Influences of canopy structure and physiological traits on flux partitioning between understory and overstory in an eastern Siberian boreal larch forest

Boreal forests play an important role in the global balance of energy and CO₂. Our previous study of elaborate eddy covariance observations in a Siberian boreal larch forest, conducted both above the forest canopy and at the forest floor, revealed a significant contribution of latent heat flux (LE) from the cowberry understory to the whole ecosystem LE. Thus, in the present study, we examined what factors control the partitioning of whole ecosystem LE and CO₂ flux into the understory and overstory vegetation, using detailed leaf-level physiology (for both understory and overstory vegetation) and soil respiration property measurements as well as a multilayer soil-vegetation-atmosphere transfer (SVAT) model. The modeling results showed that the larch overstory's leaf area index (LAI) and vertical profile of leaf photosynthetic capacity were major factors determining the flux partitioning in this boreal forest ecosystem. This is unlike other forest ecosystems that tend to have dense LAI. We concluded that control of the larch overstory's LAI had a relationship with both the coexistence of the larch with the cowberry understory and with the water resources available to the total forest ecosystem.     

Simulation of interannual responses of trembling aspen stands to climatic variation and insect defoliation in western Canada

A carbon-based model has been developed to simulate responses of trembling aspen (Populus tremuloides Michx.) stands to interannual climatic variation and insect defoliation. The model is designed for medium time scale (10–100 years) simulations and requires only daily maximum and minimum temperature and precipitation as meteorological inputs. The modelling approach is similar to FOREST-BGC but includes additional processes known to be important in deciduous forests. These include removal of leaf area during outbreaks of forest tent caterpillar (Malacosoma disstria Hbn.), phenological changes in leaf area index, storage and allocation of non-structural carbohydrate and the contribution of understorey vegetation to evapotranspiration. The model was used for simulations of growth and mortality of biomass carbon in two mature aspen forests located in the climatically dry transition zone between the boreal forest and prairie grassland regions of Saskatchewan, Canada. Model inputs of annual defoliation intensity were based on historic records of insect defoliation and the incidence of light-coloured tree rings in disks or cores collected from aspen at each of the two sites. At both sites, moderately good correlations (r²=0.47–0.54) were obtained between modelled interannual changes in stem carbon growth and observed interannual changes in stem basal area increment obtained from tree-ring analysis. Model outputs of stem biomass carbon were found to be highly sensitive to parameters describing seasonal leaf area duration, insect defoliation intensity, photosynthesis and root respiration and carbohydrate allocation to growth versus storage.     

Linking intra-seasonal variations in climate and tree-ring δC: A functional modelling approach

Stable carbon isotopic composition (δ¹³C) in tree rings is a widely recognized tool for climate reconstruction, and several works suggest that seasonal information can be extracted from intra-ring δ¹³C variations. In this study, we explored the link between climate and intra-seasonal oak ring δ¹³C using a process-based modelling approach. The ISOCASTANEA model was developed to compute the seasonal dynamics of tree-ring δ¹³C for deciduous species from half-hourly climatic data by accounting for photosynthetic discrimination and carbon translocation and allocation at the tree scale and in tree rings.The model was applied from March 2005 to December 2007 in a 150-year-old deciduous oak forest. Canopy photosynthesis and stomatal conductance were calibrated using H₂O and CO₂ fluxes measured by the eddy flux technique, and simulated δ¹³C values were compared to seasonal patterns of total organic matter δ¹³C measured in tree rings for 2006 and 2007 at the same site. With the inclusion of carbon translocation and with regard to ¹³C enrichment of starch compared to soluble sugars, the model can reasonably simulate the intra-seasonal and inter-annual variability of tree-ring δ¹³C using the same parameter values for 2006 and 2007. The amplitude of the seasonal carbon isotope pattern in tree rings was influenced by both photosynthetic and post-photosynthetic processes (starch enrichment and reserve use). The δ¹³C variations in the early part of the ring, i.e., mainly in the earlywood, were related mostly to carbohydrate metabolism, although diluted information about environmental conditions during the previous year could also be found. The last part of the ring, consisting mainly of latewood, was found to be a good recorder of current-year environmental conditions, in particular relative humidity, at a fine temporal resolution when the growth rate was high. The sensitivity of the δ¹³C in the early part of the ring to carbohydrate metabolism suggests that intra-ring δ¹³C could be used to explore the relationship between tree decline or mortality and carbohydrate deficiency.     

