30 research outputs found

    Relationship between biodiversity indicators and its economic value – case study

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    Background and Purpose:Within the framework ofmulti-purpose forest management, biodiversity is usually considered as one of forest functions along with production, recreation and other functions of forests, while according to biodiversity definition and its partial components, these functions are integral elements of biodiversity. Forest inventory is an objective method for collecting information about biodiversity and forest functions. Materials and Methods: In the presented study, the data from forest inventory of the University Forest Enterprise Kostelec based on stratification sampling design (1,188 sample plots in 86 strata) were used for the analysis of the relationship between biodiversity indicators and its economic value. The area of the enterprise is characterised by heterogeneous site and landscape conditions. From the inventory data we quantified 171 partial diversity indicators. On the base of ANOVA andmultiple linear regression analysis, we selected the most suitable indicators most closely correlated to the sum of the values of individual social and economic forest functions. Results and Conclusion: We found that the relationship between the economic value of biodiversity and selected indicators is significant. Nevertheless, the derived models could explain not more than 25% of the total variability of the analysed relationship. Future research should search for objective indicators of biodiversity, and should aim at improving economic valuation of biodiversity

    Forest carbon allocation modelling under climate change

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    Carbon allocation plays a key role in ecosystem dynamics and plant adaptation to changing environmental conditions. Hence, proper description of this process in dynamic vegetation models is crucial for the simulations of the impact of climate change on carbon cycling in forests. Here we review how carbon allocation modelling is implemented in 31 dynamic vegetation models to identify the main gaps compared to our theoretical and empirical understanding of carbon allocation. We found that a hybrid approach based on combining several principles and/or types of carbon allocation modelling prevailed in examined models. The analysis revealed that although the number of carbon allocation studies over the last 10 years has substantially increased, some background processes are still insufficiently understood, and some issues in models are frequently oversimplified or even omitted. Hence, current challenges for carbon allocation modelling in forest ecosystems are (i) to overcome remaining limits in process understanding, particularly regarding the impact of disturbances on carbon allocation, accumulation and utilisation of non-structural carbohydrates, and carbon use by symbionts, and (ii) to implement existing knowledge to mechanistic description of carbon allocation in models that would integrate the impact of environmental conditions, disturbances, and seasonal variation in carbon allocation, or (iii) to improve more simplistic models by accounting for the impact of crucial factors affecting carbon allocation in particular environment

    Tree mortality submodels drive simulated long-term forest dynamics: assessing 15 models from the stand to global scale

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    Models are pivotal for assessing future forest dynamics under the impacts of changing climate and management practices, incorporating representations of tree growth, mortality, and regeneration. Quantitative studies on the importance of mortality submodels are scarce. We evaluated 15 dynamic vegetation models (DVMs) regarding their sensitivity to different formulations of tree mortality under different degrees of climate change. The set of models comprised eight DVMs at the stand scale, three at the landscape scale, and four typically applied at the continental to global scale. Some incorporate empirically derived mortality models, and others are based on experimental data, whereas still others are based on theoretical reasoning. Each DVM was run with at least two alternative mortality submodels. Model behavior was evaluated against empirical time series data, and then, the models were subjected to different scenarios of climate change. Most DVMs matched empirical data quite well, irrespective of the mortality submodel that was used. However, mortality submodels that performed in a very similar manner against past data often led to sharply different trajectories of forest dynamics under future climate change. Most DVMs featured high sensitivity to the mortality submodel, with deviations of basal area and stem numbers on the order of 10–40% per century under current climate and 20–170% under climate change. The sensitivity of a given DVM to scenarios of climate change, however, was typically lower by a factor of two to three. We conclude that (1) mortality is one of the most uncertain processes when it comes to assessing forest response to climate change, and (2) more data and a better process understanding of tree mortality are needed to improve the robustness of simulated future forest dynamics. Our study highlights that comparing several alternative mortality formulations in DVMs provides valuable insights into the effects of process uncertainties on simulated future forest dynamics

    Quantification of tree species diversity in forest stands—model BIODIVERSS

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    Country and regional carbon stock in forest cover – estimates based on the first cycle of the Czech National Forest Inventory data (2001–2004)

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    Since forests can play an efficient role in the mitigation of greenhouse gas emissions, objective information about the actual carbon stock is very important. Therefore, the presented paper analysed the carbon stock in the living merchantable trees (with diameter at breast height above 7 cm) of the Czech forests with regard to groups of tree species and tree compartments (wood under bark with diameter above 7 cm, wood under bark with diameter below 7 cm, bark, green twigs, foliage, stump and roots). We examined its regional distribution and relationship to the number of inhabitants and the gross domestic product. The data used for the analysis originated from 13,929 forest plots of the first Czech National Forest Inventory performed between 2001 and 2004. The total tree carbon stock was obtained as a sum of the carbon stock in the individual tree compartments estimated from the biomass amount in the compartments multiplied by the relative carbon content. Wood biomass amount was calculated by multiplying a particular part of tree volume with species-specific green wood density. The total amount of carbon stored in forest trees in the Czech Republic was over 327 mill. t, which is about 113 t of carbon per ha of forests. The highest carbon amount (160 mill. t, i.e. 49.0% of the total amount) was fixed in spruce. The minimum carbon amount fixed in the forest cover (14.35 mill. t) was calculated for Ústecký kraj (region), while the maximum carbon amount (51.51 mill. t) was found in Jihočeský kraj
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