Process-based Ecophysiological Model Research Articles

Within and between population phenotypic variation in growth vigor and sensitivity to drought stress in five temperate tree species

Within-population variation in individual tree growth and response to climate has an impact on forest dynamics, resilience and adaptation to environmental change.Combining dendrochronological analyses with a process-based ecophysiological model simulating drought stress at the stand scale, we studied the phenotypic variation of two growth-related traits within 22 pure stands of five contrasted tree species sampled in the RENECOFOR network over a wide range of ecological conditions. First, we computed the annual stress level from soil, climate and stand inventory data. Second, we computed individual sensitivity as the quantitative growth response to drought stress level and individual vigor as the capacity to grow in favorable years relative to an average stand-level growth model. We analyzed within-population variation and covariation of individual vigor and sensitivity, their temporal changes during stand development, as well as the effect of environmental conditions on population-level means, variances and correlation.Our results show that within-population variances in sensitivity and vigor exceed the between-population variances for all species. The populations located in more stressful environments, i.e., low summer precipitation and extractable soil water, showed lower mean and variance of sensitivity, suggesting possible multiscale adaptation at the population level and within populations. None of the environmental factors considered had an effect on the average population vigor or on the within-population variance of vigor. We found a general positive correlation between individual growth sensitivity and vigor in 17 out of 22 populations, potentially revealing a growth performance trade-off. The correlation was more pronounced in low extractable soil water environments, which may be related to a need for stressful conditions to reveal the trade-off or be the consequence of adaptive processes, i.e., acclimation and selection.If high within-population stand phenotypic variation in growth traits contributes to the resilience and adaptive capacity of forests to climate change, a trade-off could represent a constraint on selection. We provide genetic and environmental arguments supporting the hypothesis of a trade-off, then we highlight the importance of integrating it into the management process, especially during selective thinning, to avoid indirectly increasing population sensitivity by selecting the most vigorous trees.

Tree Mortality Risks Under Climate Change in Europe: Assessment of Silviculture Practices and Genetic Conservation Networks

General Context: Climate change can positively or negatively affect abiotic and biotic drivers of tree mortality. Process-based models integrating these climatic effects are only seldom used at species distribution scale.Objective: The main objective of this study was to investigate the multi-causal mortality risk of five major European forest tree species across their distribution range from an ecophysiological perspective, to quantify the impact of forest management practices on this risk and to identify threats on the genetic conservation network.Methods: We used the process-based ecophysiological model CASTANEA to simulate the mortality risk of Fagus sylvatica, Quercus petraea, Pinus sylvestris, Pinus pinaster, and Picea abies under current and future climate conditions, while considering local silviculture practices. The mortality risk was assessed by a composite risk index (CRIM) integrating the risks of carbon starvation, hydraulic failure and frost damage. We took into account extreme climatic events with the CRIMmax, computed as the maximum annual value of the CRIM.Results: The physiological processes' contributions to CRIM differed among species: it was mainly driven by hydraulic failure for P. sylvestris and Q. petraea, by frost damage for P. abies, by carbon starvation for P. pinaster, and by a combination of hydraulic failure and frost damage for F. sylvatica. Under future climate, projections showed an increase of CRIM for P. pinaster but a decrease for P. abies, Q. petraea, and F. sylvatica, and little variation for P. sylvestris. Under the harshest future climatic scenario, forest management decreased the mean CRIM of P. sylvestris, increased it for P. abies and P. pinaster and had no major impact for the two broadleaved species. By the year 2100, 38–90% of the European network of gene conservation units are at extinction risk (CRIMmax=1), depending on the species.Conclusions: Using a process-based ecophysiological model allowed us to disentangle the multiple drivers of tree mortality under current and future climates. Taking into account the positive effect of increased CO2 on fertilization and water use efficiency, average mortality risk may increase or decrease in the future depending on species and sites. However, under extreme climatic events, our process-based projections are as pessimistic as those obtained using bioclimatic niche models.

Evaluating short-season soybean management adaptations for cover crop rotations with a crop simulation model

Cover crop fall biomass production and thus successful provisioning of ecosystem services depend on the previous cash crop harvest date. We used a process-based eco-physiological model to investigate the potential of short-season soybean maturity groups (MG) to lengthen the cover crop growing window while achieving yields similar to full-season MG cultivars. Cultivar coefficients for MG 0–4 cultivars for the DSSAT – CROPGRO model were calibrated with data from 13 site-years (in 2017 and 2018) across Kentucky, Nebraska, and Ohio. The model was efficient in predicting differences in soybean harvest maturity date (R8; Model efficiency [ME] = 0.61; Root Mean Square Error [RMSE] = 7.4 days) and yield (ME = 0.38; RMSE = 0.452 Mg ha−1) for an independent set of soybean cultivars in the same site-years. Thereafter, a multi-factor sensitivity analysis across 30-yr of historical weather data was conducted. Simulated results showed that MG 3 cultivars would not reduce yield and would advance cover crop establishment compared to MG 4 cultivars. For planting dates in May and conditions of no water stress, adaptating cultivar choices to MG lower than 3 would reduce yields by 55 to 567 kg ha−1 per unit decrease in MG. Under water stress or when planting date was delayed, adapting cultivar choices to MG lower than 3 had a less detrimental effect on yield. Overall, switching to earlier cutlivar maturities would advance soybean harvest by 7–11 days MG−1 (May 15 planting date) or 1–7 days MG-1 (Jul 1 planting date), and lengthen the cover crop growing season in the fall by 95–198 °C day MG−1 (May 15 planting date) or 19−104 °C day MG−1 (Jul 1 planting date). The greater potential to increase the cover crop growing season with short-season MG cultivars was also associated with a greater soybean yield penalty in the warmest locations in our study. Using crop coefficients calibrated by MG rather than by specific cultivar provided a way to increase model application within a study region to study cultivar maturity adaptations for crop rotations while reducing the need for calibration. Further studies that analyze the tradeoffs from soybean cultivar adaptation on C, N, and water balance, and other indirect ecosystem services from cover crops are necessary.

