Ecophysiological Model Research Articles

Hot, dry, and salty: The present and future of an Extremophile model lizard from Argentina

Global warming poses a threat to lizard populations by raising ambient temperatures above historical norms and reducing thermoregulation opportunities. Whereas the reptile fauna of desert systems is relatively well studied, the lizard fauna of saline environments has not received much attention and—to our knowledge—thermal ecology and the effects of global warming on lizards from saline environments have not been yet addressed. This pioneer study investigates the thermal ecology, locomotor performance and potential effects of climate warming on Liolaemus ditadai, a lizard endemic to one of the largest salt flats on Earth. We sampled L. ditadai using traps and active searches along its known distribution, as well as in other areas within Salinas Grandes and Salinas de Ambargasta, where the species had not been previously recorded. Using ensemble models (GAM, MARS, RandomForest), we modeled climatically suitable habitats for L. ditadai in the present and under a pessimistic future scenario (SSP585, 2070). L. ditadai emerges as an efficient thermoregulator, tolerating temperatures near its upper thermal limits. Our ecophysiological model suggests that available activity hours predict its distribution, and the projected temperature increase due to global climate change should minimally impact its persistence or may even have a positive effect on suitable thermal habitat. However, this theoretical increase in habitat could be linked to the distribution of halophilous scrub in the future. Our surveys reveal widespread distribution along the borders of Salinas Grandes and Salinas de Ambargasta, suggesting a potential presence along the entire border of both salt plains wherever halophytic vegetation exists. Optimistic model results, extended distribution, and no evidence of flood-related adverse effects offer insights into assessing the conservation status of L. ditadai, making it and the Salinas Grandes system suitable models for studying lizard ecophysiology in largely unknown saline environments.

Estimating growth using an ecophysiological and scope for growth model for the mussel Perna perna grown under suspended culture in Santa Catarina, Brazil

We present a dynamic simulation ecophysiological model for an important aquaculture mussel, Perna perna, grown under suspended culture in Santa Catarina, Brazil. The ecophysiological model was divided in four sectors; driving variables, feeding, energy reserve, and growth. This generated descriptions and explanations of the functions controlling feeding and metabolic responses to changing food availability and seawater temperature. The driving variables sector included time-series of seston variables likely to influence food and energy acquisition in mussels. It included relationships among seston variables to estimate the energy content of phytoplankton, the main component of mussel diet. The feeding sector described mussel suspension-feeding behavior measured using natural seston. Rates of filtration, rejection, ingestion, and absorption were directly related to the quantity and quality of available food. In the energy reserve sector, absorbed matter was transformed to absorbed energy using estimates of energy content of food provided in the driving variables sector. After accounting for the maintenance requirements of the mussels (heat loss and excretion), surplus energy, or the scope for growth, was directed to the growth sector. The growth sector included byssus, organic shell, and soft tissue production based on energy partitioning estimated from monthly measurements of somatic and reproductive tissue and shell growth. The model successfully predicted mussel growth during the study and provided estimates of the response to food acquisition, energy expenditure and allocation to growth. This was the first attempt to model the ecophysiology of this fast growing sub-tropical mussel. Given the capacity of this ecophysiological model to estimate growth of mussels, it has significant economic and environmental value in estimating carrying capacity to support sustainable management of shellfish farming in Brazil.

Methods for Functional Physiological Phenotyping and High-Order Data Quantification.

This chapter presents the application of Plantarray, a high-throughput platform commercially available for noninvasive monitoring of plant functional physiology phenotyping (FPP). The platform continuously measures water flux in the soil-plant-atmosphere for each plant in dynamic environments. To better interpret the massive phenotypic data acquired with FPP, several quantitative analysis methods were demonstrated for various types of data. Simple mathematical models were utilized to fit characteristic parameters of plant transpiration response to drought stress. Additionally, ecophysiological models were employed to quantify the sensitivity of transpiration to radiation and vapor pressure deficit (VPD) as component traits and predict more complex higher-order traits. The established protocols provide a tangible tool for integrating FPP and model analysis to address complex traits.

