Modeling patterns of nonlinearity in ecosystem responses to temperature, CO2, and precipitation changes.

It is commonly acknowledged that ecosystem responses to global climate change are nonlinear. However, patterns of the nonlinearity have not been well characterized on ecosystem carbon and water processes. We used a terrestrial ecosystem (TECO) model to examine nonlinear patterns of ecosystem responses to changes in temperature, CO2, and precipitation individually or in combination. The TECO model was calibrated against experimental data obtained from a grassland ecosystem in the central United States and ran for 100 years with gradual change at 252 different scenarios. We primarily used the 100th-year results to explore nonlinearity of ecosystem responses. Variables examined in this study are net primary production (NPP), heterotrophic respiration (R(h)), net ecosystem carbon exchange (NEE), runoff, and evapotranspiration (ET). Our modeling results show that nonlinear patterns were parabolic, asymptotic, and threshold-like in response to temperature, CO2, and precipitation anomalies, respectively, for NPP, NEE, and R(h). Runoff and ET exhibited threshold-like pattern in response to both temperature and precipitation anomalies but were less sensitive to CO2 changes. Ecosystem responses to combined temperature, CO2, and precipitation anomalies differed considerably from the responses to individual factors in terms of response patterns and/or critical points of nonlinearity. Our results suggest that nonlinear patterns in response to multiple global-change factors were diverse and were considerably affected by combined climate anomalies on ecosystem carbon and water processes. The diverse response patterns in nonlinearity have profound implications for both experimental design and theoretical development.     

Light-stress avoidance mechanisms in a Sphagnum-dominated wet coastal Arctic tundra ecosystem in Alaska

The Arctic experiences a high-radiation environment in the summer with 24-hour daylight for more than two months. Damage to plants and ecosystem metabolism can be muted by overcast conditions common in much of the Arctic. However, with climate change, extreme dry years and clearer skies could lead to the risk of increased photoxidation and photoinhibition in Arctic primary producers. Mosses, which often exceed the NPP of vascular plants in Arctic areas, are often understudied. As a result, the effect of specific environmental factors, including light, on these growth forms is poorly understood. Here, we investigated net ecosystem exchange (NEE) at the ecosystem scale, net Sphagnum CO2 exchange (NSE), and photoinhibition to better understand the impact of light on carbon exchange from a moss-dominated coastal tundra ecosystem during the summer season 2006. Sphagnum photosynthesis showed photoinhibition early in the season coupled with low ecosystem NEE. However, later in the season, Sphagnum maintained a significant CO2 uptake, probably for the development of subsurface moss layers protected from strong radiation. We suggest that the compact canopy structure of Sphagnum reduces light penetration to the subsurface layers of the moss mat and thereby protects the active photosynthetic tissues from damage. This stress avoidance mechanism allowed Sphagnum to constitute a significant percentage (up to 60%) of the ecosystem net daytime CO2 uptake at the end of the growing season despite the high levels of radiation experienced.     

Multiple sources of predictive uncertainty in modeled estimates of net ecosystem CO2 exchange

