Climatic thresholds shape northern high‐latitude fire regimes and imply vulnerability to future climate change

Boreal forests and arctic tundra cover 33% of global land area and store an estimated 50% of total soil carbon. Because wildfire is a key driver of terrestrial carbon cycling, increasing fire activity in these ecosystems would likely have global implications. To anticipate potential spatiotemporal variability in fire‐regime shifts, we modeled the spatially explicit 30‐yr probability of fire occurrence as a function of climate and landscape features (i.e. vegetation and topography) across Alaska. Boosted regression tree (BRT) models captured the spatial distribution of fire across boreal forest and tundra ecoregions (AUC from 0.63–0.78 and Pearson correlations between predicted and observed data from 0.54–0.71), highlighting summer temperature and annual moisture availability as the most influential controls of historical fire regimes. Modeled fire–climate relationships revealed distinct thresholds to fire occurrence, with a nonlinear increase in the probability of fire above an average July temperature of 13.4°C and below an annual moisture availability (i.e. P‐PET) of approximately 150 mm. To anticipate potential fire‐regime responses to 21st‐century climate change, we informed our BRTs with Coupled Model Intercomparison Project Phase 5 climate projections under the RCP 6.0 scenario. Based on these projected climatic changes alone (i.e. not accounting for potential changes in vegetation), our results suggest an increasing probability of wildfire in Alaskan boreal forest and tundra ecosystems, but of varying magnitude across space and throughout the 21st century. Regions with historically low flammability, including tundra and the forest–tundra boundary, are particularly vulnerable to climatically induced changes in fire activity, with up to a fourfold increase in the 30‐yr probability of fire occurrence by 2100. Our results underscore the climatic potential for novel fire regimes to develop in these ecosystems, relative to the past 6000–35 000 yr, and spatial variability in the vulnerability of wildfire regimes and associated ecological processes to 21st‐century climate change.     

北京山区3种暖温带森林生态系统未来碳平衡的模拟与分析

使用LPJ-GUESS植被动态模型, 在北京山区研究了未来100a以辽东栎 (Quercus liaotungensis) 为优势种的落叶阔叶林、以白桦 (Betula platyphylla) 为主的阔叶林和油松 (Pinus tabulaeformis) 为优势种的针阔混交林的碳变化, 定量分析了生态系统净初级生产力 (NPP) 、土壤异养呼吸 (Rh) 、净生态系统碳交换 (NEE) 和碳生物量 (Carbon bio-mass) 对两种未来气候情景 (SRES A2和B2) 以及相应大气CO2浓度变化情景的响应特征。结果表明:1) 未来100a两种气候情景下3种森林生态系统的NPP和Rh均增加, 并且A2情景下增加的程度更大;2) 由于3种生态系统树种组成的不同, 未来气候情景下各自NPP和Rh增加的比例不同, 导致三者NEE的变化也相异:100a后辽东栎林由碳汇转变为弱碳源, 白桦林仍保持为碳汇但功能减弱, 油松林成为一个更大的碳汇;3) 3种森林生态系统的碳生物量在未来气候情景下均增大, 21世纪末与20世纪末相比:辽东栎林在A2情景下碳生物量增加的比例为27.6%, 大于B2情景下的19.3%;白桦林和油松林在B2情景下碳生物量增加的比例分别为34.2%和52.2%, 大于A2情景下的30.8%和28.4%。     

Quantifying the Hydroregime of a Temporary Pool Habitat: A Modelling Approach for Ephemeral Rock Pools in SE Botswana