Impacts of changing frost regimes on Swedish forests: Incorporating cold hardiness in a regional ecosystem model

Understanding the effects of climate change on boreal forests which hold about 7% of the global terrestrial biomass carbon is a major issue. An important mechanism in boreal tree species is acclimatization to seasonal variations in temperature (cold hardiness) to withstand low temperatures during winter. Temperature drops below the hardiness level may cause frost damage. Increased climate variability under global and regional warming might lead to more severe frost damage events, with consequences for tree individuals, populations and ecosystems. We assessed the potential future impacts of changing frost regimes on Norway spruce (Picea abies L. Karst.) in Sweden. A cold hardiness and frost damage model were incorporated within a dynamic ecosystem model, LPJ-GUESS. The frost tolerance of Norway spruce was calculated based on daily mean temperature fluctuations, corresponding to time and temperature dependent chemical reactions and cellular adjustments. The severity of frost damage was calculated as a growth-reducing factor when the minimum temperature was below the frost tolerance. The hardiness model was linked to the ecosystem model by reducing needle biomass and thereby growth according to the calculated severity of frost damage. A sensitivity analysis of the hardiness model revealed that the severity of frost events was significantly altered by variations in the hardening rate and dehardening rate during current climate conditions. The modelled occurrence and intensity of frost events was related to observed crown defoliation, indicating that 6-12% of the needle loss could be attributed to frost damage. When driving the combined ecosystem-hardiness model with future climate from a regional climate model (RCM), the results suggest a decreasing number and strength of extreme frost events particularly in northern Sweden and strongly increasing productivity for Norway spruce by the end of the 21st century as a result of longer growing seasons and increasing atmospheric CO₂ concentrations. However, according to the model, frost damage might decrease the potential productivity by as much as 25% early in the century.     

Climate, canopy conductance and leaf area development controls on evapotranspiration in a boreal coniferous forest over a 10-year period: A united model assessment

The aim of this work was to test a process-based model (hydrological model combined with forest growth model) on the simulation of seasonal variability of evapotranspiration (ET) in an even-aged boreal Scots pine (Pinus sylvestris L.) stand over a 10 year period (1999-2008). The water flux components (including canopy transpiration (E_t) and evaporation from canopy (E_c) and ground surface (E_g) were estimated in order to output the long-term stand water budget considering the interaction between climate variations and stand development. For validation, half-hourly data on eddy water vapor fluxes were measured during the 10 growing seasons (May-September). The model predicted well the seasonal course of ET compared to the measured values, but slightly underestimated the water fluxes both in non-drought and drought (2000, 2003 and 2006) years. The prediction accuracy was, on average, higher in drought years. The simulated ET over the 10 years explained, on average, 58% of the daily variations and 84% of the monthly amount of ET. Water amount from E_t contributed most to the ET, with the fractions of E_t, E_c and E_g being, on average, 67, 11 and 23% over the 10-year period, respectively. Regardless of weather conditions, the daily ET was strongly dependent on air temperature (T_a) and vapor pressure deficit (D_a), but less dependent on soil moisture (W_s). On cloudy and rainy days, there was a non-linear relationship between the ET and solar radiation (R_o). During drought years, the model predicted lower daily canopy stomatal conductance (g_cs) compared with non-drought years, leading to a lower level of E_t. The modeled daily g_cs responded well to D_a and W_s. In the model simulation, the annual LAI increased by 35% between 1999 and 2008. The ratio of E_c: ET correlated strongly with LAI. Furthermore, LAI reduced the proportion of E_g as a result of the increased share of E_c and E_t and radiation interception. Although the increase of LAI affected positively E_t, the contribution of E_t in ET was not significantly correlated with LAI. To conclude, although the model predicted reasonably well the seasonal course of ET, the calculation time steps of different processes in the model should be homogenized in the future to increase the prediction accuracy.     

Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July-September (T_amax) in all process models (R² = 0.4-0.6), indicating that these correlations were robust. The negative correlation between T_amax and NEP was attributed to different processes in different models, which were tested by comparing CO₂ fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (T_a). The general agreement in sensitivity of annual NPP to T_amax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′ = NPP − 57.1 (T_amax − 18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July-September, and T_amax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to T_amax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.     