Climate change and collapsing thermal niches of desert reptiles and amphibians: Assisted migration and acclimation rescue from extirpation

Recent climate change should result in expansion of species to northern or high elevation range margins, and contraction at southern and low elevation margins in the northern hemisphere, because of local extirpations or range shifts or both. We combined museum occurrence records from both the continental U.S. and Mexico with a new eco-physiological model of extinction developed for lizard families of the world to predict the distributions of 30 desert-endemic reptile and amphibian species under climate change scenarios. The model predicts that 38 % of local populations will go extinct in the next 50 years, across all 30 species. However, extinctions may be attenuated in forested sites and by the presence of montane environments in contemporary ranges. Of the 30 species, three were at very high risk of extinction as a result of their thermal limits being exceeded, which illustrates the predictive value of ecophysiological modeling approaches for conservation studies. In tandem with global strategies of limiting CO2 emissions, we propose urgent regional management strategies for existing and new reserves that are targeted at three species: Barred Tiger Salamander (Ambystomatidae: Ambystoma mavortium stebbinsi), Desert Short-horned Lizard (Phrynosomatidae: Phrynosoma ornatissimum), and Morafka's Desert Tortoise (Testudinidae: Gopherus morafkai), which face a high risk of extinction by 2070. These strategies focus on assisted migration and preservation within climatic refugia, such as high-elevation and forested habitats. We forecast where new reserves should be established by merging our model of extinction risk with gap analysis. We also highlight that acclimation (i.e., phenotypic plasticity) could ameliorate risk of extinction but is rarely included in ecophysiological models. We use Ambystoma salamanders to show how acclimation can be incorporated into such models of extinction risk.

Modeling functional relationships between morphogenetically active radiation and photosynthetic photon flux density in mango tree crown

Light is a key factor in plant ecophysiological modeling because of its crucial effects on plant growth and development. However, solar light quantity and quality change with environmental factors such as sky condition and solar elevation. When passing through a tree crown, light is modified by its interaction with the phytoelements, leaves and axes. This leads to a variability of light quantity and quality within the crown, with consequences on light-related processes such as photosynthesis and photomorphogenesis. We evaluated the effects of positional (depth within the crown) and environmental (sky condition, solar elevation) factors on light quantity and quality within the crown of the tropical evergreen mango tree. Functional relationships were modeled between morphogenetically active radiation variables that describe light quality [narrowband red (Rn), narrowband far-red (FRn), the ratio ζ=Rn : FRn, and UVA-blue (UVA-BL)] and light quantity [photosynthetic photon flux density (PPFD) and relative transmitted PPFD (TrPPFD)]. Light quantity and quality varied within the mango tree crown in a wide range similar to that of a forest. This variability was structured by the depth within the crown as well as by sky condition and solar elevation. Linear relationships linked Rn, FRn and UVA-BL to PPFD, and non-linear relationships linked ζ to TrPPFD. These relationships were strong, accurate and unbiased. They were affected by positional and environmental factors. The results suggested that these relationships were shaped by the characteristics of incident solar light and/or by the interactions between light and phytoelements. Two consequences of interest emerged from this research: i) the modeled relationships allow to infer light quality, that is difficult and time-consuming to simulate, from light quantity modeling within a tree crown, and ii) sky condition and solar elevation should be considered to improve light modeling within a tree crown.

Disentangling the impact of photosynthesis and stomatal conductance on rising water-use efficiency at different altitudes on the Tibetan plateau

Tree intrinsic water-use efficiency (iWUE) has dramatically increased in recent decades in global forests. The rising iWUE can be a result of either enhanced photosynthesis rate (A), or decreased stomatal conductance (gs) or both. The underlying physiological mechanisms are still not well understood. Here, we investigated tree-ring isotopes δ13C and δ18O from two tree species in three altitudinal transects on the southeast Tibetan plateau. We found that the relationship between iWUE and ∆18Olw was negative at lower-altitude forests, whereas it was positive at the treeline, indicating that enhanced photosynthesis was the main driver of the increasing iWUE at the treeline, whereas reduction in stomatal conductance was the prime regulator at lower-altitude forests. Furthermore, vapor pressure deficit (VPD) and precipitation during the main growing season showed the highest and significant correlations with leaf water 18O (Δ18Olw) at lower-altitude forests, suggesting that gs was strongly controlled by moisture conditions in the growing season particularly in the lower-altitude forests. These findings shed light to a better understanding of the regulatory mechanism of iWUE changes under the background of rising atmospheric CO2 and climate change and serve to improve the reliability of ecophysiological modeling.