Ecological and evolutionary processes in temporary rock pools operate within constraints imposed by their hydrologic regimes. These shallow pools flood when seasonal rains accumulate on impermeable substrates. Despite the ecological importance of hydrologic conditions for these ecosystems, we typically lack tools and empirical data required to understand the implications of hydrologic variability and climate change for biotic populations and communities in these habitats. In this study, we developed a hydrologic model to simulate rock pool hydrologic regimes based on rainfall, evapotranspiration, and basin geometry. The model was used to investigate long-term patterns of seasonal and inter-annual variation in hydroregime. In addition, hydrologic conditions associated with potential climate change scenarios were simulated and evaluated with respect to the biological requirements of the anostracan Branchipodopsis wolfi. The model’s output for daily inundation matched with field observations with an overall accuracy of 85% and correctly estimated complete hydroperiods with an overall accuracy of 70%. Simulations indicate large variation in individual hydroperiods (76–115%) as well as in the number of hydroperiods per year (19–23%). Furthermore, this study suggests that climate change may significantly alter the rock pool hydroregime. These findings confirm the hydrologic sensitivity of these ephemeral habitats to precipitation patterns, and their potential sensitivity to future climate change. Modelling indicates that the suitability of average inundation conditions for B. wolfi deteriorates significantly under future climate predictions. High levels of spatial and temporal variation in hydrologic conditions are dominant features of these habitats and an essential consideration for understanding population and community-level ecological processes.     

A net ecosystem carbon budget for snow dominated forested headwater catchments: linking water and carbon fluxes to critical zone carbon storage

Climate-driven changes in carbon (C) cycling of forested ecosystems have the potential to alter long-term C sequestration and the global C balance. Prior studies have shown that C uptake and partitioning in response to hydrologic variation are system specific, suggesting that a comprehensive assessment is required for distinct ecosystems. Many sub-humid montane forest ecosystems in the US are projected to experience increased water limitation over the next decades and existing water-limited forests can be used as a model for how changes in the hydrologic cycle will impact such ecosystems more broadly. Toward that goal we monitored precipitation, net ecosystem exchange and lateral soil and stream C fluxes in three semi-arid to sub-humid montane forest catchments for several years (WY 2009–2013) to investigate how the amount and timing of water delivery affect C stores and fluxes. The key control on aqueous and gaseous C fluxes was the distribution of water between winter and summer precipitation, affecting ecosystem C uptake versus heterotrophic respiration. We furthermore assessed C stores in soil and above- and below-ground biomass to assess how spatial patterns in water availability influence C stores. Topographically-driven patterns in catchment wetness correlated with modeled soil C stores, reflecting both long-term trends in local C uptake as well as lateral redistribution of C leached from upslope organic soil horizons to convergent landscape positions. The results suggest that changes in the seasonality of precipitation from winter snow to summer rain will influence both the amount and the spatial distribution of soil C stores.     

Predicted Effects of Gypsy Moth Defoliation and Climate Change on Forest Carbon Dynamics in the New Jersey Pine Barrens

Disturbance regimes within temperate forests can significantly impact carbon cycling. Additionally, projected climate change in combination with multiple, interacting disturbance effects may disrupt the capacity of forests to act as carbon sinks at large spatial and temporal scales. We used a spatially explicit forest succession and disturbance model, LANDIS-II, to model the effects of climate change, gypsy moth (Lymantria dispar L.) defoliation, and wildfire on the C dynamics of the forests of the New Jersey Pine Barrens over the next century. Climate scenarios were simulated using current climate conditions (baseline), as well as a high emissions scenario (HadCM3 A2 emissions scenario). Our results suggest that long-term changes in C cycling will be driven more by climate change than by fire or gypsy moths over the next century. We also found that simulated disturbances will affect species composition more than tree growth or C sequestration rates at the landscape level. Projected changes in tree species biomass indicate a potential increase in oaks with climate change and gypsy moth defoliation over the course of the 100-year simulation, exacerbating current successional trends towards increased oak abundance. Our research suggests that defoliation under climate change may play a critical role in increasing the variability of tree growth rates and in determining landscape species composition over the next 100 years.     

Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity

Tropical forests harbor a significant portion of global biodiversity and are a critical component of the climate system. Reducing deforestation and forest degradation contributes to global climate‐change mitigation efforts, yet emissions and removals from forest dynamics are still poorly quantified. We reviewed the main challenges to estimate changes in carbon stocks and biodiversity due to degradation and recovery of tropical forests, focusing on three main areas: (1) the combination of field surveys and remote sensing; (2) evaluation of biodiversity and carbon values under a unified strategy; and (3) research efforts needed to understand and quantify forest degradation and recovery. The improvement of models and estimates of changes of forest carbon can foster process‐oriented monitoring of forest dynamics, including different variables and using spatially explicit algorithms that account for regional and local differences, such as variation in climate, soil, nutrient content, topography, biodiversity, disturbance history, recovery pathways, and socioeconomic factors. Generating the data for these models requires affordable large‐scale remote‐sensing tools associated with a robust network of field plots that can generate spatially explicit information on a range of variables through time. By combining ecosystem models, multiscale remote sensing, and networks of field plots, we will be able to evaluate forest degradation and recovery and their interactions with biodiversity and carbon cycling. Improving monitoring strategies will allow a better understanding of the role of forest dynamics in climate‐change mitigation, adaptation, and carbon cycle feedbacks, thereby reducing uncertainties in models of the key processes in the carbon cycle, including their impacts on biodiversity, which are fundamental to support forest governance policies, such as Reducing Emissions from Deforestation and Forest Degradation.     

三江源地区主要草地类型土壤碳氮沿海拔变化特征及其影响因素

以三江源地区主要草地类型为研究对象,分析了不同草地类型土壤有机碳和全氮的变化特征及其与环境因子、土壤特征等的相互关系。结果表明:沿着海拔的逐渐升高,土壤有机碳和全氮含量均呈现出 “V"字形变化规律,即土壤有机碳氮含量在海拔最高处(5 120 m)和最低处(4 176 m)比较高,而在中间海拔梯度较低,土壤有机碳与全氮含量极显著相关( r=0.905)且高寒草甸土壤碳、氮含量高于高山草原土壤碳、氮含量;土壤中有机碳含量和全氮含量均随着土壤含水量的增加而增加,偏相关分析结果表明:对0~30 cm土层中土壤有机碳和土壤全氮影响最大的是土壤含水量,偏相关系数为0.946 5、0.905 9(p<0.01);土壤有机碳含量和全氮含量与植被盖度和草地生产力存在正相关趋势;土壤有机碳含量和全氮含量与土壤pH值和全盐量存在负相关趋势。     

Hotspots of species loss do not vary across future climate scenarios in a drought‐prone river basin

Climate change is expected to alter the distributions of species around the world, but estimates of species’ outcomes vary widely among competing climate scenarios. Where should conservation resources be directed to maximize expected conservation benefits given future climate uncertainty? Here, we explore this question by quantifying variation in fish species’ distributions across future climate scenarios in the Red River basin south‐central United States. We modeled historical and future stream fish distributions using a suite of environmental covariates derived from high‐resolution hydrologic and climatic modeling of the basin. We quantified variation in outcomes for individual species across climate scenarios and across space, and identified hotspots of species loss by summing changes in probability of occurrence across species. Under all climate scenarios, we find that the distribution of most fish species in the Red River Basin will contract by 2050. However, the variability across climate scenarios was more than 10 times higher for some species than for others. Despite this uncertainty in outcomes for individual species, hotspots of species loss tended to occur in the same portions of the basin across all climate scenarios. We also find that the most common species are projected to experience the greatest range contractions, underscoring the need for directing conservation resources toward both common and rare species. Our results suggest that while it may be difficult to predict which species will be most impacted by climate change, it may nevertheless be possible to identify spatial priorities for climate mitigation actions that are robust to future climate uncertainty. These findings are likely to be generalizable to other ecosystems around the world where future climate conditions follow prevailing historical patterns of key environmental covariates.     