不同土地覆被下岩溶表层系统CO2体积分数研究

对重庆金佛山林地、裸地表层岩溶生态系统CO2体积分数进行了野外监测,揭示了CO2体积分数变化规律,这种变化与土壤温度有密切的关系。林地与裸地各个层次土壤的CO2体积分数与土温呈一致性变化,随着土温的升高或降低而相应的增加或减少。文章进一步揭示了林地植被平抑这种动态效应,而裸地则响应于温度变化;这种不同植被系统下的动态差异在解释岩溶沉积记录和讨论岩溶作用与碳循环的关系时值得充分注意。     

土壤温室气体产生与排放影响因素研究进展

土壤是温室气体(如CO2、CH4和N2O)产生的重要源,土壤温室气体主要来自于微生物呼吸,植物根呼吸和土壤动物呼吸。土壤温室气体排放机制及其影响因素是研究全球碳氮循环的重要组成部分。研究表明,影响土壤呼吸的因素很多,土壤理化性质如温度、含水量、有机质含量、pH值、氧化还原电位(Eh)、土壤质地等因素都可以直接影响土壤微生物量及其生理生化过程,从而影响温室气体排放。其中,土壤温度,湿度、有机质含量是关键性因素。此外,地域气候、土地利用以及土地覆盖变化也可以通过改变土壤理化性质及呼吸底物来影响温室气体排放。文章重点论述了土壤温室气体排放机制,排放影响因素以及排放的日变化和季节变化规律。认为今后的研究方向应该是土壤微环境碳氮循环机制,土壤呼吸模型在尺度上的推延,以及注重中国陆地与近海生态系统碳固定及减少碳排放的对策和应用技术研究,特别在人工林碳固定及农业固碳减排方面加大研究力度等。     

Assessing self-organization of plant communities—A thermodynamic approach

Thermodynamics is a powerful tool for the study of system development and has the potential to be applied to studies of ecological complexity. Here, we develop a set of thermodynamic indicators including energy capture and energy dissipation to quantify plant community self-organization. The study ecosystems included a tropical seasonal rainforest, an artificial tropical rainforest, a rubber plantation, and two Chromolaena odorata (L.) R.M. King & H. Robinson communities aged 13 years and 1 year. The communities represent a complexity transect from primary vegetation, to transitional community, economic plantation, and fallows and are typical for Xishuangbanna, southwestern China. The indicators of ecosystem self-organization are sensitive to plant community type and seasonality, and demonstrate that the tropical seasonal rainforest is highly self-organized and plays an important role in local environmental stability via the land surface thermal regulation. The rubber plantation is at a very low level of self-organization as quantified by the thermodynamic indicators, especially during the dry season. The expansion of the area of rubber plantation and shrinkage of tropical seasonal rainforest would likely induce local surface warming and a larger daily temperature range.     

A hierarchical analysis of terrestrial ecosystem model Biome-BGC: Equilibrium analysis and model calibration

The increasing complexity of ecosystem models represents a major difficulty in tuning model parameters and analyzing simulated results. To address this problem, this study develops a hierarchical scheme that simplifies the Biome-BGC model into three functionally cascaded tiers and analyzes them sequentially. The first-tier model focuses on leaf-level ecophysiological processes; it simulates evapotranspiration and photosynthesis with prescribed leaf area index (LAI). The restriction on LAI is then lifted in the following two model tiers, which analyze how carbon and nitrogen is cycled at the whole-plant level (the second tier) and in all litter/soil pools (the third tier) to dynamically support the prescribed canopy. In particular, this study analyzes the steady state of these two model tiers by a set of equilibrium equations that are derived from Biome-BGC algorithms and are based on the principle of mass balance. Instead of spinning-up the model for thousands of climate years, these equations are able to estimate carbon/nitrogen stocks and fluxes of the target (steady-state) ecosystem directly from the results obtained by the first-tier model. The model hierarchy is examined with model experiments at four AmeriFlux sites. The results indicate that the proposed scheme can effectively calibrate Biome-BGC to simulate observed fluxes of evapotranspiration and photosynthesis; and the carbon/nitrogen stocks estimated by the equilibrium analysis approach are highly consistent with the results of model simulations. Therefore, the scheme developed in this study may serve as a practical guide to calibrate/analyze Biome-BGC; it also provides an efficient way to solve the problem of model spin-up, especially for applications over large regions. The same methodology may help analyze other similar ecosystem models as well.     

