Process-based modelling of tree and stand growth: towards a hierarchical treatment of multiscale processes

2003 ◽  
Vol 33 (3) ◽  
pp. 398-409 ◽  
Author(s):  
Annikki Mäkelä

A generally accepted method has not emerged for managing the different temporal and spatial scales in a forest ecosystem. This paper reviews a hierarchical-modular modelling tradition, with the main focus on individual tree growth throughout the rotation. At this scale, model performance requires (i) realistic long-term dynamic properties, (ii) realistic responses of growth and mortality of competing individuals, and (iii) realistic responses to ecophysio logical inputs. Model development and validation are illustrated through allocation patterns, height growth, and size-related feedbacks. Empirical work to test the approach is reviewed. In this approach, finer scale effects are embedded in parameters calculated using more detailed, interacting modules. This is exemplified by (i) the within-year effect of weather on annual photosynthesis, (ii) the effects of fast soil processes on carbon allocation and photosynthesis, and (iii) the utilization of detailed stem structure to predict wood quality. Prevailing management paradigms are reflected in growth modelling. A shift of emphasis has occurred from productivity in homogeneous canopies towards, e.g., wood quality versus total yield, spatially more explicit models, and growth decline in old-growth forests. The new problems emphasize the hierarchy of the system and interscale interactions, suggesting that the hierarchical-modular approach could prove constructive.

2021 ◽  
Vol 13 (12) ◽  
pp. 2355
Author(s):  
Linglin Zeng ◽  
Yuchao Hu ◽  
Rui Wang ◽  
Xiang Zhang ◽  
Guozhang Peng ◽  
...  

Air temperature (Ta) is a required input in a wide range of applications, e.g., agriculture. Land Surface Temperature (LST) products from Moderate Resolution Imaging Spectroradiometer (MODIS) are widely used to estimate Ta. Previous studies of these products in Ta estimation, however, were generally applied in small areas and with a small number of meteorological stations. This study designed both temporal and spatial experiments to estimate 8-day and daily maximum and minimum Ta (Tmax and Tmin) on three spatial scales: climate zone, continental and global scales from 2009 to 2018, using the Random Forest (RF) method based on MODIS LST products and other auxiliary data. Factors contributing to the relation between LST and Ta were determined based on physical models and equations. Temporal and spatial experiments were defined by the rules of dividing the training and validation datasets for the RF method, in which the stations selected in the training dataset were all included or not in the validation dataset. The RF model was first trained and validated on each spatial scale, respectively. On a global scale, model accuracy with a determination coefficient (R2) > 0.96 and root mean square error (RMSE) < 1.96 °C and R2 > 0.95 and RMSE < 2.55 °C was achieved for 8-day and daily Ta estimations, respectively, in both temporal and spatial experiments. Then the model was trained and cross-validated on each spatial scale. The results showed that the data size and station distribution of the study area were the main factors influencing the model performance at different spatial scales. Finally, the spatial patterns of the model performance and variable importance were analyzed. Both daytime and nighttime LST had a significant contribution in the 8-day Tmax estimation on all the three spatial scales; while their contribution in daily Tmax estimation varied over different continents or climate zones. This study was expected to improve our understanding of Ta estimation in terms of accuracy variations and influencing variables on different spatial and temporal scales. The future work mainly includes identifying underlying mechanisms of estimation errors and the uncertainty sources of Ta estimation from a local to a global scale.


2018 ◽  
Author(s):  
F. Reyes ◽  
B. Pallas ◽  
C. Pradal ◽  
F. Vaggi ◽  
D. Zanotelli ◽  
...  