Potassium limitation of forest productivity – Part 1: A mechanistic model simulating the effects of potassium availability on canopy carbon and water fluxes in tropical eucalypt stands

Abstract. The extent of the potassium (K) limitation of forest productivity is probably more widespread than previously thought, and K limitation could influence the response of forests to future global changes. To understand the effects of K limitation on forest primary production, we have developed the first ecophysiological model simulating the K cycle and its interactions with the carbon (C) and water cycles. We focused on the limitation of the gross primary productivity (GPP) by K availability in tropical eucalypt plantations in Brazil. We used results from stand-scale fertilisation experiments as well as C flux measurements in two tropical eucalypt plantations to parameterise the model. The model was parameterised for fertilised conditions and then used to test for the effects of contrasting additions of K fertiliser. Simulations showed that K deficiency limits GPP by more than 50 % during a 6-year rotation, a value in agreement with estimations in K-limited eucalypt stands. Simulations showed a decrease of modelled canopy transpiration of around 50 % and a decrease in modelled water-use efficiency WUEGPP of 10 %. Through a sensitivity analysis, we used the model to identify the most critical processes to consider when studying K limitation of GPP. The inputs of K to the stands, such as the atmospheric deposition and weathering fluxes, and the regulation of the cycle of K within the ecosystem were critical for the response of the system to K deficiency. Litter leaching processes were of lower importance, since residence time of K in litter was low. The new forest K-cycle model developed in the present study includes multiple K processes interacting with the carbon and water cycles, and strong feedbacks on GPP were outlined. This is a first step in identifying the source or sink limitation of forest growth by K.

Nutrient extraction and ecosystem impact by suspended mussel mitigation cultures at two contrasting sites

Mussel mitigation culture is increasingly recognized as a tool to extract nutrients from eutrophic systems by harvesting mussel biomass and nutrients contained therein. The net effect of mussel production on the nutrient cycling in the ecosystem is, however, not straightforward due to the interaction with physical- and biogeochemical processes regulating ecosystem functioning. The aim of the present study was to evaluate the potential of using mussel culture as a tool to mitigate eutrophication at two contrasting sites: a semi-enclosed fjord and a coastal bay. We applied a 3D coupled hydrodynamic-biogeochemical-sediment model combined with a mussel eco-physiological model. The model was validated against monitoring data and research field data on mussel growth, sediment impacts, and particle depletion from a pilot mussel farm in the study area. Model scenarios with intensified mussel farming in the fjord and/or the bay were conducted. The results showed that mussel mitigation culture still has a high net N-extraction when including ecosystem effects, such as changes in biodeposition, nutrient retention, denitrification, and sediment nutrient fluxes in the model. Mussel farms located in the fjord were more effective in directly addressing excess nutrients and improving water quality due to the relative vicinity to primary nutrient sources (riparian) and physical characteristics of the fjord system. The results will be important to consider in other systems concerning site selection, development of bivalve aquaculture, and associated sampling strategies for monitoring the farming impacts.

Climate warming erodes tropical reef habitat through frequency and intensity of episodic hypoxia

Climate warming threatens marine life by increasing metabolic oxygen demand while decreasing oxygen availability. Tropical species living in warm, low oxygen environments may be most at risk, but their tolerances and exposures to these stressors remain poorly documented. We evaluated habitat restrictions for two brittle star species from Caribbean coral reefs by integrating field observations, laboratory experiments and an ecophysiological model. The absence of one species from the warmest reefs results from vital activity restrictions during episodic low oxygen extremes, even though average conditions are well within physiological tolerance limits. Over the past decade, warmer temperatures have been significantly correlated with a greater frequency and intensity of hypoxic events. Continued warming will progressively exclude hypoxia-tolerant species, even if average oxygen remains constant. A warming-driven increase in frequency or intensity of low oxygen extremes could similarly accelerate habitat loss across other marine ecosystems.

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.

Evaluating management and climatic scenarios on Eucalyptus plantations using a new ecophysiological model of water dynamics and wood production

Evaluating management and climatic scenarios on Eucalyptus plantations using a new ecophysiological model of water dynamics and wood production

Linking genetic markers with an eco-physiological model to pyramid favorable alleles and design wheat ideotypes.