Net ecosystem CO₂ exchange (NEE) is typically measured directly by eddy covariance towers or is estimated by ecosystem process models, yet comparisons between the data obtained by these two methods can show poor correspondence. There are three potential explanations for this discrepancy. First, estimates of NEE as measured by the eddy-covariance technique are laden with uncertainty and can potentially provide a poor baseline for models to be tested against. Second, there could be fundamental problems in model structure that prevent an accurate simulation of NEE. Third, ecosystem process models are dependent on ecophysiological parameter sets derived from field measurements in which a single parameter for a given species can vary considerably. The latter problem suggests that with such broad variation among multiple inputs, any ecosystem modeling scheme must account for the possibility that many combinations of apparently feasible parameter values might not allow the model to emulate the observed NEE dynamics of a terrestrial ecosystem, as well as the possibility that there may be many parameter sets within a particular model structure that can successfully reproduce the observed data. We examined the extent to which these three issues influence estimates of NEE in a widely used ecosystem process model, Biome-BGC, by adapting the generalized likelihood uncertainty estimation (GLUE) methodology. This procedure involved 400,000 model runs, each with randomly generated parameter values from a uniform distribution based on published parameter ranges, resulting in estimates of NEE that were compared to daily NEE data from young and mature Ponderosa pine stands at Metolius, Oregon. Of the 400,000 simulations run with different parameter sets for each age class (800,000 total), over 99% of the simulations underestimated the magnitude of net ecosystem CO₂ exchange, with only 4.07% and 0.045% of all simulations providing satisfactory simulations of the field data for the young and mature stands, even when uncertainties in eddy-covariance measurements are accounted for. Results indicate fundamental shortcomings in the ability of this model to produce realistic carbon flux data over the course of forest development, and we suspect that much of the mismatch derives from an inability to realistically model ecosystem respiration. However, difficulties in estimating historic climate data are also a cause for model-data mismatch, particularly in a highly ecotonal region such as central Oregon. This latter difficulty may be less prevalent in other ecosystems, but it nonetheless highlights a challenge in trying to develop a dynamic representation of the terrestrial biosphere.     

基于DNDC模型评估水位变化对滨海湿地净生态系统CO2交换的影响

水位是影响滨海湿地生态系统蓝碳功能的重要因素。气候变化引起的海平面上升以及极端气候事件的频发,可能加快水位的变化,从而改变生态系统碳交换的过程。然而,滨海湿地碳汇功能响应水位变化的机制尚不清楚。为了评估水位对滨海湿地净生态系统CO₂交换(NEE)特征的影响,以及验证DNDC(denitrification-decomposition)模型对模拟预测滨海湿地生态系统碳交换的适用性,该研究设计了野外水位控制试验(自然水位,地下20 cm水位、地表10 cm水位),并利用DNDC模型模拟和预测水位变化对滨海湿地NEE的影响。结果表明:(1)不同水位处理之间NEE差异显著,地表10 cm水位处理促进CO₂吸收,地下20 cm水位则抑制CO₂吸收;(2)经过校准和验证的DNDC模型可以准确模拟水位变化对黄河三角洲湿地NEE的影响,NEE模拟值的日动态与田间观测结果显著相关(R²>0.6);(3)通过改变气候、土壤和田间管理等输入参数对DNDC模型进行灵敏度检验,生态系统碳交换过程对日均温、降雨和水位改变的响应最为显著,其中,水位对NEE的影响主要作用于土壤呼吸(Rs)。未来气候情境下,不同水位变化下的生态系统碳交换过程随年份增长呈现不同的规律,因此未来的模拟研究应关注DNDC中水文模块和植被演替过程的完善。该研究可为预测水文变化情境下滨海湿地碳汇功能的未来发展以及政策制定提供参考。     

基于IRGA通量箱法的草坪夏季晴天CO_2净交换量日动态

利用红外气体箱式法(Infrared Gas Analyze,IRGA),于2008年8月晴天对福州市马尼拉草坪(Zoysia matrel-la)的生态系统CO2净交换(NEE)和环境因子进行观测,阐明NEE及其组分的昼夜动态变化特征和影响因子。马尼拉草坪NEE的昼夜变化呈现为单峰型曲线,昼间其变化规律较强,夜间呈波动状态。NEE(取绝对值)最大值出现在10:00,最小值出现在16:00左右。太阳辐射、腔室内空气相对湿度和气温与NEE的相关性均为极显著(p<0.01),太阳辐射、腔室内空气相对湿度和5cm土壤温度共同解释NEE速率昼夜变异的89.30%。太阳辐射和腔室内空气相对湿度是影响草坪生态系统CO2净交换量日动态的主导环境因子;其中,太阳辐射可以单独解释NEE速率昼夜变化的79.70%,腔室内空气相对湿度可以单独解释NEE速率昼夜变化的50.40%;夏季晴天草坪生态系统在日尺度上表现为净吸收,平均CO2净交换速率为-4.11μmol/(m2.s)(负值表示吸收),平均日总通量为-0.18 mol/(m2.d)。     