ABSTRACTBackground and aimsCarbon allocation in plants is usually represented at a specific spatial scale, peculiar to each model. This makes the results obtained by different models, and the impact of their scale of representation, difficult to compare. In this work we developed a Multi Scale Carbon Allocation model (MuSCA) that can be applied at different, user-defined, topological scales of a plant, and used to assess the impact of each spatial scale on simulated results and computation time.MethodsModel multi-scale consistency and behavior were tested by applications on three realistic apple tree structures. Carbon allocation was computed at five spatial scales, spanning from the metamer (the finest scale, used as a reference) up to 1st order branches, and for different values of a sap friction coefficient. Fruit dry mass increments were compared across spatial scales and with field data.Key ResultsThe model showed physiological coherence in representing competition for carbon assimilates. Results from intermediate values of the friction parameter best fitted the field data. For these, fruit growth simulated at the metamer scale (considered as a reference) differed from about 1% at growth unit scale up to 35% at first order branch scale. Generally, the coarser the spatial scale the more fruit growth diverged from the reference and the lower the obtained within-tree fruit growth variability. Coherence in the carbon allocated across scales was also differently impacted, depending on the tree structure considered. Decreasing the topological resolution reduced computation time up to four orders of magnitude.ConclusionsMuSCA revealed that the topological scale has a major influence on the simulation of carbon allocation, suggesting that this factor should be carefully evaluated when using different carbon allocation models or comparing their results. Trades-off between computation time and prediction accuracy can be evaluated by changing topological scales.


2014 ◽  
Author(s):  
C.J.. J. Segnini ◽  
M.. Rashwan ◽  
M.J.. J. Hernandez ◽  
J. A. Rojas ◽  
M.A.. A. Infante

Abstract This paper presents a methodology for the probabilistic analysis of an infill or step-out opportunity using numerical simulation. Sensitivity and uncertainty analyses for all involved parameters were evaluated through different experimental design techniques. Subsequently, a proxy model was established to reproduce the numerical model performance. Finally, three appropriate solutions were selected from a large population of realizations corresponding to probabilistic percentiles (90%, 50%, and 10% certainty that the specified volume will be recovered). This proposed methodology helped the asset team to evaluate the well candidates more precisely, confidently, and in less time than the current standard methodology. More knowledge about the variables and their effects on overall outcomes was also gained, which helped the team make more-informed decisions. The workflow used the same numerical modeling software, incorporating and facilitating the changes of both static and dynamic properties simultaneously. A case study from Teak field, on the east coast of Trinidad, illustrates the applicability of the methodology and compares its results to those obtained using the standard workflow for the asset. The methodology is one of the latest developments in reservoir simulation, and it has not yet been incorporated into the operator's common practices and procedures for exploitation of the TSP fields.


Ocean Science ◽  
2015 ◽  
Vol 11 (6) ◽  
pp. 879-896 ◽  
Author(s):  
M. Haller ◽  
F. Janssen ◽  
J. Siddorn ◽  
W. Petersen ◽  
S. Dick

Abstract. For understanding and forecasting of hydrodynamics in coastal regions, numerical models have served as an important tool for many years. In order to assess the model performance, we compared simulations to observational data of water temperature and salinity. Observations were available from FerryBox transects in the southern North Sea and, additionally, from a fixed platform of the MARNET network. More detailed analyses have been made at three different stations, located off the English eastern coast, at the Oyster Ground and in the German Bight. FerryBoxes installed on ships of opportunity (SoO) provide high-frequency surface measurements along selected tracks on a regular basis. The results of two operational hydrodynamic models have been evaluated for two different time periods: BSHcmod v4 (January 2009 to April 2012) and FOAM AMM7 NEMO (April 2011 to April 2012). While they adequately simulate temperature, both models underestimate salinity, especially near the coast in the southern North Sea. Statistical errors differ between the two models and between the measured parameters. The root mean square error (RMSE) of water temperatures amounts to 0.72 °C (BSHcmod v4) and 0.44 °C (AMM7), while for salinity the performance of BSHcmod is slightly better (0.68 compared to 1.1). The study results reveal weaknesses in both models, in terms of variability, absolute levels and limited spatial resolution. Simulation of the transition zone between the coasts and the open sea is still a demanding task for operational modelling. Thus, FerryBox data, combined with other observations with differing temporal and spatial scales, can serve as an invaluable tool not only for model evaluation, but also for model optimization by assimilation of such high-frequency observations.


