scholarly journals Large-Scale Forest Modeling: Deducing Stand Density from Inventory Data

2012 ◽  
Vol 2012 ◽  
pp. 1-13 ◽  
Author(s):  
Oskar Franklin ◽  
Elena Moltchanova ◽  
Florian Kraxner ◽  
Rupert Seidl ◽  
Hannes Böttcher ◽  
...  
Keyword(s):  
Large Scale ◽  
Model Performance ◽  
Stand Density ◽  
Forest Growth ◽  
Data Availability ◽  
Inventory Data ◽  
Combined Model ◽  
Age Cohorts ◽  
Forest Growth Model ◽  
Forest Modeling

While effects of thinning and natural disturbances on stand density play a central role for forest growth, their representation in large-scale studies is restricted by both model and data availability. Here a forest growth model was combined with a newly developed generic thinning model to estimate stand density and site productivity based on widely available inventory data (tree species, age class, volume, and increment). The combined model successfully coupled biomass, increment, and stand closure (=stand density/self-thinning limited stand density), as indicated by cross-validation against European-wide inventory data. The improvement in model performance attained by including variable stand closure among age cohorts compared to a fixed closure suggests that stand closure is an important parameter for accurate forest growth modeling also at large scales.

scholarly journals Landscape-scale parameterization of a tree-level forest growth model: a k-nearest neighbor imputation approach incorporating LiDAR data

2010 ◽  
Vol 40 (2) ◽  
pp. 184-199 ◽  
Author(s):  
Michael J. Falkowski ◽  
Andrew T. Hudak ◽  
Nicholas L. Crookston ◽  
Paul E. Gessler ◽  
Edward H. Uebler ◽  
...  
Keyword(s):  
Forest Inventory ◽  
Nearest Neighbor ◽  
Forest Growth ◽  
Tree Level ◽  
Lidar Data ◽  
Inventory Data ◽  
K Nearest Neighbor ◽  
Forest Inventory Data ◽  
Forest Growth Model ◽  
Nearest Neighbor Imputation

Sustainable forest management requires timely, detailed forest inventory data across large areas, which is difficult to obtain via traditional forest inventory techniques. This study evaluated k-nearest neighbor imputation models incorporating LiDAR data to predict tree-level inventory data (individual tree height, diameter at breast height, and species) across a 12 100 ha study area in northeastern Oregon, USA. The primary objective was to provide spatially explicit data to parameterize the Forest Vegetation Simulator, a tree-level forest growth model. The final imputation model utilized LiDAR-derived height measurements and topographic variables to spatially predict tree-level forest inventory data. When compared with an independent data set, the accuracy of forest inventory metrics was high; the root mean square difference of imputed basal area and stem volume estimates were 5 m2·ha–1 and 16 m3·ha–1, respectively. However, the error of imputed forest inventory metrics incorporating small trees (e.g., quadratic mean diameter, tree density) was considerably higher. Forest Vegetation Simulator growth projections based upon imputed forest inventory data follow trends similar to growth projections based upon independent inventory data. This study represents a significant improvement in our capabilities to predict detailed, tree-level forest inventory data across large areas, which could ultimately lead to more informed forest management practices and policies.

Dynamic coupling of allometric ratios to a process-based forest growth model for estimating the impacts of stand density changes

2020 ◽  
Vol 93 (5) ◽  
pp. 601-615
Author(s):  
Rüdiger Grote ◽  
David Kraus ◽  
Wendelin Weis ◽  
Rasmus Ettl ◽  
Axel Göttlein
Keyword(s):  
Climate Change ◽  
Early Development ◽  
Stand Density ◽  
Climate Change Impacts ◽  
Forest Growth ◽  
Canopy Layer ◽  
Mature Trees ◽  
Development Stages ◽  
Allometric Relations ◽  
Forest Growth Model

Abstract Process-based models are increasingly applied for simulating long-term forest developments in order to capture climate change impacts and to investigate suitable management responses. Regarding dimensional development, however, allometric relations such as the height/diameter ratio, branch and coarse root fractions or the dependency of crown dimension on stem diameter often do not account for environmental influences. While this may be appropriate for even-aged, monospecific forests, serious biases can be expected if stand density or forest structure changes rapidly. Such events occur in particular when forests experience disturbances such as intensive thinning or during early development stages of planted or naturally regenerated trees. We therefore suggest a calculation of allometric relationships that depends primarily on neighbourhood competition. Respective equations have been implemented into a physiology-based ecosystem model that considers asymmetric competition by explicit simulation of resource acquisition and depletion per canopy layer. The new implementation has been tested at two sites in Germany where beech (Fagus sylvatica) saplings have either been planted below a shelterwood of old spruces (Picea abies) or grown under clear-cut conditions. We show that the modified model is able to realistically describe tree development in response to stand density changes and is able to represent regeneration growth beneath a gradually decreasing overstorey of mature trees. In particular, the model could represent the faster crown size development in saplings until full ground coverage is established and a faster height growth afterwards. The effect enhances leaf area and thus assimilation per tree and increases carbon availability for stem growth at early development stages. Finally, the necessity to consider dynamic allometric relations with respect to climate change impacts is discussed, and further improvements are suggested.