Genetic markers can be linked with eco-physiological crop models to accurately predict genotype performance and individual markers' contributions in target environments, exploring interactions between genotype and environment. Here, wheat (Triticum aestivum L.) yield was dissected into seven traits corresponding to cultivar genetic coefficients in an eco-physiological model. Loci for these traits were discovered through the genome-wide association studies (GWAS). The cultivar genetic coefficients were derived from the loci using multiple linear regression or random forest, building a marker-based eco-physiological model. It is then applied to simulate wheat yields and design virtual ideotypes. The results indicated that the loci identified through GWAS explained 46-75% variations in cultivar genetic coefficients. Using the marker-based model, the normalized root mean square error (nRMSE) between the simulated yield and observed yield was 13.95% by multiple linear regression and 13.62% by random forest. The nRMSE between the simulated and observed maturity dates was 1.24% by multiple linear regression and 1.11% by random forest, respectively. Structural equation modelling indicated that variations in grain yield could be well explained by cultivar genetic coefficients and phenological data. In addition, 24 pleiotropic loci in this study were detected on 15 chromosomes. More significant loci were detected by the model-based dissection method than considering yield per se. Ideotypes were identified by higher yield and more favorable alleles of cultivar genetic traits. This study proposes a genotype-to-phenotype approach and demonstrates novel ideas and tools to support the effective breeding of new cultivars with high yield through pyramiding favorable alleles and designing crop ideotypes. This article is protected by copyright. All rights reserved.

A research agenda for nonvascular photoautotrophs under climate change.

Nonvascular photoautotrophs (NVP), including bryophytes, lichens, terrestrial algae, and cyanobacteria, are increasingly recognized as being essential to ecosystem functioning in many regions of the world. Current research suggests that climate change may pose a substantial threat to NVP, but the extent to which this will affect the associated ecosystem functions and services is highly uncertain. Here, we propose a research agenda to address this urgent question, focusing on physiological and ecological processes that link NVP to ecosystem functions while also taking into account the substantial taxonomic diversity across multiple ecosystem types. Accordingly, we developed a new categorization scheme, based on microclimatic gradients, which simplifies the high physiological and morphological diversity of NVP and world-wide distribution with respect to several broad habitat types. We found that habitat-specific ecosystem functions of NVP will likely be substantially affected by climate change, and more quantitative process understanding is required on (1) potential for acclimation, (2) response to elevated CO2 , (3) role of the microbiome, and (4) feedback to (micro)climate. We suggest an integrative approach of innovative, multimethod laboratory and field experiments and ecophysiological modelling, for which sustained scientific collaboration on NVP research will be essential.

Testing machine learning algorithms on a binary classification phenological model

AbstractAimPhenological models have become a vital tool for predicting future phenological responses to global climate change. Recently, machine learning (ML) has been used successfully to develop phenological models based on ground observations. However, fitting an observation series that has been observed for only a few years (or even a decade) can easily lead to overfitting, and it is still a great challenge to predict future phenology accurately based on a short observation series. Here, based on historical ground phenological observations, we construct an ML‐based binary classification phenological model that can be applied to temperate trees.InnovationWe thoroughly describe the construction process of a species‐specific ML‐based binary classification phenological model that is suitable for phenological predictions in both spring and autumn. Through experiments, we evaluate 18 commonly used ML classification algorithms and the effects of two parameters on the prediction performance of the model. Finally, we compare the performance between the binary classification model and six widely used ecophysiological models for accuracy of spring phenological prediction.Main conclusionsThe median root mean square error (RMSE) of the binary classification model for the first flowering date (93 observation series) was only 2.99 days, which proves that it is a good method of phenological prediction for temperate trees. This model can effectively overcome the insufficient sample size of ground observations for specific species and provide new insights of phenological predictions for tropical and subtropical trees. The comparison of different ML algorithms showed that the median root mean square errors of the six algorithms were <3.5 days, and lower than those of six ecophysiological models (>3.7 days) in prediction of spring phenology. In addition, this model can help us to infer plant physiological mechanisms and drivers of phenological change and provide more accurate predictions of plant phenological responses to climate change.

Examination of the effects of toxicity and nutrition on a two-prey one-predator system with a metabolomics-inspired model

