framtida atmosfäriska CO2-koncentrationer och metanutsläpp från torvmarkerna. Den sista delen av avhandlingen behandlar ytterligare utveckling av modellen för att dynamiskt kunna modellera DOC i markvatten, samt den laterala (horisontella) transporten av DOC i landskapet. Resultaten visar att produktion och mineralisering av DOC i stor utsträckning bidrar till DOC-flöden, samt att våta torvmarker är och kommer att vara hetfläckar (även kallade hotspots) för DOC-export. Sammanfattningsvis visar denna avhandling möjligheterna att implementera topografiska index och vattenflöden (lateralt och vertikalt) i LPJ-GUESS. Den demonstrerar också vikten av att ta hänsyn till rumslig heterogenitet i hydrologiska förhållanden vid modellering av koldynamik på höga latituder. Avhandlingsarbetet har gjort det möjligt att genom integrering av vertikala och laterala kolflöden vid höga rumsliga upplösningar noggrannare skatta en fullständig kolbudget, samt att dynamiskt simulera vilken påverkan klimatförändringarna har på olika kolkomponenter. 北极和亚北极地区对全球气候变化影响尤为重要。目前，北极地区正面临着变暖速度高于全球平均的现状。全球大约有50%的土壤碳储存在高纬度地区的土壤里，这些土壤碳主要分布于冻土层和泥炭层中。冻土层的解冻会使原先被冻结的土壤碳加速分解，产生温室气体，从而对全球变暖形成一个强烈的正反馈。与此同时，气温的增加可能会很大程度地影响植被在这些地区的生长和分布。动态生态系统模型是一种非常强大的工具，被用来研究气候变化对生态系统的影响，并且可以量化生态系统对大气的反馈信息。然而这些模型通常只关注大气、地表植被和土壤之间的水和碳的纵向转移，从而忽略了其在模型空间单元中的横向移动。这样可能会导致模型对于水和碳平衡的计算不够准确和全面，尤其在气候敏感的高纬度极地地区，这种偏差可能会更大。 本论文旨在解决动态生态系统模型中的这个局限性问题。基于目前最先进的动态生态系统模型LPJ-GUESS，我们利用和结合空间地形指数实现了模拟水和碳（主要是土壤溶解性有机碳）在空间单元中的相互作用。文中所提出来的建模方法和算法被应用到坐落于亚北极地区，瑞典北部的Stordalen流域，以探索模型新方法对估算水文和生态过程的潜在影响。在整个应用过程中，我们采用了大量的观测数据集来进行模型评估。 我们提出了一种基于网格单元对网格单元的分布式水文（DH）方法来动态模拟流域内的水流。我们进一步比较了不同的流量路径算法对于模拟水文和生态过程的影响。结果表明，当我们在Stordalen流域内使用结合了分布式水文方法的模型时，该模型对于径流估算的精度比以往有所提高。同时实验结果也表明了流量路径算法的选择会对研究区域内水通量和碳通量的估算产生重大的影响。基于以上结果，我们（在高空间分辨率下）利用该模型对流域内的碳预算有了一个更为完整的估算。我们发现，Stordalen流域现在是一个碳汇，并且在不久的将来有可能成为一个更大的碳汇。然而这一预测结果非常地依赖于空气中二氧化碳浓度的增加对流域内植被固碳能力的影响，同时还受流域内泥炭地里甲烷的排放量的影响。除此之外，该模型进一步扩展了对土壤水中的溶解性有机碳（DOC）的含量及其空间横向传输的动态模拟。模拟的输出表明，土壤中DOC的动态变化主要受DOC 的产生量和矿化作用的影响，潮湿的沼泽泥炭地在现在和将来都会是土壤DOC输出的热点区域。 总而言之，本论文展示了在LPJ-GUESS模型中加入用以描述水流的地形指数的可行性，同时证明了在高纬度地区模拟碳动态变化时对于水文条件的空间异质性的考量的重要性。此外，本论文还说明了在高空间分辨率下，综合考虑垂直和水平碳通量可以提供更准确和更完整的碳预算的估计，也可以动态地模拟不同的碳成分在应对气候变化时产生的不同结果。