菌根类型对森林树木净初级生产力的影响

菌根是土壤真菌与植物根系形成的共生体,存在于绝大多数植物（90%）的根系和生境中。菌根共有7种类型,在生态系统的过程和功能方面都扮演着十分重要的角色。为了增强对菌根在森林生态系统中重要功能的理解,文章基于全球森林数据库,在全球尺度上研究了不同菌根类型对森林树木净初级生产力（NPP）的影响。结果表明,森林树木NPP随菌根类型的不同而不同,AM类型菌根森林的NPP[679.49 g.m-2.a-1（以C计）]要显著高于含ECM类型菌根的森林[479.00 g.m-2.a-1（以C计）];菌根类型的不同对森林树木地上和地下及其各组分NPP的影响和贡献也存在着显著的不同,AM类型菌根对地下NPP的贡献要高于ECM菌根,而ECM菌根对地上NPP的贡献则较大。菌根类型对地上、地下NPP组分的影响分析则表明,AM类型的菌根对树叶和细根NPP的贡献较大,而ECM类型菌根则对树木主干和枝NPP的贡献较大。可见,森林树木总体NPP及其各组分NPP都随着菌根类型的不同而存在显著的差异。     

水、氮控制对短花针茅草原气体交换的影响

随着对气候变化日趋关注,人们对生态系统气体交换及其主要影响因素进行了大量研究。短花针茅草原作为荒漠草原的典型代表,是亚洲特有的一种草原类型,是最干旱的草原类型,生态环境异常严酷,系统极度脆弱,稳定性差,在自然和人为干扰下极易退化。以短花针茅（Stipa breviflora）草原为研究对象,通过控制降雨量以及氮素添加对生态系统气体交换进行监测,研究气体交换对降雨量和氮素添加的响应过程,揭示降雨量和氮素添加对生态系统气体交换的影响作用。该文在2012年自然条件下,采用自动CO2通量系统（Li-6400, Li-COR, Lincoln, NE, USA）野外测定短花针茅（Stipa breviflora）草原生态系统气体交换数据,比较研究了增雨施肥（WN）、增雨不施肥（W）、减雨施肥（RN）、减雨不施肥（R）、单独施肥（N）、自然状况（CK）条件下2012年气体交换变化规律。结果表明：整个生长季生态系统净 CO2交换（NEE）、总的生态系统生产力（GEP）、生态系统呼吸值（ER）都呈先升高后降低的趋势,并在生长旺盛期（8月）达到最大值。NEE在N、W处理下有升高,其他处理都降低。ER在N、WN处理下都有升高,其他处理都降低。GEP在W、N、WN处理下都有升高,其他处理都降低。NEE、ER、GEP都是在N处理中达到最大值。     

Improved estimates of net primary productivity from modis satellite data at regional and local scales.

We compared estimates of net primary production (NPP) from the MODIS satellite with estimates from a forest ecosystem process model (PnET-CN) and forest inventory and analysis (FIA) data for forest types of the mid-Atlantic region of the United States. The regional means were similar for the three methods and for the dominant oak-hickory forests in the region. However, MODIS underestimated NPP for less-dominant northern hardwood forests and overestimated NPP for coniferous forests. Causes of inaccurate estimates of NPP by MODIS were (1) an aggregated classification and parameterization of diverse deciduous forests in different climatic environments into a single class that averages different radiation conversion efficiencies; and (2) lack of soil water constraints on NPP for forests or areas that occur on thin or sandy, coarse-grained soil. We developed the "available soil water index" for adjusting the MODIS NPP estimates, which significantly improved NPP estimates for coniferous forests. The MODIS NPP estimates have many advantages such as globally continuous monitoring and remarkable accuracy for large scales. However, at regional or local scales, our study indicates that it is necessary to adjust estimates to specific vegetation types and soil water conditions.     