Mercury (Hg) sequestration by phytoplankton results in intracellular concentrations that are multiple times greater than ambient water levels, and therefore the consumption of contaminated phytoplankton by herbivorous zooplankton, such as Daphnia, and their inefficient excretion of methylmercury (MeHg) can mediate the transfer to higher trophic levels. Employing a modified version of a metabolomics-inspired Daphnia ecophysiological model, the present study introduces two prey species to a simple Lotka-Volterra predator-prey system in order to shed light on the implications for the integrity of zooplankton assemblages, when experiencing multiple prey items of different toxicity and nutritional quality. We also examine the capacity of adaptive strategies of the predator (homeostatic rigidity, energetic investments to cope with toxicity) to shape predator-prey interactions. Our analysis suggests that the degree of nutritional quality of the prey items is a predominant driver of the predator-prey relationships, shifting from prey- to predator-dominated food webs with increasing nutritional quality. Increasing prey nutritional content leads to the emergence of oscillatory behaviour, which can be further modulated by the growth rates and degree of toxicity of different prey species. Severe exposure to contamination could lead to a decline of the predator biomass with faster growth rates of low nutritional quality prey, even though the increase of its MeHg somatic quota is only modest. In stark contrast, when a prey assemblage of superior nutritional quality prevails in an environment of elevated toxicity, faster prey growth rates are conducive to higher predator biomass levels, albeit its distinctly higher internal contaminant content. Owing to the heightened somatic growth dilution, the ingestion of carbon and nutritional metabolites is significantly higher relative to the MeHg intake rates, which leads to faster net growth of the predator and thus reinforces the benefits brought about by the nutritional value of their diet. Our results suggest that the homeostatic rigidity of the predator can assist in coping with toxic exposure. With a tighter range between the minimum and optimum somatic quotas, the predator population appears to be more resilient and its decline begins at higher levels of MeHg exposure. The predator-prey system displays a greater propensity for oscillatory behaviour, with their amplitude being driven by the interplay between the degree of saturation for nutritionally beneficial metabolites, and the energetic investments allotted to cope with toxicity and/or the excretion of excess metabolic by-products. We conclude by highlighting the prospect of our modelling work to guide new directions of research, to test a multitude of hypotheses pertaining to various ecophysiological facets of predator-prey systems, and extend its use to other contexts, such as the implications of toxin-producing algae for the predator physiology.

Tree-Ring Isotopic Records Suggest Seasonal Importance of Moisture Dynamics Over Glacial Valleys of the Central Himalaya

Accelerated glacier mass loss is primarily attributed to greenhouse-induced global warming. Land–climate interactions have increasingly been recognized as an important forcing at the regional-local scale, but the related effects on the Himalayan glaciers are less explored and thought to be an important factor regulating spatial heterogeneity. The aim of the present study is a multi-decadal approximation of glacier—hydroclimate interaction over the western region of the central Himalaya (WCH). Multi-species, highly coherent, tree-ring cellulose δ18O chronologies from three sites across the WCH were used to derive atmospheric humidity (Atmospheric Moisture Content: AMC) record of the last four centuries. Annual-scale AMC reconstruction implies a decreasing regional atmospheric moisture since the mid-19th century and a sharp decline in recent decades (1960s). Coherency analyses between regional AMC and glacier mass balance (GMB) indicate an abrupt phase-shift in the relationship after the 1960s within a common record of the last 273 years. To ascertain the cause of this phase-shift, annual AMC was disintegrated into seasonal-scale, utilizing ∼200 years of δ18O record of a deciduous tree species. Seasonal (winter: October–March; summer: April–September) AMC reconstructions and disaggregation results indicate higher sensitivity of regional ice-mass variability to winter moisture dynamics than summer.Winter season AMC reconstruction confirms a revival of winter westerlies-driven moisture influx in the region since the 1970 s. Meanwhile, the record for the summer season AMC indicates a gradual decline in moisture influx from the beginning of the 20th century. Interestingly, despite a prominent decline in Indian summer monsoon (ISM) precipitation after the mid-20th century, the summer season AMC—GMB relation remained stable. We hypothesize that decadal-scale greening, and consequently increased evapotranspiration and pre-monsoon precipitation might have been recycled through the summer season, to compensate for the ISM part of precipitation. However, isotope-enabled ecophysiological models and measurements would strengthen this hypothesis. In addition, high-resolution radiative forcing and long-term vegetation greening trends point towards a probable influence of valley greening on GMB. Our results indicate that attribution of ice mass to large-scale dynamics is likely to be modulated by local vegetation changes. This study contributes to the understanding of long-term hydroclimate—ice mass variability in the central Himalaya, where predictions are crucial for managing water resources and ecosystems.

Comprehensive Impacts of Climate Change on Rice Production and Adaptive Strategies in China.