Decadally cycling soil carbon is more sensitive to warming than faster‐cycling soil carbon

The response of soil organic carbon (SOC) pools to globally rising surface temperature crucially determines the feedback between climate change and the global carbon cycle. However, there is a lack of studies investigating the temperature sensitivity of decomposition for decadally cycling SOC which is the main component of total soil carbon stock and the most relevant to global change. We tackled this issue using two decadally ¹³C‐labeled soils and a much improved measuring system in a long‐term incubation experiment. Results indicated that the temperature sensitivity of decomposition for decadally cycling SOC (>23 years in one soil and >55 years in the other soil) was significantly greater than that for faster‐cycling SOC (<23 or 55 years) or for the entire SOC stock. Moreover, decadally cycling SOC contributed substantially (35–59%) to the total CO₂ loss during the 360‐day incubation. Overall, these results indicate that the decomposition of decadally cycling SOC is highly sensitive to temperature change, which will likely make this large SOC stock vulnerable to loss by global warming in the 21st century and beyond.     

Spatial Heterogeneity of Denitrification in Semi-Arid Floodplains

Riparian ecosystems are recognized as sinks for inorganic nitrogen (N). Denitrification, a heterotrophic microbial process, often accounts for a significant fraction of the N removed. Characteristics of both riparian soils and hydrologic vectors may constrain the locations where denitrification can occur within riparian ecosystems by influencing the distribution of substrates, water, and suitable redox conditions. We employed spatially explicit methods to quantify heterogeneity of soil characteristics and potential rate of denitrification in semi-arid riparian ecosystems. These results allow us to evaluate the relative contributions of hydrologic vectors (water courses that convey materials) and soil resources (materials required by biota) to spatial heterogeneity of denitrification. During dry and monsoon seasons we contrasted a mesic site, characterized by shallow groundwater and annual inundation by floods, with a xeric site that is inundated less often and has a deeper water table. Potential denitrification was detected throughout the mesic floodplain and the average rate of denitrification was greater at the mesic site than at the xeric site, indicating the influence of water availability on denitrification. At the xeric reach, sharp declines in pools of soil resources and rate of denitrification occurred away from the stream, demonstrating the importance of the stream in determining spatial patterns. Using geographically weighted regression analysis, we determined that soil organic matter and soil nitrate were significant predictors of denitrification at the xeric site, but that factors influencing denitrification varied spatially. Spatial heterogeneity of carbon (C) and N substrates in soils likely influenced spatial patterns of denitrification, but distribution of C and N substrates was ultimately organized by hydrologic vectors. Droughts will increase the abundance of reaches with hydrogeomorphic templates similar to the xeric reach studied here. Consequences of such a transition may include a reduced rate of denitrification and patchy distribution of denitrification in floodplain soils, which will decrease the contribution of riparian ecosystems to N removal. TKH designed and completed the study and wrote the paper; EAW contributed methods and edited the paper; NBG designed the study and edited the paper.     

Inclusion of ecologically based trait variation in plant functional types reduces the projected land carbon sink in an earth system model

Earth system models demonstrate large uncertainty in projected changes in terrestrial carbon budgets. The lack of inclusion of adaptive responses of vegetation communities to the environment has been suggested to hamper the ability of modeled vegetation to adequately respond to environmental change. In this study, variation in functional responses of vegetation has been added to an earth system model (ESM) based on ecological principles. The restriction of viable mean trait values of vegetation communities by the environment, called ‘habitat filtering’, is an important ecological assembly rule and allows for determination of global scale trait–environment relationships. These relationships were applied to model trait variation for different plant functional types (PFTs). For three leaf traits (specific leaf area, maximum carboxylation rate at 25 °C, and maximum electron transport rate at 25 °C), relationships with multiple environmental drivers, such as precipitation, temperature, radiation, and CO₂, were determined for the PFTs within the Max Planck Institute ESM. With these relationships, spatiotemporal variation in these formerly fixed traits in PFTs was modeled in global change projections (IPCC RCP8.5 scenario). Inclusion of this environment‐driven trait variation resulted in a strong reduction of the global carbon sink by at least 33% (2.1 Pg C yr^?1) from the 2nd quarter of the 21st century onward compared to the default model with fixed traits. In addition, the mid‐ and high latitudes became a stronger carbon sink and the tropics a stronger carbon source, caused by trait‐induced differences in productivity and relative respirational costs. These results point toward a reduction of the global carbon sink when including a more realistic representation of functional vegetation responses, implying more carbon will stay airborne, which could fuel further climate change.     