Temperature influences carbon accumulation in moist tropical forests

Evergreen broad-leaved tropical forests can have high rates of productivity and large accumulations of carbon in plant biomass and soils. They can therefore play an important role in the global carbon cycle, influencing atmospheric CO2 concentrations if climate warms. We applied meta-analyses to published data to evaluate the apparent effects of temperature on carbon fluxes and storages in mature, moist tropical evergreen forest ecosystems. Among forests, litter production, tree growth, and belowground carbon allocation all increased significantly with site mean annual temperature (MAT); total net primary productivity (NPP) increased by an estimated 0.2-0.7 Mg C x ha(-1) x yr(-1) x degrees C(-1). Temperature had no discernible effect on the turnover rate of aboveground forest biomass, which averaged 0.014 yr(-1) among sites. Consistent with these findings, forest biomass increased with site MAT at a rate of 5-13 Mg C x ha(-1) x degrees C(-1). Despite greater productivity in warmer forests, soil organic matter accumulations decreased with site MAT, with a slope of -8 Mg C x ha(-1) x degrees C(-1), indicating that decomposition rates of soil organic matter increased with MAT faster than did rates of NPP. Turnover rates of surface litter also increased with temperature among forests. We found no detectable effect of temperature on total carbon storage among moist-tropical evergreen forests, but rather a shift in ecosystem structure, from low-biomass forests with relatively large accumulations of detritus in cooler sites, to large-biomass forests with relatively smaller detrital stocks in warmer locations. These results imply that, in a warmer climate, conservation of forest biomass will be critical to the maintenance of carbon stocks in moist tropical forests.     

CO2 fluxes near a forest edge: a numerical study

In contrast with recent advances on the dynamics of the flow at a forest edge, few studies have considered its role on scalar transport and, in particular, on CO2 transfer. The present study addresses the influence of the abrupt roughness change on forest atmosphere CO2 exchange and contrasts the concentration and flux fields against those of a uniform forested surface. We use an atmospheric boundary layer two-equation closure model that accounts for the flow dynamics and vertical divergence of CO2 sources/sinks within a plant canopy. This paper characterizes the spatial variation of CO2 fluxes as a function of both sources/sinks distribution and the vertical structure of the canopy. Results suggest that the ground source plays a major role in the formation of wave-like vertical CO2 flux behavior downwind of a forest edge, despite the fact that the contribution of foliage sources/sinks changes monotonously. Such a variation is caused by scalar advection in the trunk space and reveals itself as a decrease or increase in vertical fluxes over the forest relative to carbon dioxide exchange of the underlying forest. The effect was more pronounced in model forests where the leaf area is concentrated in the upper part of the canopy. These results can be useful both for interpretation of existing measurements of net ecosystem exchange of CO2 (NEE) from flux towers in limited fetch conditions and in planning future CO2 transport experiments.     

Inter-annual variability of ecosystem production in boreal jack pine forests (1975-2004) estimated from tree-ring data using CBM-CFS3

We describe and apply a method of using tree-ring data and an ecosystem model to reconstruct past annual rates of ecosystem production. Annual data on merchantable wood volume increment and mortality obtained by dendrochronological stand reconstruction were used as input to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to estimate net ecosystem production (NEP), net primary production (NPP), and heterotrophic respiration (Rh) annually from 1975 to 2004 at 10 boreal jack pine (Pinus banksiana Lamb.) stands in Saskatchewan and Manitoba, Canada. From 1975 (when sites aged 41-60 years) to 2004 (when they aged 70-89 years), all sites were moderate C sinks except during some warmer than average years where estimated Rh increased. Across all sites and years, estimated annual NEP averaged 57 g Cm⁻² yr⁻¹ (range −31 to 176 g Cm⁻² yr⁻¹), NPP 244 g Cm⁻² yr⁻¹ (147-376 g Cm⁻² yr⁻¹), and Rh 187 g Cm⁻² yr⁻¹ (124-270 g Cm⁻² yr⁻¹). Across all sites, NPP was related to stand age and density, which are proxies for successional changes in leaf area. Regionally, warm spring temperature increased NPP and defoliation by jack pine budworm 1 year previously reduced NPP. Our estimates of NPP, Rh, and NEP were plausible when compared to regional eddy covariance and carbon stock measurements. Inter-annual variability in ecosystem productivity contributes uncertainty to inventory-based assessments of regional forest C budgets that use yield curves predicting averaged growth over time. Our method could expand the spatial and temporal coverage of annual forest productivity estimates, providing additional data for the development of empirical models accounting for factors not presently considered by these models.     