The rice production system is one of the most climate change sensitive agro-ecosystems. This paper reviews the effects of current and future climate change on rice production in China. In recent decades, thermal resources have increased during the rice growing season, while solar radiation resources have decreased, and precipitation heterogeneity has increased. The increasing frequency of high-temperature stress, heavy rainfall, drought, and flood disasters may reduce the utilization efficiency of hydrothermal resources. Climate change, thus far, has resulted in a significant northward shift in the potential planting boundaries of single- and double-cropping rice production systems, which negatively affects the growth duration of single-, early-, and late-cropping rice. Studies based on statistical and process-based crop models show that climate change has affected rice production in China. The effects of climate change on the yield of single rice (SR), early rice (ER), and late rice (LR) were significant; however, the results of different methods and different rice growing areas were different to some extent. The trend of a longer growth period and higher yield of rice reflects the ability of China’s rice production system to adapt to climate change by adjusting planting regionalization and improving varieties and cultivation techniques. The results of the impact assessment under different climate scenarios indicated that the rice growth period would shorten and yield would decrease in the future. This means that climate change will seriously affect China’s rice production and food security. Further research requires a deeper understanding of abiotic stress physiology and its integration into ecophysiological models to reduce the uncertainty of impact assessment and expand the systematicness of impact assessment.

Maximize crop production and environmental sustainability: Insights from an ecophysiological model of plant-pest interactions and multi-criteria decision analysis

Satisfying the demand for agricultural products while also protecting the environment from negative impacts of agriculture is a major challenge for crop management. We used an ecophysiological model of plant-pest interaction and multi-criteria decision analysis to optimize crop management when considering two contrasting objectives: (1) maximizing crop production and (2) minimizing environmental impact related to fertilization, irrigation and pesticide deployment. The model provides an indicator of crop production for 27 management scenarios, obtained combining three levels of fertilization, irrigation and pesticide use, respectively. We computed the environmental impact relevant to each management scenario by means of a weighted sum of costs assigned to fertilization, irrigation and pesticide use. We identified the optimal scenarios with respect to the considered objectives analysing the Pareto front. These scenarios were mostly characterized by high fertilization and no pesticide use. We evaluated the multi-functionality of the optimal scenarios by mean of the Gini coefficient: the scenario better assuring the equality between the two objectives was characterized by high fertilization, intermediate irrigation and no pesticide. Although our results remain qualitative and not immediately transferable to agronomic practices, our analytical framework provides a useful tool to evidence trade-offs among two contrasting objectives and provide solutions to act in an efficient way by leaving a certain degree of freedom to the decision maker.

Dynamic QTL-based ecophysiological models to predict phenotype from genotype and environment data

BackgroundPredicting the phenotype from the genotype is one of the major contemporary challenges in biology. This challenge is greater in plants because their development occurs mostly post-embryonically under diurnal and seasonal environmental fluctuations. Most current crop simulation models are physiology-based models capable of capturing environmental fluctuations but cannot adequately capture genotypic effects because they were not constructed within a genetics framework.ResultsWe describe the construction of a mixed-effects dynamic model to predict time-to-flowering in the common bean (Phaseolus vulgaris L.). This prediction model applies the developmental approach used by traditional crop simulation models, uses direct observational data, and captures the Genotype, Environment, and Genotype-by-Environment effects to predict progress towards time-to-flowering in real time. Comparisons to a traditional crop simulation model and to a previously developed static model shows the advantages of the new dynamic model.ConclusionsThe dynamic model can be applied to other species and to different plant processes. These types of models can, in modular form, gradually replace plant processes in existing crop models as has been implemented in BeanGro, a crop simulation model within the DSSAT Cropping Systems Model. Gene-based dynamic models can accelerate precision breeding of diverse crop species, particularly with the prospects of climate change. Finally, a gene-based simulation model can assist policy decision makers in matters pertaining to prediction of food supplies.

Variability in frost occurrence under climate change and consequent risk of damage to trees of western Quebec, Canada

Climate change affects timings, frequency, and intensity of frost events in northern ecosystems. However, our understanding of the impacts that frost will have on growth and survival of plants is still limited. When projecting the occurrence of frost, the internal variability and the different underlying physical formulations are two major sources of uncertainty of climate models. We use 50 climate simulations produced by a single-initial large climate ensemble and five climate simulations produced by different pairs of global and regional climate models based on the concentration pathway (RCP 8.5) over a latitudinal transect covering the temperate and boreal ecosystems of western Quebec, Canada, during 1955–2099 to provide a first-order estimate of the relative importance of these two sources of uncertainty on the occurrence of frost, i.e. when air temperature is < 0 °C, and their potential damage to trees. The variation in the date of the last spring frost was larger by 21 days (from 46 to 25 days) for the 50 climate simulations compared to the 5 different pairs of climate models. When considering these two sources of uncertainty in an eco-physiological model simulating the timings of budbreak for trees of northern environment, results show that 20% of climate simulations expect that trees will be exposed to frost even in 2090. Thus, frost damage to trees remains likely under global warming.