scholarly journals Extending a Large-Scale Model to Better Represent Water Resources without Increasing the Model’s Complexity

Water ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3067
Author(s):  
Robyn Horan ◽  
Nathan J. Rickards ◽  
Alexandra Kaelin ◽  
Helen E. Baron ◽  
Thomas Thomas ◽  
...  
Keyword(s):  
Large Scale ◽  
Model Performance ◽  
Data Availability ◽  
Model Complexity ◽  
Low Flow ◽  
Scale Model ◽  
Water Balance Components ◽  
Large Scale Model ◽  
Scale Models ◽  
Availability Assessment

The increasing impact of anthropogenic interference on river basins has facilitated the development of the representation of human influences in large-scale models. The representation of groundwater and large reservoirs have realised significant developments recently. Groundwater and reservoir representation in the Global Water Availability Assessment (GWAVA) model have been improved, critically, with a minimal increase in model complexity and data input requirements, in keeping with the model’s applicability to regions with low-data availability. The increased functionality was assessed in two highly anthropogenically influenced basins. A revised groundwater routine was incorporated into GWAVA, which is fundamentally driven by three input parameters, and improved the simulation of streamflow and baseflow in the headwater catchments such that low-flow model skill increased 33–67% in the Cauvery and 66–100% in the Narmada. The existing reservoir routine was extended and improved the simulation of streamflow in catchments downstream of major reservoirs, using two calibratable parameters. The model performance was improved between 15% and 30% in the Cauvery and 7–30% in the Narmada, with the daily reservoir releases in the Cauvery improving significantly between 26% and 164%. The improvement of the groundwater and reservoir routines in GWAVA proved successful in improving the model performance, and the inclusions allowed for improved traceability of simulated water balance components. This study illustrates that improvement in the representation of human–water interactions in large-scale models is possible, without excessively increasing the model complexity and input data requirements.

scholarly journals Waldertrag und Anbaurisiko in einer unsicheren Klimazukunft

2016 ◽  
Vol 167 (1) ◽  
pp. 29-38 ◽  
Author(s):  
Christian Kölling ◽  
Tobias Mette ◽  
Thomas Knoke
Keyword(s):  
Large Scale ◽  
Analytical Approach ◽  
Mixed Forest ◽  
Forest Growth ◽  
Inventory Data ◽  
Potential Yield ◽  
Climate Conditions ◽  
Yield Risk ◽  
Risk Approach ◽  
Objective Basis

Forest productivity and cultivation risk in an uncertain climate future Changes in climate conditions will lead to strong yet uncertain changes concerning forest growth and cultivation risk. Economic success as an important criterion for management decisions depends on both aspects, natural yield and risk. This study presents a new concept how (potential) yield and risk can be estimated from large-scale inventory data. As a result, any stand can be plotted in a yield-risk coordinate system and its future yield expectancy can be described by a trajectory in the yield-risk space. This strictly analytical approach cannot take over silvicultural decisions, but facilitates them from an objective basis. The implementation of approved economic guidelines such as the caution principle or the principle of flexibility builds upon the yield-risk approach and demonstrates benefits of climate-adapted stable mixed forest silviculture.

Das nachhaltig verfügbare Holznutzungspotenzial im Schweizer Wald

2016 ◽  
Vol 167 (3) ◽  
pp. 162-171 ◽  
Author(s):  
Ruedi Taverna ◽  
Michael Gautschi ◽  
Peter Hofer
Keyword(s):  
National Level ◽  
Reference Value ◽  
Forest Growth ◽  
Long Term Effects ◽  
Management Scenarios ◽  
Additional Time ◽  
Basic Scenario ◽  
Economic Framework ◽  
Forest Growth Model ◽  
New Findings