Water and carbon fluxes above European coniferous forests modelled with artificial neural networks

Artificial neural networks are used to select a minimal set of input variables to model water vapour and carbon exchange of coniferous forest ecosystems, independently of tree species and without detailed physiological information. Neural networks are used because of their power to fit highly non-linear relations between input and output-variables. Radiation, temperature, vapour pressure deficit and time of the day showed to be the dynamic input variables that determine ecosystem water fluxes. The same variables, together with projected leaf area index are needed for modelling CO₂-fluxes. The results for the individual sites show that the neural networks found mean water and carbon flux responses to the driving variables valid for all sites. The sensitivity analysis of the derived neural networks shows that the LAI-effect of the CO₂-flux model is overfitted because of the low variability of LAI. However, the predictions of CO₂-fluxes of sites not included in the calibration set indicate that the LAI-response of the network is reliable and that results can be used as a first estimate of the net ecosystem carbon exchange of the forest sites. Independent predictions of forest ecosystem vapour fluxes were equally satisfying as empirical models specifically calibrated for the individual sites. The results indicate that both short term water and carbon fluxes of European coniferous forests can be modelled without using detailed physiological and site specific information.     

Sensitivity of mesquite shrubland CO2 exchange to precipitation in contrasting landscape settings

In semiarid ecosystems, physiography (landscape setting) may interact with woody-plant and soil microbe communities to constrain seasonal exchanges of material and energy at the ecosystem scale. In an upland and riparian shrubland, we examined the seasonally dynamic linkage between ecosystem CO2 exchange, woody-plant water status and photosynthesis, and soil respiration responses to summer rainfall. At each site, we compared tower-based measurements of net ecosystem CO2 exchange (NEE) with ecophysiological measurements among velvet mesquite (Prosopis velutina Woot.) in three size classes and soil respiration in sub-canopy and inter-canopy micro-sites. Monsoonal rainfall influenced a greater shift in the magnitude of ecosystem CO2 assimilation in the upland shrubland than in the riparian shrubland. Mesquite water status and photosynthetic gas exchange were closely linked to the onset of the North American monsoon in the upland shrubland. In contrast, the presence of shallow alluvial groundwater in the riparian shrubland caused larger size classes of mesquite to be physiologically insensitive to monsoonal rains. In both shrublands, soil respiration was greatest beneath mesquite canopies and was coupled to shallow soil moisture abundance. Physiography, through its constraint on the physiological sensitivity of deeply rooted woody plants, may interact with plant-mediated rates of soil respiration to affect the sensitivity of semiarid-ecosystem carbon exchange in response to episodic rainfall.     

An integrated ecosystem service assessment in an artificial desert oasis of northwestern China

Spatially explicit integrated assessment of ecosystem services is a new and important research field in landscape ecology. The objective of this paper was to develop an integrated process-based modeling method to simulate changes in multiple ecosystem services in 2000–2009 at pixel and regional scales in the Zhangye oasis of northwestern China. Six ecosystem service indicators were selected and quantified using process-based models, including net primary production (NPP), grain production, net oxygen production (NOP), carbon sequestration (CS), water conservation, and soil conservation. Analytical results were as follows: (1) At the oasis scale, NPP, NOP, CS, water conservation, and soil conservation decreased from 2000 to 2009, whereas grain production increased. (2) At the pixel scale, the spatial changes in NPP were similar to those in NOP and CS, but changes in grain production showed the opposite pattern. Water conservation and soil conservation showed somewhat unintuitive spatial patterns. (3) The impact of land-use forms on ecosystem services showed that grazing and township construction both had negative impacts on all services, but that nature conservation and wetland development had positive impacts on all services. This research showed that the integrated modeling can be proposed as an environmental decision-making tool in similar case studies.     