Shifts in bacterial community composition associated with increased carbon cycling in a mosaic of phytoplankton blooms

Marine microbes have a pivotal role in the marine biogeochemical cycle of carbon, because they regulate the turnover of dissolved organic matter (DOM), one of the largest carbon reservoirs on Earth. Microbial communities and DOM are both highly diverse components of the ocean system, yet the role of microbial diversity for carbon processing remains thus far poorly understood. We report here results from an exploration of a mosaic of phytoplankton blooms induced by large-scale natural iron fertilization in the Southern Ocean. We show that in this unique ecosystem where concentrations of DOM are lowest in the global ocean, a patchwork of blooms is associated with diverse and distinct bacterial communities. By using on-board continuous cultures, we identify preferences in the degradation of DOM of different reactivity for taxa associated with contrasting blooms. We used the spatial and temporal variability provided by this natural laboratory to demonstrate that the magnitude of bacterial production is linked to the extent of compositional changes. Our results suggest that partitioning of the DOM resource could be a mechanism that structures bacterial communities with a positive feedback on carbon cycling. Our study, focused on bacterial carbon processing, highlights the potential role of diversity as a driving force for the cycling of biogeochemical elements.     

气候变暖对陆地生态系统碳循环的影响

作为全球变化的主要表现之一,气候变暖对全球陆地生态系统碳循环的影响巨大,揭示这一作用对于精确理解碳循环的过程和相关政策的制定具有重要的指导意义。该文综述了此领域近十几年来的主要研究工作,总结了陆地生态系统碳循环对气候变暖响应的主要内部机制及其过程,简述了相关模型的发展及其主要应用,并指出以往研究中存在的主要问题以及未来研究的主要方向。在气候变暖条件下,陆地生态系统碳循环的变化主要体现在以下几个方面:1)低纬度地区生态系统NPP一般表现为降低,而在中高纬度地区通常表现为增加,而在全球尺度上表现为NPP增加;2)土壤呼吸作用增强,但经过一段时间后表现出一定的适应性;3)高纬度地区的生态系统植被碳库表现为增加趋势,低纬度地区生态系统植被碳库变化不大,或略微降低,在全球尺度上表现为植被碳库增加;4)地表凋落物的产量和分解速率增加;5)土壤有机碳分解加速,进而减少土壤碳储存,同时植被碳库向土壤碳库的流动增加从而增加土壤碳库,这两种作用在不同生态系统的比重不同,在全球尺度上表现为土壤碳库的减少;6)尽管不同生态系统表现各异,总体上全球陆地生态系统表现为一个弱碳源。生物物理模型、生物地理模型和生物地球化学模型陆续被开发出来用于研究工作,并取得了一定的成果,但是研究结果仍然存在很大的不确定性。在未来的数年甚至是数十年间,气候变暖与全球变化的其它表现间的协同影响将是下一步的研究重点,气候变暖和陆地生态系统间的双向反馈作用机制是进行更准确研究的理论基础,生态系统结构和功能对气候变化的适应性是准确理解和预测未来气候情景下陆地生态系统碳循环的前提。     

Hydrologic variability in dryland regions: impacts on ecosystem dynamics and food security

Research on ecosystem and societal response to global environmental change typically considers the effects of shifts in mean climate conditions. There is, however, some evidence of ongoing changes also in the variance of hydrologic and climate fluctuations. A relatively high interannual variability is a distinctive feature of the hydrologic regime of dryland regions, particularly at the desert margins. Hydrologic variability has an important impact on ecosystem dynamics, food security and societal reliance on ecosystem services in water-limited environments. Here, we investigate some of the current patterns of hydrologic variability in drylands around the world and review the major effects of hydrologic fluctuations on ecosystem resilience, maintenance of biodiversity and food security. We show that random hydrologic fluctuations may enhance the resilience of dryland ecosystems by obliterating bistable deterministic behaviours and threshold-like responses to external drivers. Moreover, by increasing biodiversity and the associated ecosystem redundancy, hydrologic variability can indirectly enhance post-disturbance recovery, i.e. ecosystem resilience.     