2018 ◽  
Vol 10 (12) ◽  
pp. 1972 ◽  
Author(s):  
Katarzyna Zielewska-Büttner ◽  
Marco Heurich ◽  
Jörg Müller ◽  
Veronika Braunisch

Forest biodiversity conservation requires precise, area-wide information on the abundance and distribution of key habitat structures at multiple spatial scales. We combined airborne laser scanning (ALS) data with color-infrared (CIR) aerial imagery for identifying individual tree characteristics and quantifying multi-scale habitat requirements using the example of the three-toed woodpecker (Picoides tridactylus) (TTW) in the Bavarian Forest National Park (Germany). This bird, a keystone species of boreal and mountainous forests, is highly reliant on bark beetles dwelling in dead or dying trees. While previous studies showed a positive relationship between the TTW presence and the amount of deadwood as a limiting resource, we hypothesized a unimodal response with a negative effect of very high deadwood amounts and tested for effects of substrate quality. Based on 104 woodpecker presence or absence locations, habitat selection was modelled at four spatial scales reflecting different woodpecker home range sizes. The abundance of standing dead trees was the most important predictor, with an increase in the probability of TTW occurrence up to a threshold of 44–50 dead trees per hectare, followed by a decrease in the probability of occurrence. A positive relationship with the deadwood crown size indicated the importance of fresh deadwood. Remote sensing data allowed both an area-wide prediction of species occurrence and the derivation of ecological threshold values for deadwood quality and quantity for more informed conservation management.


Author(s):  
Nils Henriksson ◽  
Oskar Franklin ◽  
Lasse Tarvainen ◽  
John Marshall ◽  
Judith Lundberg-Felten ◽  
...  

The mycorrhizal symbiosis is ubiquitous in boreal forests. Trees and plants provide their fungal partners with photosynthetic carbon in exchange for soil nutrients like nitrogen, which is critical to the growth and survival of the plants. But plant carbon allocation to mycorrhizal symbionts can also fuel nitrogen immobilization, hampering tree growth. Here we present results from field and greenhouse experiments combined with mathematical modelling, showing that mycorrhizal fungi can be simultaneously mutualistic to an individual tree and parasitic to the networked community of trees. Mycorrhizal networks connect multiple plants and fungi, and we show that each tree gains additional nitrogen at the expense of its neighbors by supplying more carbon to the fungi. But this additional carbon supply eventually aggravates nitrogen immobilization in the shared fungal biomass. Individual trees may thus independently benefit from increasing their carbon investment to mycorrhiza, while causing a decline in nitrogen availability for the whole plant community. We illustrate the evolutionary underpinnings of this situation by drawing on the analogous the tragedy of the commons, and explain how rising atmospheric CO2 may lead to greater nitrogen immobilization in the future.


2010 ◽  
Vol 11 (5) ◽  
pp. 1191-1198 ◽  
Author(s):  
Bong-Chul Seo ◽  
Witold F. Krajewski

Abstract This study explores the scale effects of radar rainfall accumulation fields generated using the new super-resolution level II radar reflectivity data acquired by the Next Generation Weather Radar (NEXRAD) network of the Weather Surveillance Radar-1988 Doppler (WSR-88D) weather radars. Eleven months (May 2008–August 2009, exclusive of winter months) of high-density rain gauge network data are used to describe the uncertainty structure of radar rainfall and rain gauge representativeness with respect to five spatial scales (0.5, 1, 2, 4, and 8 km). While both uncertainties of gauge representativeness and radar rainfall show simple scaling behavior, the uncertainty of radar rainfall is characterized by an almost 3 times greater standard error at higher temporal and spatial resolutions (15 min and 0.5 km) than at lower resolutions (1 h and 8 km). These results may have implications for error propagation through distributed hydrologic models that require high-resolution rainfall input. Another interesting result of the study is that uncertainty obtained by averaging rainfall products produced from the super-resolution reflectivity data is slightly lower at smaller scales than the uncertainty of the corresponding resolution products produced using averaged (recombined) reflectivity data.