Modelling carbon and water balance of Eucalyptus plantations at regional scale: Effect of climate, soil and genotypes

Carbon and water budgets of forest plantations are spatially and temporally variable and hardly empirically predictable. We applied G’DAY, a process-based ecophysiological model, to simulate carbon and water budgets and stem biomass production of Eucalyptus plantations in São Paulo State, Brazil. Our main objective was to assess the drivers of spatial variability in plantation production at regional scale. We followed a multi-site calibration approach: the model was first parameterized using a detailed experimental dataset. Then a subset of the parameters were re-calibrated on two independent experimental datasets. An additional genotype-specific calibration of a subset of parameters was performed. Model predictions of key carbon-related variables (e.g., gross primary production, leaf area index and stem biomass) and key water-related variables (e.g., plant available water and evapotranspiration) agreed closely with measurements. Application of the model across ca. 27,500 ha of forests planted with different genotypes of Eucalyptus indicated that the model was able to capture 89% of stem biomass variability measured at different ages. Several factors controlling Eucalyptus production variability in time and space were grouped in three categories: soil, climate, and the planted genotype. Modelling analysis showed that calibrating the model for genotypic differences was critical for stem biomass prediction at regional scale, but that taking into account climate and soil variability significantly improved the results. We conclude that application of process-based models at regional scale can be used for accurate predictions of Eucalyptus production, provided that an accurate calibration of the model for key genotype-specific parameters is conducted.

The trade-offs between milk production and soil organic carbon storage in dairy systems under different management and environmental factors

A possible agricultural climate change mitigation option is to increase the amount of soil organic carbon (SOC). Conversely, some factors might lead to inadvertent losses of SOC. Here, we explore the effect of various management options and environmental changes on SOC storage and milk production of dairy pastures in New Zealand. We used CenW 4.1, a process-based ecophysiological model, to run a range of scenarios to assess the effects of changes in management options, plant properties and environmental factors on SOC and milk production. We tested the model by using 2years of observations of the exchanges of water and CO2 measured with an eddy covariance system on a dairy farm in New Zealand's Waikato region. We obtained excellent agreement between the model and observations, especially for evapotranspiration and net photosynthesis.For the scenario analysis, we found that SOC could be increased through supplying supplemental feed, increasing fertiliser application, or increasing water availability through irrigation on very dry sites, but SOC decreased again for larger increases in water availability. Soil warming strongly reduced SOC. For other changes in key properties, such as changes in soil water-holding capacity and plant root:shoot ratios, SOC changes were often negatively correlated with changes in milk production.The work showed that changes in SOC were determined by the complex interplay between (1) changes in net primary production; (2) the carbon fraction taken off-site through grazing; (3) carbon allocation within the system between labile and stabilised SOC; and (4) changes in SOC decomposition rates. There is a particularly important trade-off between carbon either being removed by grazing or remaining on site and available for SOC formation. Changes in SOC cannot be fully understood unless all four factors are considered together in an overall assessment.

Retrieval of seasonal Rubisco-limited photosynthetic capacity at global FLUXNET sites from hyperspectral satellite remote sensing: Impact on carbon modelling

Process-based ecophysiological models, which simulate carbon exchange at the land-surface, are powerful and indispensable tools for understanding how vegetation behaves under present and future climate. However, these models are necessarily complex, containing numerous biophysical parameters which are often poorly defined. The current study develops a novel retrieval of Rubisco-limited top-of-canopy photosynthetic capacity (i.e. maximum carboxylation rate, Vcmax25,toc), which is one of the most critical parameters in the calculation of Gross Primary Productivity (GPP). The retrieval combines standard remote sensing satellite products of Leaf Area Index (LAI), from the Moderate Resolution Imaging Spectroradiometer (MODIS), with a hyperspectral index of total canopy chlorophyll concentration from the MEdium Resolution Imaging Spectrometer (MERIS). Monthly values of Vcmax25,toc are determined over a 9 year period for 296 global FLUXNET sites (catalogue made available online) and 8 Plant Functional Types (PFTs). PFT averages agree favourably with compilations of field-based measurements. However, according to a Monte Carlo analysis, our method is still currently subject to large systematic uncertainties (25–30%), much of which arises from the empirical relationship between maximum electron transport and leaf chlorophyll content. For all 8 PFTs, except tropical broadleaf forest, Vcmax25,toc varies considerably across the season (generally a factor of 1.6). Similarly, variability between sites of the same PFT is significant (interquartile range is 40% of the median). This suggests an important additional role for satellites in the spatial and temporal parameterisation of carbon models. Inclusion of this temporal and spatial variability in a process-based ecophysiological model produces, respectively, an impact of 11% and 12% on simulated GPP.

