Element mobility and partitioning along a soil acidity gradient in central Ontario forests, Canada

The potential environmental risk posed by metals in forest soils is typically evaluated by modeling metal mobility using soil-solution partitioning coefficients (K(d)), although such information is generally restricted to a few well-studied metals. Soil-solution partitioning coefficients were determined for 17 mineral elements (Al, As, Be, Ba, Ca, Cr, Cu, Fe, Ga, K, Li, Mg, Rb, Sr, Tl, U and V) in A-horizon (0-5 cm) soil at 46 forested sites that border the Precambrian Shield in central Ontario, where soil pH(aq) varied from 3.9 to 8.1. Sites were dominated by mature sugar maple (Acer saccharum Marsh.), white birch (Betula papyrifera Marsh.), balsam fir (Abies balsamea (L.) Mill.) or white pine (Pinus strobus L.). Log K(d) values for all elements could be predicted by empirical linear regression with soil pH (r (2) = 0.17-0.77) independent of forest type, although this relationship was greatly affected by positive relationships between acid-extractable metal concentration and pH(aq) for 13 of the 17 elements. Elements that exhibited strong or moderate (r (2)> 0.29; p < 0.001) relationships with soil pH(aq) in soil water extracts include Al, Ba, Fe, Ga, K, Li, Rb, Tl, V (negative) and Ca (positive). Elemental partitioning in mineral soil was independent of forest type; tree species differed in their response to chemical differences in mineral soil. For example, Rb, Ba, and Sr concentrations in foliage of sugar maple and white birch significantly increased with increasing soil acidity, whereas Rb, Ba, and Sr concentrations in balsam fir and white pine foliage exhibited no response to soil pH(aq). While K(d) values can provide useful information on the potential mobility and bioavailability of mineral elements in forest soils, care must be used when interpreting the relative contribution of solid and aqueous phases to this relationship and the differing responses of vegetation in elemental cycling in forests must also be considered.     

Modeling mercury emissions from forest fires in the Mediterranean region

Mercury emissions from forest fires in countries bordering the Mediterranean Sea have been estimated on the basis of satellite observations for the year 2006. The assessment has been done by means of the Moderate Resolution Imaging Spectroradiometer (MODIS) products (MOD12Q1, MOD14A2, MOD15A2, MOD44B). Estimates show that wild fires have burnt 310,268 ha in the Region, affecting by 45% the Mixed Forest and by 37% the Evergreen Needleleaf Forest and the Evergreen Broadleaf Forest. The amount of biomass burned was about 66,000 Mg for the Evergreen Needleleaf Forest, 72,000 Mg for the Evergreen Broadleaf Forest and 196,000 Mg for the Mixed Forest. The total amount of mercury released to the atmosphere in the Mediterranean countries accounted for 4.3 Mg year⁻¹ with Italy, France, Austria, Bulgaria, Algeria, Spain and Croatia being the most contributing countries with annual emission ranging from 330 to 970 kg year⁻¹. The maximum release of Gaseous Elemental Mercury (GEM) and particulate mercury (Hg(p)) in the region occurred in July with 1,218 kg. The uncertainty of our estimates is comparable with that associated to current assessments of mercury emissions from major industrial sources.     

Bioconcentration factors of mercury by Parasol Mushroom (Macrolepiota procera)

To examine bioconcentration factors (BCFs) of mercury by Parasol Mushroom (Macrolepiota procera) roughly similarly sized (a cap diameter) fruiting bodies of this fungus and underlying soil (0–10 cm) samples were collected at 15 sites in Poland between 1995 and 2003. The total mercury content of the individual caps and stipes of Parasol Mushroom ranged from 0.05 to 22 mg Hg/kg dry matter (d.m.) and from 0.05 to 20 mg Hg/kg d.m., while the means were from 1.1 to 8.4 mg Hg/kg d.m. and from 0.83 to 6.8 mg Hg/kg d.m., respectively. The caps generally contained higher concentrations of mercury when compared to stipes, and the means of the cap to stipe mercury concentration quotient ranged from 1.3 to 4.6. The range of mercury concentration in topsoil samples collected at the sites where the fruiting bodies were collected was from 0.01 to 0.54 mg/g d.m. (means ranged from 0.022 to 0.36 mg/g d.m.). The BCFs factors for total mercury varied from 0.52 to 470 for individual caps and 0.52 to 360 for stipes, while average values, depending on the site, were from 16 to 220 and from 7.6 to 130 for caps and stipes, respectively.     