Modeling seasonal course of carbon fluxes and evapotranspiration in response to low temperature and moisture in a boreal Scots pine ecosystem

Environmental conditions act above and below ground, and regulate carbon fluxes and evapotranspiration. The productivity of boreal forest ecosystems is strongly governed by low temperature and moisture conditions, but the understanding of various feedbacks between vegetation and environmental conditions is still unclear. In order to quantify the seasonal responses of vegetation to environmental factors, the seasonality of carbon and heat fluxes and the corresponding responses for temperature and moisture in air and soil were simulated by merging a process-based model (CoupModel) with detailed measurements representing various components of a forest ecosystem in Hyytiälä, southern Finland. The uncertainties in parameters, model assumptions, and measurements were identified by generalized likelihood uncertainty estimation (GLUE). Seasonal and diurnal courses of sensible and latent heat fluxes and net ecosystem exchange (NEE) of CO₂ were successfully simulated for two contrasting years. Moreover, systematic increases in efficiency of photosynthesis, water uptake, and decomposition occurred from spring to summer, demonstrating the strong coupling between processes. Evapotranspiration and NEE flux both showed a strong response to soil temperature conditions via different direct and indirect ecosystem mechanisms. The rate of photosynthesis was strongly correlated with the corresponding water uptake response and the light use efficiency. With the present data and model assumptions, it was not possible to precisely distinguish the various regulating ecosystem mechanisms. Our approach proved robust for modeling the seasonal course of carbon fluxes and evapotranspiration by combining different independent measurements. It will be highly interesting to continue using long-term series data and to make additional tests of optional stomatal conductance models in order to improve our understanding of the boreal forest ecosystem in response to climate variability and environmental conditions.     

湿地生态系统CO2净交换、水汽通量及二者关系浅析

湿地生态系统碳循环是陆地碳循环研究中的重要组成部分,对于全球变化具有重要意义。水汽通量是影响湿地生态系统碳循环最重要、最基本的生态因子之一,与湿地生态系统CO2净交换密切相关。本文在总结湿地生态系统CO2净交换与水汽通量变化基本规律及其主要影响因子的基础上,从宏观和微观2个方面分析二者之间的内在关系。从宏观上看,湿地生态系统本身的特点决定了CO2净交换与水汽通量之间必然是相互影响、相互制约的;就微观而言,叶片尺度上的气孔行为是水分蒸腾和净碳通量这两个生理生态过程相互联系的纽带。最后,对湿地生态系统CO2净交换与水汽通量关系的研究方向提出展望。     

Carbon allocation to ectomycorrhizal fungi correlates with belowground allocation in culture studies

Ectomycorrhizal fungi form symbioses with most temperate and boreal tree species, but difficulties in measuring carbon allocation to these symbionts have prevented the assessment of their importance in forest ecosystems. Here, I surveyed allocation patterns in 14 culture studies and five field studies of ectomycorrhizal plants. In culture studies, allocation to ectomycorrhizal fungi (NPPf) was linearly related to total belowground net primary production (NPPb) by the equation NPPf = 41.5% x NPPb - 11.3% (r2 = 0.55, P < 0.001) and ranged from 1% to 21% of total net primary production. As a percentage of NPP, allocation to ectomycorrhizal fungi was highest at lowest plant growth rates and lowest nutrient availabilities. Because total belowground allocation can be estimated using carbon balance techniques, these relationships should allow ecologists to incorporate mycorrhizal fungi into existing ecosystem models. In field studies, allocation to ectomycorrhizal fungi ranged from 0% to 22% of total allocation, but wide differences in measurement techniques made intercomparisons difficult. Techniques such as fungal in-growth cores, root branching-order studies, and isotopic analyses could refine our estimates of turnover rates of fine roots, mycorrhizae, and extraradical hyphae. Together with ecosystem modeling, such techniques could soon provide good estimates of the relative importance of root vs. fungal allocation in belowground carbon budgets.     