草原群落退化演替过程中微斑块土壤碳氮的空间异质动态

微斑块变化是草原退化过程中的活跃成分。分析了呼伦贝尔克氏针茅草原逆行演替过程中微斑块土壤全碳、全氮和碱解氮含量的空间异质性,提出了"养分聚集效应"的概念。研究结果表明:随着群落退化演替的加剧,土壤全碳、全氮和碱解氮的含量均表现为演替前期演替后期演替中期(P0.05)。从土壤全碳、全氮和碱解氮的变异系数和变异函数综合分析来看,10 cm×10 cm微尺度上,草原退化演替过程中土壤全碳、全氮和碱解氮的空间异质性具有明显的不一致性;全碳的空间异质性表现为演替中期演替前期演替后期,全氮表现为演替后期演替前期演替中期,碱解氮表现为演替中期演替后期演替前期。草原退化过程中土壤养分在微斑块上的富积和迁移表现出尺度依赖性和变异性。     

Estimating the uncertainty in annual net ecosystem carbon exchange: spatial variation in turbulent fluxes and sampling errors in eddy-covariance measurements

Above forest canopies, eddy covariance (EC) measurements of mass (CO₂, H₂O vapor) and energy exchange, assumed to represent ecosystem fluxes, are commonly made at one point in the roughness sublayer (RSL). A spatial variability experiment, in which EC measurements were made from six towers within the RSL in a uniform pine plantation, quantified large and dynamic spatial variation in fluxes. The spatial coefficient of variation (CV) of the scalar fluxes decreased with increasing integration time, stabilizing at a minimum that was independent of further lengthening the averaging period (hereafter a ‘stable minimum’). For all three fluxes, the stable minimum (CV=9–11%) was reached at averaging times (τ_p) of 6–7 h during daytime, but higher stable minima (CV=46–158%) were reached at longer τ_p (>12 h) during nighttime. To the extent that decreasing CV of EC fluxes reflects reduction in micrometeorological sampling errors, half of the observed variability at τ_p=30 min is attributed to sampling errors. The remaining half (indicated by the stable minimum CV) is attributed to underlying variability in ecosystem structural properties, as determined by leaf area index, and perhaps associated ecosystem activity attributes. We further assessed the spatial variability estimates in the context of uncertainty in annual net ecosystem exchange (NEE). First, we adjusted annual NEE values obtained at our long‐term observation tower to account for the difference between this tower and the mean of all towers from this experiment; this increased NEE by up to 55 g C m^?2 yr^?1. Second, we combined uncertainty from gap filling and instrument error with uncertainty because of spatial variability, producing an estimate of variability in annual NEE ranging from 79 to 127 g C m^?2 yr^?1. This analysis demonstrated that even in such a uniform pine plantation, in some years spatial variability can contribute ～50% of the uncertainty in annual NEE estimates.     

What can and can't we say about indirect land‐use change in Brazil using an integrated economic – land‐use change model?

It is commonly recognized that large uncertainties exist in modelled biofuel‐induced indirect land‐use change, but until now, spatially explicit quantification of such uncertainties by means of error propagation modelling has never been performed. In this study, we demonstrate a general methodology to stochastically calculate direct and indirect land‐use change (dLUC and iLUC) caused by an increasing demand for biofuels, with an integrated economic – land‐use change model. We use the global Computable General Equilibrium model MAGNET, connected to the spatially explicit land‐use change model PLUC. We quantify important uncertainties in the modelling chain. Next, dLUC and iLUC projections for Brazil up to 2030 at different spatial scales and the uncertainty herein are assessed. Our results show that cell‐based (5 × 5 km²) probabilities of dLUC range from 0 to 0.77, and of iLUC from 0 to 0.43, indicating that it is difficult to project exactly where dLUC and iLUC will occur, with more difficulties for iLUC than for dLUC. At country level, dLUC area can be projected with high certainty, having a coefficient of variation (cv) of only 0.02, while iLUC area is still uncertain, having a cv of 0.72. The latter means that, considering the 95% confidence interval, the iLUC area in Brazil might be 2.4 times as high or as low as the projected mean. Because this confidence interval is so wide that it is likely to straddle any legislation threshold, our opinion is that threshold evaluation for iLUC indicators should not be implemented in legislation. For future studies, we emphasize the need for provision of quantitative uncertainty estimates together with the calculated LUC indicators, to allow users to evaluate the reliability of these indicators and the effects of their uncertainty on the impacts of land‐use change, such as greenhouse gas emissions.     