Response of tree growth to a changing climate in boreal central Canada: A comparison of empirical,process-based,and hybrid modelling approaches

The impact of 2 × CO₂ driven climate change on radial growth of boreal tree species Pinus banksiana Lamb., Populus tremuloides Michx. and Picea mariana (Mill.) BSP growing in the Duck Mountain Provincial Forest of Manitoba (DMPF), Canada, is simulated using empirical and process-based model approaches. First, empirical relationships between growth and climate are developed. Stepwise multiple-regression models are conducted between tree-ring growth increments (TRGI) and monthly drought, precipitation and temperature series. Predictive skills are tested using a calibration–verification scheme. The established relationships are then transferred to climates driven by 1× and 2 × CO₂ scenarios using outputs from the Canadian second-generation coupled global climate model. Second, empirical results are contrasted with process-based projections of net primary productivity allocated to stem development (NPP_s). At the finest scale, a leaf-level model of photosynthesis is used to simulate canopy properties per species and their interaction with the variability in radiation, temperature and vapour pressure deficit. Then, a top-down plot-level model of forest productivity is used to simulate landscape-level productivity by capturing the between-stand variability in forest cover. Results show that the predicted TRGI from the empirical models account for up to 56.3% of the variance in the observed TRGI over the period 1912–1999. Under a 2 × CO₂ scenario, the predicted impact of climate change is a radial growth decline for all three species under study. However, projections obtained from the process-based model suggest that an increasing growing season length in a changing climate could counteract and potentially overwhelm the negative influence of increased drought stress. The divergence between TRGI and NPP_s simulations likely resulted, among others, from assumptions about soil water holding capacity and from calibration of variables affecting gross primary productivity. An attempt was therefore made to bridge the gap between the two modelling approaches by using physiological variables as TRGI predictors. Results obtained in this manner are similar to those obtained using climate variables, and suggest that the positive effect of increasing growing season length would be counteracted by increasing summer temperatures. Notwithstanding uncertainties in these simulations (CO₂ fertilization effect, feedback from disturbance regimes, phenology of species, and uncertainties in future CO₂ emissions), a decrease in forest productivity with climate change should be considered as a plausible scenario in sustainable forest management planning of the DMPF.     

An assessment of sampling,preservation, and analytical procedures for arsenic speciation in potentially contaminated waters

This study was undertaken to ascertain optimal methods of sampling, preserving, separating, and analyzing arsenic species in potentially contaminated waters. Arsenic species are readily transformed in nature by slight changes in conditions. Each species has a different toxicity and mobility. The conventional field sampling method using filters of 0.45 μm in size could overestimate the dissolved arsenic concentrations, as passing suspended particles that can act as a sink or source of arsenic depending on the site condition. For arsenic species in neutral pH and iron-poor waters, the precipitation can be stable for up to 3 days without any treatment, but for longer periods, a preservative, such as phosphoric acid, is required. Also, the analytical procedure must be selected carefully because the levels and hydride generation efficiencies of arsenic in different species can vary, even for the same amount of arsenic. For arsenic speciation in samples that also include organic species, a hybrid high-performance liquid chromatography (HPLC) column and inductively coupled plasma mass spectrometry (ICP-MS) gave the best resolution and lowest detection limits. However, the procedure using a solid phase extraction (SPE) cartridge can be used economically and conveniently for analyzing samples containing only inorganic arsenic species, such as groundwater, especially that related to mine activity.     

Potentials and limitations of using large-scale forest inventory data for evaluating forest succession models

Forest gap models have been applied widely to examine forest development under natural conditions and to investigate the effect of climate change on forest succession. Due to the complexity and parameter requirements of such models a rigorous evaluation is required to build confidence in the simulation results. However, appropriate data for model assessment are scarce at the large spatial and temporal scales of successional dynamics. In this study, we explore a data source for the evaluation of forest gap models that has been used only little in the past, i.e., large-scale National Forest Inventory data. The key objectives of this study were (a) to examine the potentials and limitations of using large-scale forest inventory data for evaluating the performance of forest gap models and (b) to test two particular models as case studies to derive recommendations for their future improvement.     