CBM-CFS3: A model of carbon-dynamics in forestry and land-use change implementing IPCC standards

The scientific community, forest managers, environmental organizations, carbon-offset trading systems and policy-makers require tools to account for forest carbon stocks and carbon stock changes. In this paper we describe updates to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) implemented over the past years. This model of carbon-dynamics implements a Tier 3 approach of the Intergovernmental Panel on Climate Change (IPCC) Good Practice Guidance for reporting on carbon stocks and carbon stock changes resulting from Land Use, Land-use Change and Forestry (LULUCF). The CBM-CFS3 is a generic modelling framework that can be applied at the stand, landscape and national levels. The model provides a spatially referenced, hierarchical system for integrating datasets originating from different forest inventory and monitoring programs and includes a structure that allows for tracking of land areas by different land-use and land-use change classes. Ecosystem pools in CBM-CFS3 can be easily mapped to IPCC-defined pools and validated against field measurements. The model uses sophisticated algorithms for converting volume to biomass and explicitly simulates individual annual disturbance events (natural and anthropogenic). Several important scientific updates have been made to improve the representation of ecosystem structure and processes from previous versions of CBM-CFS. These include: (1) an expanded representation of dead organic matter and soil carbon, particularly standing dead trees, and a new algorithm for initializing these pools prior to simulation, (2) a change in the input data requirement for simulating growth from biomass to readily available merchantable volume curves, and new algorithms for converting volume to biomass, (3) improved prediction of belowground biomass, and (4) improved parameters for soil organic matter decay, fire, insect disturbances, and forest management. In addition, an operational-scale version of CBM-CFS3 is freely available and includes tools to import data in standard formats, including the output of several timber supply models that are commonly used in Canada. Although developed for Canadian forests, the flexible nature of the model has enabled it to be adapted for use in several other countries.     

A Bayesian strategy for combining predictions from empirical and process-based models

We present a strategy for using an empirical forest growth model to reduce uncertainty in predictions made with a physiological process-based forest ecosystem model. The uncertainty reduction is carried out via Bayesian melding, in which information from prior knowledge and a deterministic computer model is conditioned on a likelihood function. We used predictions from an empirical forest growth model G-HAT in place of field observations of aboveground net primary productivity (ANPP) in a deciduous temperate forest ecosystem. Using Bayesian melding, priors for the inputs of the process-based forest ecosystem PnET-II were propagated through the model, and likelihoods for the PnET-II output ANPP were calculated using the G-HAT predictions. Posterior distributions for ANPP and many PnET-II inputs obtained using the G-HAT predictions largely matched posteriors obtained using field data. Since empirical growth models are often more readily available than extensive field data sets, the method represents a potential gain in efficiency for reducing the uncertainty of process-based model predictions when reliable empirical models are available but high-quality data are not.     

Soil erosion and significance for carbon fluxes in a mountainous Mediterranean-climate watershed.

In topographically complex terrains, downslope movement of soil organic carbon (OC) can influence local carbon balance. The primary purpose of the present analysis is to compare the magnitude of OC displacement by erosion with ecosystem metabolism in such a complex terrain. Does erosion matter in this ecosystem carbon balance? We have used the Revised Universal Soil Loss Equation (RUSLE) erosion model to estimate lateral fluxes of OC in a watershed in northwestern Mexico. The watershed (4900 km2) has an average slope of 10 degrees +/- 9 degrees (mean +/- SD); 45% is >10 degrees, and 3% is >30 degrees. Land cover is primarily shrublands (69%) and agricultural lands (22%). Estimated bulk soil erosion averages 1350 Mg x km(-2) x yr(-1). We estimate that there is insignificant erosion on slopes < 2 degrees and that 20% of the area can be considered depositional. Estimated OC erosion rates are 10 Mg x km(-2) x yr(-1) for areas steeper than 2 degrees. Over the entire area, erosion is approximately 50% higher on shrublands than on agricultural lands, but within slope classes, erosion rates are more rapid on agricultural areas. For the whole system, estimated OC erosion is approximately 2% of net primary production (NPP), increasing in high-slope areas to approximately 3% of NPP. Deposition of eroded OC in low-slope areas is approximately 10% of low-slope NPP. Soil OC movement from erosional slopes to alluvial fans alters the mosaic of OC metabolism and storage across the landscape.