Past-century decline in forest regeneration potential across a latitudinal and elevational gradient in Canada

The regeneration niche of trees greatly narrows the fundamental niche and is sensitive to climatic change. Development from seed and phenology are regulated by biological and environmental controls, shaping forest successional pathways. We hypothesized that recent climate change is reducing regeneration suitability in northern forests. We used a process-based ecophysiological model to examine changes in forest regeneration conditions across an elevational and latitudinal gradient in Alberta, Canada from 1923 to 2012. We compared these results to a recent empirical study in the region to infer the recent drivers of regeneration change in northern forests. Our results suggest that these forests are experiencing climatically driven declines in conditions suitable for regeneration. Contrary to previous findings indicating poorer current conditions in low elevation forests, we found more stable regeneration potential there, attributable to a relative abundance of soil moisture. Rocky soils resulted in modeled losses of soil moisture at higher elevations, potentially preventing upslope migrations of species despite warming. We identify potential mechanisms driving unexpected tree regeneration patterns described in previous studies. Our simulations suggest a delayed response of forest regeneration to warming throughout the past 90 years.

Time variable hydraulic parameters improve the performance of a mechanistic stand transpiration model. A case study of Mediterranean Scots pine sap flow data assimilation

Tree transpiration is regulated by short-term physiological adjustments and long-term shifts in hydraulic architecture in response to fluctuating evaporative demand and water supply. Despite the tight interdependence of plant water loss and carbon uptake and its crucial implications for plant growth and survival under drought conditions, the underlying mechanisms remain incompletely represented in most state-of-the-art mechanistic models. Important process information is resolved in tree transpiration (sap flow) data, which are the measurable outcome of water transport through the soil-plant-atmosphere continuum under variable environmental conditions. Here, we assimilated sap flow data measured in two Scots pine stands from climatically contrasting sites – one of which experiencing a strong drought during the study period – in NE Spain into a process-based ecophysiological model (SPA) using the Ensemble Kalman Filter (EnKF) in order to: (1) distinguish differences in hydraulic characteristics between sites and between healthy and defoliated individuals within a site; (2) identify possible structural model deficiencies, particularly regarding temporal changes in plant hydraulic conductance which the model assumes constant; and (3) derive implications for gross photosynthesis and carbon cycling. In terms of stomatal control, the assimilation of sap flow data into SPA showed a more conservative water use under dry conditions. Time-varying plant conductivity substantially improved model performance under severe drought, while seasonally varying capacitance and stomatal efficiency only resulted in marginal improvements. Not accounting for this seasonal variability would translate into a 30–60% overestimation of modelled GPP during drought. Our results suggest that an explicit representation of mechanisms leading to temporal changes in hydraulic conductivity (i.e., xylem embolism) is required for models to reproduce tree functioning under extreme drought.

Comparison of an energy systems mini-model to a process-based eco-physiological model for simulating forest growth

The mini-modeling technique that H.T. Odum developed in conjunction with his approach to ecological and energy-based systems principles provides a relatively simple, yet powerful way for simulating ecosystem processes at many scales. However, its simplicity presents limitations that should be articulated. This paper developed a mini-model that simulated the biomass growth and soil organic matter accumulation of three subtropical forest plantations typical of South China to compare its simulated results with field observations and the simulated results of a widely applied process-based model of forest ecosystems (Biome-BGC model). The mini-model's simulated results were close to both the observed values and those of the Biome-BGC model over a 23-year record of early growth (R2>0.90 for biomass). This indicated that when the key ecosystem components, processes and driving forces were fully considered, the mini-model technique could closely emulate the ecosystem processes using only a few equations. Thus, developing a mini-model from ecological and energetic systems principles is a powerful tool for testing and expanding upon general energy principles applicable to many systems and offers the unique opportunity to perform dynamic emergy accounting. Developing a mini-model, on the other hand, can benefit from exploring a complex process-based eco-physiological model, especially to understand ecosystem structure and processes. Compared with process-based ecosystem models, the mini-model does not include specific eco-physiological mechanisms of material production, but simply simulates the ecosystem processes based on the main flows of energy. However, investigation of energy interactions in the mini-model and sensitivity analysis showed that the parameters of the mini-model need to be set within their confidence intervals to avoid errors and, like most simulations, should be validated with field observations before applying the model further. Energy systems mini-models provide the capability to simulate key ecosystem processes and the dynamics of emergy, which can prove useful for evaluating the temporal change in the accumulated value of ecosystems such as forests for environmental accounting purposes.