The sustainably available wood use potential in Swiss forests Based on the most recent simulations created using the Massimo forest growth model, the sustainably available wood use potential in Swiss forests was calculated for five management scenarios for the next three decades as well as for two additional time periods in the future (to monitor the long-term effects). The term “sustainably available wood use potential” covers those wood quantities that could be put on the market, taking into account socio-ecological and economic restrictions on use. The sustainably available wood use potential is provided for production regions, priority functions as well as the assortment and qualities of timber. The previously used factors of the applied “onion” model were checked and modified, if necessary, in order to take new findings and current cost developments into consideration. The calculations for all scenarios come up with a sustainably available wood use potential that is much lower than in earlier investigations. Depending on the scenario and decade, sustainably available wood use potential accounts for less than 50% of the total use potential. The biggest decrease in total use potential was due to economic framework conditions. Turning to Switzerland as a whole, towards the end of the investigation period (2106) those scenarios including a sharp increase in use in the first three decades result in a sustainably available wood use potential that is clearly lower than the reference value used at the beginning of the simulation. In the basic scenario (constant stock) and in the scenario in which the form of management used to date (increasing stock) was simulated, the sustainably available wood use potential at national level remained more or less the same throughout the simulation period, ranging from 5 to 6 million m3 per year.

Financial distress determinants among SMEs: empirical evidence from Sweden

2020 ◽  
Vol 47 (3) ◽  
pp. 547-560 ◽  
Author(s):  
Darush Yazdanfar ◽  
Peter Öhman
Keyword(s):  
Financial Crisis ◽  
Financial Distress ◽  
Large Scale ◽  
Global Financial Crisis ◽  
Binary Logistic Regression ◽  
Data Availability ◽  
Cross Sectional ◽  
Data Set ◽  
Content Type ◽  
The Global Financial Crisis

PurposeThe purpose of this study is to empirically investigate determinants of financial distress among small and medium-sized enterprises (SMEs) during the global financial crisis and post-crisis periods.Design/methodology/approachSeveral statistical methods, including multiple binary logistic regression, were used to analyse a longitudinal cross-sectional panel data set of 3,865 Swedish SMEs operating in five industries over the 2008–2015 period.FindingsThe results suggest that financial distress is influenced by macroeconomic conditions (i.e. the global financial crisis) and, in particular, by various firm-specific characteristics (i.e. performance, financial leverage and financial distress in previous year). However, firm size and industry affiliation have no significant relationship with financial distress.Research limitationsDue to data availability, this study is limited to a sample of Swedish SMEs in five industries covering eight years. Further research could examine the generalizability of these findings by investigating other firms operating in other industries and other countries.Originality/valueThis study is the first to examine determinants of financial distress among SMEs operating in Sweden using data from a large-scale longitudinal cross-sectional database.

scholarly journals Process-Based Model Prediction of Coastal Dune Erosion through Parametric Calibration

2021 ◽  
Vol 9 (6) ◽  
pp. 635
Author(s):  
Hyeok Jin ◽  
Kideok Do ◽  
Sungwon Shin ◽  
Daniel Cox
Keyword(s):  
Large Scale ◽  
Numerical Models ◽  
Model Performance ◽  
Coastal Dunes ◽  
Wave Transformation ◽  
Storm Event ◽  
Face Model ◽  
Dune Erosion ◽  
Simulation Performance ◽  
Sand Bar

Coastal dunes are important morphological features for both ecosystems and coastal hazard mitigation. Because understanding and predicting dune erosion phenomena is very important, various numerical models have been developed to improve the accuracy. In the present study, a process-based model (XBeachX) was tested and calibrated to improve the accuracy of the simulation of dune erosion from a storm event by adjusting the coefficients in the model and comparing it with the large-scale experimental data. The breaker slope coefficient was calibrated to predict cross-shore wave transformation more accurately. To improve the prediction of the dune erosion profile, the coefficients related to skewness and asymmetry were adjusted. Moreover, the bermslope coefficient was calibrated to improve the simulation performance of the bermslope near the dune face. Model performance was assessed based on the model-data comparisons. The calibrated XBeachX successfully predicted wave transformation and dune erosion phenomena. In addition, the results obtained from other two similar experiments on dune erosion with the same calibrated set matched well with the observed wave and profile data. However, the prediction of underwater sand bar evolution remains a challenge.

scholarly journals Quantitative Recognition and Characteristic Analysis of Production-Living-Ecological Space Evolution for Five Resource-Based Cities: Zululand, Xuzhou, Lota, Surf Coast and Ruhr

2021 ◽  
Vol 13 (8) ◽  
pp. 1563
Author(s):  
Yuanyuan Tao ◽  
Qianxin Wang
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Large Scale ◽  
Remote Sensing Image ◽  
Data Availability ◽  
Function Evaluation ◽  
Characteristic Analysis ◽  
Accurate Identification ◽  
Living Space ◽  
Evolution Characteristics