A historical meta‐analysis of global terrestrial net primary productivity: are estimates converging?

Net primary productivity (NPP) is one of the most important ecosystem parameters, representing vegetation activity, biogeochemical cycling, and ecosystem services. To assess how well the scientific community understands the biospheric function, a historical meta‐analysis was conducted. By surveying the literature from 1862 to 2011, I extracted 251 estimates of total terrestrial NPP at the present time (NPP_T) and calculated their statistical metrics. For all the data, the mean±standard deviation and median were 56.2±14.3 and 56.4 Pg C yr^–1, respectively. Even for estimates published after 2000, a substantial level of uncertainty (coefficient of variation by ±15%) was inevitable. The estimates were categorized on the basis of methodology (i.e., inventory analysis, empirical model, biogeochemical model, dynamic global vegetation model, and remote sensing) to examine the consistency among the statistical metrics of each category. Chronological analysis revealed that the present NPP_T estimates were directed by extensive field surveys in the 1960s and 1970s (e.g., the International Biological Programme). A wide range of uncertainty remains in modern estimates based on advanced biogeochemical and dynamic vegetation models and remote‐sensing techniques. Several critical factors accounting for the estimation uncertainty are discussed. Ancillary analyses were performed to derive additional ecological and human‐related parameters related to NPP. For example, interannual variability, carbon‐use efficiency (a ratio of NPP to gross photosynthesis), human appropriation, and preindustrial NPP_T were assessed. Finally, I discuss the importance of improving NPP_T estimates in the context of current global change studies and integrated carbon cycle research.     

Assessing the Role of Parameter and Input Uncertainty in Ecohydrologic Modeling: Implications for a Semi-arid and Urbanizing Coastal California Catchment

Ecohydrologic models are a key tool in understanding plant–water interactions and their vulnerability to environmental change. Although implications of uncertainty in these models are often assessed within a strictly hydrologic context (for example, runoff modeling), the implications of uncertainty for estimation of vegetation water use are less frequently considered. We assess the influence of commonly used model parameters and inputs on predictions of catchment-scale evapotranspiration (ET) and runoff. By clarifying the implications of uncertainty, we identify strategies for insuring that the quality of data used to drive models is considered in interpretation of model predictions. Our assessment also provides insight into unique features of semi-arid, urbanizing watersheds that shape ET patterns. We consider four sources of uncertainty: soil parameters, irrigation inputs, and spatial extrapolation of both point precipitation and air temperature for an urbanizing, semi-arid coastal catchment in Santa Barbara, CA. Our results highlight a seasonal transition from soil parameters to irrigation inputs as key controls on ET. Both ET and runoff show substantial sensitivity to uncertainty in soil parameters, even after parameters have been calibrated against observed streamflow. Sensitivity to uncertainty in precipitation manifested primarily in winter runoff predictions, whereas sensitivity to irrigation manifested exclusively in modeled summer ET. Neither ET nor runoff was highly sensitive to uncertainty in spatial interpolation of temperature. Results argue that efforts to improve ecohydrologic modeling of vegetation water use and associated water-limited ecological processes in these semi-arid regions should focus on improving estimates of anthropogenic outdoor water use and explicit accounting of soil parameter uncertainty.