Model correlation in stochastic forest simulators—A case of multilevel multivariate model for seedling establishment

Forest development can be predicted by the use of forest simulators based on various statistical models describing the forest and its dynamics. One potential approach to study the reliability of the simulators is to utilise Monte Carlo simulation techniques to generate a predictive distribution of a forest characteristic. One problem in examining the effect of model uncertainty in forestry decision making, however, is correlation between the models. If this is not taken into account, predictions of the model systems may become biased, and the effect of errors on decision making may be underestimated. In reality, the models often are interdependent, but the correlations usually are not known because the models have been estimated in separate studies. The aim of this paper is to study the impacts of between-model dependencies on the predictive distribution of forest characteristics by Monte Carlo simulation techniques. We utilise a case of predicting seedling establishment of planted Norway spruce (Picea abies (L.) Karst.) stands as an example with multivariate multilevel model structures. Regardless of low cross-correlations between the models, ignoring them led to significant underestimation of the amount of competing broadleaves to be removed in pre-commercial thinning. Therefore, we recommend that between-model dependencies are clarified and considered in stochastic simulations. In our case, between-model interdependencies can be reliably estimated with a limited dataset. In addition, estimating the models separately and using the model residuals to estimate interdependencies between models were also sufficient to take the between-model dependencies into account when producing stochastic predictions for silvicultural decision making.     

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.     

The impact of fragmentation and density regulation on forest succession in the Atlantic rain forest

The Atlantic Rain Forest, an important biodiversity hot spot, has faced severe habitat loss since the last century which has resulted in a highly fragmented landscape with a large number of small forest patches (<100 ha). For conservation planning it is essential to understand how current and future forest regeneration depends on ecological processes, fragment size and the connection to the regional seed pool. We have investigated the following questions by applying the forest growth simulation model FORMIND to the situation of the Atlantic Forest in the state of São Paulo, SE Brazil: (1) which set of parameters describing the local regeneration and level of density regulation can reproduce the biomass distribution and stem density of an old growth forest in a reserve? (2) Which additional processes apart from those describing the dynamics of an old growth forest, drive forest succession of small isolated fragments? (3) Which role does external seed input play during succession? Therefore, more than 300 tree species have been classified into nine plant functional types (PFTs), which are characterized by maximum potential height and shade tolerance. We differentiate between two seed dispersal modes: (i) local dispersal, i.e. all seedlings originated from fertile trees within the simulated area and (ii) external seed rain. Local seed dispersal has been parameterized following the pattern oriented approach, using biomass estimates of old growth forest. We have found that moderate density regulation is essential to achieve coexistence for a broad range of regeneration parameters. Considering the expected uncertainty and variability in the regeneration processes it is important that the forest dynamics are robust to variations in the regeneration parameters. Furthermore, edge effects such as increased mortality at the border and external seed rain have been necessary to reproduce the patterns for small isolated fragments. Overall, simulated biomass is much lower in the fragments compared to the continuous forest, whereas shade tolerant species are affected most strongly by fragmentation. Our simulations can supplement empirical studies by extrapolating local knowledge on edge effects of fragments to larger temporal and spatial scales. In particular our results show the importance of external seed rain and therefore highlight the importance of structural connectivity between regenerating fragments and mature forest stands.     

Using MCA tools for evaluating community-managed forests from a green economy perspective: lessons from Nepal

ABSTRACT

Nepal is in the process of formulating its forest policies at the provincial level . Various community-managed forests have been designed in the past by the Nepal government to decentralize the forest for its sustainable management practice. This study facilitates the process of identifying appropriate forest management options in two of the provinces, namely Provinces Three and Gandaki. Four forest management options – passive, active, scientific and multiple – were identified following the existing management practices. For the evaluation of the overall performance of the options, a framework with three criteria, 10 indicators and 28 verifiers were designed. The framework followed the green economy perspective considering the improvement of the forest conditions, economic and social well-being, and low carbon emission. The Analytical Hierarchy Process was used to prioritize the best management option and analyse trade-offs to guide future decision-making and reduce the risk of unwanted consequences. Our results show that the elicitation of preferences for the evaluation criteria varied by stakeholder groups. Their preference was largely guided by improving the forest resource condition and economic well-being. Foresters prefer scientific and active forest management, policymakers prefer multiple-use forest management and scientific management, whereas community forest user groups prefer active forest management. We argue that a scientific management approach may contribute better to economic aspects, although it may often compromise the other aspects. The multiple forest management option seems to be the best for green economy considering ecological, economic and social consequences.