3 forest simulation model

The 3 forest simulation model is a process model of tree growth, carbon and nitrogen dynamics in a single-species, even-aged forest stand. It is based on the model. Major changes include the computation of sun angle and radiation as a function of latitude and day of the year, the closed-form integration of canopy production as a function of day and hour, the introduction of tree number, height, and diameter as separate state variables, and different growth strategies, mortalities, and resulting self-thinning as function of crowding competition.The tree/soil system is described by a set of nonlinear ordinary differential equations for the state variables: tree number, base diameter, tree height, wood biomass, nitrogen in wood, leaf mass, fine root mass, fruit biomass, assimilate, carbon and nitrogen in litter, carbon and nitrogen in soil organic matter, and plant-available nitrogen. The model includes explicit formulations of all relevant ecophysiological processes such as: computation of radiation as a function of seasonal time, daytime and cloudiness, light attenuation in the canopy, and canopy photosynthesis as function of latitude, seasonal time, and daytime, respiration of all parts, assimilate allocation, increment formation, nitrogen fixation, mineralization, humification and leaching, forest management (thinning, felling, litter removal, fertilization etc.), temperature effects on respiration and decomposition, and environmental effects (pollution damage to photosynthesis, leaves, and fine roots). Only ecophysiological parameters which can be either directly measured or estimated with reasonable certainty are used. 3 is a generic process model which requires species- and site-specific parametrization. It can be applied to deciduous and coniferous forests under tropical, as well as temperate or boreal conditions.The paper presents a full documentation of the mathematical model as well as representative simulation results for spruce and acacia.     

treedyn3 forest simulation model

The treedyn3 forest simulation model is a process model of tree growth, carbon and nitrogen dynamics in a single-species, even-aged forest stand. It is based on the treedyn model. Major changes include the computation of sun angle and radiation as a function of latitude and day of the year, the closed-form integration of canopy production as a function of day and hour, the introduction of tree number, height, and diameter as separate state variables, and different growth strategies, mortalities, and resulting self-thinning as function of crowding competition.The tree/soil system is described by a set of nonlinear ordinary differential equations for the state variables: tree number, base diameter, tree height, wood biomass, nitrogen in wood, leaf mass, fine root mass, fruit biomass, assimilate, carbon and nitrogen in litter, carbon and nitrogen in soil organic matter, and plant-available nitrogen. The model includes explicit formulations of all relevant ecophysiological processes such as: computation of radiation as a function of seasonal time, daytime and cloudiness, light attenuation in the canopy, and canopy photosynthesis as function of latitude, seasonal time, and daytime, respiration of all parts, assimilate allocation, increment formation, nitrogen fixation, mineralization, humification and leaching, forest management (thinning, felling, litter removal, fertilization etc.), temperature effects on respiration and decomposition, and environmental effects (pollution damage to photosynthesis, leaves, and fine roots). Only ecophysiological parameters which can be either directly measured or estimated with reasonable certainty are used. treedyn3 is a generic process model which requires species- and site-specific parametrization. It can be applied to deciduous and coniferous forests under tropical, as well as temperate or boreal conditions.The paper presents a full documentation of the mathematical model as well as representative simulation results for spruce and acacia.     

Application of a three-dimensional model for assessing effects of small clear-cuttings on radiation and soil temperature

A three-dimensional model Mixfor-3D of soil–vegetation–atmosphere transfer (SVAT) was developed and applied to estimate possible effects of tree clear-cutting on radiation and soil temperature regimes of a forest ecosystem. The Mixfor-3D model consists of several closely coupled 3D sub-models describing: forest stand structure; radiative transfer in a forest canopy; turbulent transfer of sensible heat, H₂O and CO₂ between ground surface and the atmospheric surface layer; evapotranspiration of ground surface vegetation and soil; heat and moisture transfer in soil. The model operates with the horizontal grid resolution, 2 m × 2 m; vertical resolution, 1 m and primary time step, 1 h.     

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.     

Integrating soil carbon cycling with that of nitrogen and phosphorus in the watershed model SWAT: Theory and model testing