The accurate identification of PLES changes and the discovery of their evolution characteristics is a key issue to improve the ability of the sustainable development for resource-based urban areas. However, the current methods are unsuitable for the long-term and large-scale PLES investigation. In this study, a modified method of PLES recognition is proposed based on the remote sensing image classification and land function evaluation technology. A multi-dimensional index system is constructed, which can provide a comprehensive evaluation for PLES evolution characteristics. For validation of the proposed methods, the remote sensing image, geographic information, and socio-economic data of five resource-based urbans (Zululand in South Africa, Xuzhou in China, Lota in Chile, Surf Coast in Australia, and Ruhr in Germany) from 1975 to 2020 are collected and tested. The results show that the data availability and calculation efficiency are significantly improved by the proposed method, and the recognition precision is better than 87% (Kappa coefficient). Furthermore, the PLES evolution characteristics show obvious differences at the different urban development stages. The expansions of production, living, and ecological space are fastest at the mining, the initial, and the middle ecological restoration stages, respectively. However, the expansion of living space is always increasing at any stage, and the disorder expansion of living space has led to the decrease of integration of production and ecological spaces. Therefore, the active polices should be formulated to guide the transformation of the living space expansion from jumping-type and spreading-type to filling-type, and the renovation of abandoned industrial and mining lands should be encouraged.

scholarly journals The Gut Microbiota of Healthy Aged Chinese Is Similar to That of the Healthy Young

mSphere ◽  
2017 ◽  
Vol 2 (5) ◽  
Author(s):  
Gaorui Bian ◽  
Gregory B. Gloor ◽  
Aihua Gong ◽  
Changsheng Jia ◽  
Wei Zhang ◽  
...  
Keyword(s):  
Data Analysis ◽  
Gut Microbiota ◽  
Large Scale ◽  
Compositional Data ◽  
Healthy Lifestyle ◽  
Compositional Data Analysis ◽  
Surprising Result ◽  
Microbiota Composition ◽  
Cross Sectional ◽  
Age Cohorts

ABSTRACT We report the large-scale use of compositional data analysis to establish a baseline microbiota composition in an extremely healthy cohort of the Chinese population. This baseline will serve for comparison for future cohorts with chronic or acute disease. In addition to the expected difference in the microbiota of children and adults, we found that the microbiota of the elderly in this population was similar in almost all respects to that of healthy people in the same population who are scores of years younger. We speculate that this similarity is a consequence of an active healthy lifestyle and diet, although cause and effect cannot be ascribed in this (or any other) cross-sectional design. One surprising result was that the gut microbiota of persons in their 20s was distinct from those of other age cohorts, and this result was replicated, suggesting that it is a reproducible finding and distinct from those of other populations. The microbiota of the aged is variously described as being more or less diverse than that of younger cohorts, but the comparison groups used and the definitions of the aged population differ between experiments. The differences are often described by null hypothesis statistical tests, which are notoriously irreproducible when dealing with large multivariate samples. We collected and examined the gut microbiota of a cross-sectional cohort of more than 1,000 very healthy Chinese individuals who spanned ages from 3 to over 100 years. The analysis of 16S rRNA gene sequencing results used a compositional data analysis paradigm coupled with measures of effect size, where ordination, differential abundance, and correlation can be explored and analyzed in a unified and reproducible framework. Our analysis showed several surprising results compared to other cohorts. First, the overall microbiota composition of the healthy aged group was similar to that of people decades younger. Second, the major differences between groups in the gut microbiota profiles were found before age 20. Third, the gut microbiota differed little between individuals from the ages of 30 to >100. Fourth, the gut microbiota of males appeared to be more variable than that of females. Taken together, the present findings suggest that the microbiota of the healthy aged in this cross-sectional study differ little from that of the healthy young in the same population, although the minor variations that do exist depend upon the comparison cohort. IMPORTANCE We report the large-scale use of compositional data analysis to establish a baseline microbiota composition in an extremely healthy cohort of the Chinese population. This baseline will serve for comparison for future cohorts with chronic or acute disease. In addition to the expected difference in the microbiota of children and adults, we found that the microbiota of the elderly in this population was similar in almost all respects to that of healthy people in the same population who are scores of years younger. We speculate that this similarity is a consequence of an active healthy lifestyle and diet, although cause and effect cannot be ascribed in this (or any other) cross-sectional design. One surprising result was that the gut microbiota of persons in their 20s was distinct from those of other age cohorts, and this result was replicated, suggesting that it is a reproducible finding and distinct from those of other populations.

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