2020 ◽  
Vol 24 (5) ◽  
pp. 2711-2729 ◽  
Author(s):  
Joseph L. Gutenson ◽  
Ahmad A. Tavakoly ◽  
Mark D. Wahl ◽  
Michael L. Follum

Abstract. Large-scale hydrologic forecasts should account for attenuation through lakes and reservoirs when flow regulation is present. Globally generalized methods for approximating outflow are required but must contend with operational complexity and a dearth of information on dam characteristics at global spatial scales. There is currently no consensus on the best approach for approximating reservoir release rates in large spatial scale hydrologic forecasting, particularly at diurnal time steps. This research compares two parsimonious reservoir routing methods at daily steps: Döll et al. (2003) and Hanasaki et al. (2006). These reservoir routing methods have been previously implemented in large-scale hydrologic modeling applications and have been typically evaluated seasonally. These routing methods are compared across 60 reservoirs operated by the U.S. Army Corps of Engineers. The authors vary empirical coefficients for both reservoir routing methods as part of a sensitivity analysis. The method proposed by Döll et al. (2003) outperformed that presented by Hanasaki et al. (2006) at a daily time step and improved model skill over most run-of-the-river conditions. The temporal resolution of the model influences model performances. The optimal model coefficients varied across the reservoirs in this study and model performance fluctuates between wet years and dry years, and for different configurations such as dams in series. Overall, the method proposed by Döll et al. (2003) could enhance large-scale hydrologic forecasting, but can be subject to instability under certain conditions.


2020 ◽  
Vol 60 (4) ◽  
pp. 999-1031
Author(s):  
Martin Lind ◽  
Adrian Muntean ◽  
Omar Richardson

AbstractIn this paper, we study the numerical approximation of a coupled system of elliptic–parabolic equations posed on two separated spatial scales. The model equations describe the interplay between macroscopic and microscopic pressures in an unsaturated heterogeneous medium with distributed microstructures as they often arise in modeling reactive flow in cementitious-based materials. Besides ensuring the well-posedness of our two-scale model, we design two-scale convergent numerical approximations and prove a priori error estimates for the semidiscrete case. We complement our analysis with simulation results illustrating the expected behaviour of the system.


1976 ◽  
Vol 1 (15) ◽  
pp. 156 ◽  
Author(s):  
J. Richard Weggel

In the early 1950's the Corps of Engineers' Jacksonville District initiated a series of laboratory tests to investigate the overtopping of proposed levee sections for Lake Okeechobee, Florida. For economic reasons, the alternative to build levees with crest elevations that were at times below the limit of wave runup was investigated and the quantities of water carried over the structures for various freeboard allowances, structure slopes and wave conditions determined. The initial tests were conducted at the Waterways Experiment Station (WES) in Vieksburg, Mississippi for the Jacksonville District at what was taken to be a 1 to 30 model scale. Model wave heights varied from 1+.05 cm to 12.2 cm (0.133 to 0.^0 ft). In order to expand the range of test conditions investigated, the Beach Erosion Board, currently the Coastal Engineering Research Center (CERC), commissioned an expanded series of tests that considered the overtopping of riprap faced, curved and stepped seawalls as well as the overtopping of "smooth" slopes. These tests, also conducted at WES, were considered to be at a 1 to 17 scale with model wave heights ranging from 5-36 cm to 21.5 cm (0.176 to O.706 ft). A number of tests were subsequently conducted in CERC's large wave tank to determine the influence scale effects might have on overtopping. These tests are referred to as 1 to 2 1/2 scale tests. The model wave heights investigated ranged from U8.8 cm to 11*0.2 cm. (1.60 to h.6o ft).


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