In this paper we describe and test a sub-model that integrates the cycling of carbon (C), nitrogen (N) and phosphorus (P) in the Soil Water Assessment Tool (SWAT) watershed model. The core of the sub-model is a multi-layer, one-pool soil organic carbon (S_C) algorithm, in which the decomposition rate of S_C and input rate to S_C (through decomposition and humification of residues) depend on the current size of S_C. The organic N and P fluxes are coupled to that of C and depend on the available mineral N and P, and the C:N and N:P ratios of the decomposing pools. Tillage explicitly affects the soil organic matter turnover rate through tool-specific coefficients. Unlike most models, the turnover of soil organic matter does not follow first order kinetics. Each soil layer has a specific maximum capacity to accumulate C or C saturation (S_x) that depends on texture and controls the turnover rate. It is shown in an analytical solution that S_x is a parameter with major influence in the model C dynamics. Testing with a 65-yr data set from the dryland wheat growing region in Oregon shows that the model adequately simulates the S_C dynamics in the topsoil (top 0.3 m) for three different treatments. Three key model parameters, the optimal decomposition and humification rates and a factor controlling the effect of soil moisture and temperature on the decomposition rate, showed low uncertainty as determined by generalized likelihood uncertainty estimation. Nonetheless, the parameter set that provided accurate simulations in the topsoil tended to overestimate S_C in the subsoil, suggesting that a mechanism that expresses at depth might not be represented in the current sub-model structure. The explicit integration of C, N, and P fluxes allows for a more cohesive simulation of nutrient cycling in the SWAT model. The sub-model has to be tested in forestland and rangeland in addition to agricultural land, and in diverse soils with extreme properties such high or low pH, an organic horizon, or volcanic soils.     

Vegetation competition model for water and light limitation. II: Spatial dynamics of groundwater and vegetation

In temperate climates groundwater can have a profound effect on vegetation, because it strongly influences the spatio-temporal distribution of soil moisture in the rootzone and therefore the occurrence of water and oxygen stress of vegetation. This article focuses on vegetation and groundwater dynamics along a hill slope by developing and evaluating a fully coupled hydrological-vegetation model for a temperate forest ecosystem. The vegetation model is described in part 1 of this series of two papers. To simulate the hydrology an extended version of the saturated-unsaturated hydrological model STARWARS has been used. The coupled model is used to investigate both the short and long-term dynamics for a system of two species. Both compete for light and water where one is adapted to wet conditions and the other to dry conditions. The daily dynamics show that the influence of groundwater is particularly strong in spring when waterlogging occurs due to decreased evapotranspiration in winter. Long simulation runs of 1000 years were performed to study the equilibrium state for the two species. Comparison of simulation results with observations of groundwater depth and vegetation types along a dry-wet gradient in a natural forest shows that a reductionist approach is able to capture these patterns well. Sensitivity analysis shows that the border between wet- and dry-adapted species moves upslope with increased rainfall, decreased slope angle and decreased aquifer thickness. These results are similar to previous findings which were based on global maximization of ecosystem evaporation or minimizing ecosystem stress. Comparison of runs with a fixed and a dynamic groundwater table shows that a dynamic groundwater table facilitates a wider transition zone between vegetation types along the hill slope. In this transition the biomass of vegetation is higher in the case of a dynamic groundwater than in case of a static groundwater table. This underlines the importance of incorporating spatial groundwater dynamics in models of groundwater influenced ecosystems.     

Nitrogen controls on ecosystem carbon sequestration: a model implementation and application to Saskatchewan,Canada

A plant–soil nitrogen (N) cycling model was developed and incorporated into the Integrated BIosphere Simulator (IBIS) of Foley et al. [Foley, J.A., Prentice, I.C., Ramankutty, N., Levis, S., Pollard, D., Sitch, S., Haxeltine, A., 1996. An integrated biosphere model of land surface process, terrestrial carbon balance and vegetation dynamics. Global Biogeochem. Cycles 10, 603–628]. In the N-model, soil mineral N regulates ecosystem carbon (C) fluxes and ecosystem C:N ratios. Net primary productivity (NPP) is controlled by feedbacks from both leaf C:N and soil mineral N. Leaf C:N determines the foliar and canopy photosynthesis rates, while soil mineral N determines the N availability for plant growth and the efficiency of biomass construction. Nitrogen controls on the decomposition of soil organic matter (SOM) are implemented through N immobilization and mineralization separately. The model allows greater SOM mineralization at lower mineral N, and conversely, allows greater N immobilization at higher mineral N. The model's seasonal and inter-annual behaviours are demonstrated. A regional simulation for Saskatchewan, Canada, was performed for the period 1851–2000 at a 10 km × 10 km resolution. Simulated NPP was compared with high-resolution (1 km × 1 km) NPP estimated from remote sensing data using the boreal ecosystem productivity simulator (BEPS) [Liu, J., Chen, J.M., Cihlar, J., Park, W.M., 1997. A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote Sens. Environ. 44, 81–87]. The agreement between IBIS and BEPS, particularly in NPP spatial variation, was considerably improved when the N controls were introduced into IBIS.     

Dynamic model of Lake Chozas (León, NW Spain)—Decrease in eco-exergy from clear to turbid phase due to introduction of exotic crayfish

We developed a dynamic model of the phosphorus cycle in Lake Chozas, a small shallow water body in León (NW Spain). The calibrated model simulated seasonal dynamics of phosphorus concentrations in major components of the lake's ecological network before and after 1997, the year when an invasive allochthonous crustacean, the Louisiana red swamp crayfish (Procambarus clarkii), was introduced into the lake. The shift from clean to turbid phase, due to grazing by crayfish on submerged vegetation, caused a gradual decrease in eco-exergy, reflecting an increase in entropy, related to breakdown of ecosystem internal equilibria. This case study verifies the hypothesis of Marchi et al. (2010) that, after an initial relatively stable state, the allochthonous species may cause an increase in entropy indicating perturbation of the ecosystem.     

Biotic and abiotic regulation of lightning fire initiation in the mixedwood boreal forest

Lightning fire is the dominant natural disturbance of the western mixedwood boreal forest of North America. We quantified the independent effects of weather and forest composition on lightning fire initiation (a detected and recorded fire start) patterns in Alberta, Canada, to demonstrate how these biotic and abiotic components contribute to ecosystem dynamics in the mixedwood boreal forest. We used logistic regression to describe variation in annual initiation occurrence among 10,000-ha landscape units (voxels) covering a 9 million-ha study region over 11 years. At a voxel scale, forest composition explained more variation in annual initiation than did weather indices. Initiations occurred more frequently in landscapes with more conifer fuels (Picea spp.), and less in aspen-dominated (Populus spp.) ones. Initiations were less frequent in landscapes that had recently burned. Variation in initiation was also influenced by joint weather-lightning indices, but to a lesser degree. For each voxel, these indices quantified the number of days in the fire season when moisture levels were low and lightning was detected. Regional indices of fire weather severity explained substantial interannual variation of initiation, and the effect of forest composition was stronger in years with more severe fire weather. Our study is a conclusive demonstration of biotic and abiotic regulation of lightning fire initiation in the mixedwood boreal forest. The independent effects of forest composition emphasize that vegetation feedbacks strongly regulate disturbance dynamics in the region.     

GIS-based modeling of the geographic distribution of Quercus emoryi Torr. (Fagaceae) in México and identification of significant environmental factors influencing the species’ distribution

The greatest concentration of oak species in the world is believed to be found in Mexico. These species are potentially useful for reforestation because of their capacity to adapt to diverse environments. Knowledge of their geographic distribution and of species–environment relations is essential for decision-making in the management and conservation of natural resources. The objectives of this study were to develop a model of the distribution of Quercus emoryi Torr. in Mexico, using geographic information systems and data layers of climatic and other variables, and to determine the variables that significantly influence the distribution of the species. The study consisted of the following steps: (A) selection of the target species from a botanical scientific collection, (B) characterization of the collecting sites using images with values or categories of the variables, (C) model building with the overlay of images that meet the habitat conditions determined from the characterization of sites, (D) model validation with independent data in order to determine the precision of the model, (E) model calibration through adjustment of the intervals of some variables, and (F) sensitivity analysis using precision and concordance non-parametric statistics applied to pairs of images. Results show that the intervals of the variables that best describe the species’ habitat are the following: altitude from 1650 to 2750 amsl, slope from 0 to 66°; average minimum temperature of January from −12 to −3 °C; mean temperature of June from 11 to 25 °C; mean annual precipitation from 218 to 1225 mm; soil units: lithosol, eutric cambisol, haplic phaeozem, chromic luvisol, rendzina, luvic xerosol, mollic planosol, pellic vertisol, eutric regosol; type of vegetation: oak forest, oak–pine forest, pine forest, pine–oak forest, juniperus forest, low open forest, natural grassland and chaparral. The resulting model of the geographic distribution of Quercus emoryi in Mexico had the following values for non-parametric statistics of precision and agreement: Kappa index of 0.613 and 0.788, overall accuracy of 0.806 and 0.894, sensitivity of 0.650 and 0.825, specificity of 0.963, positive predictive value of 0.945 and 0.957 and negative predictive value of 0.733 and 0.846. Results indicate that the variable average minimum temperature of January, with a maximum value of −3 °C, is an important factor in limiting the species’ distribution.