Integrating ecophysiology and forest landscape models to improve projections of drought effects under climate change

Fundamental drivers of ecosystem processes such as temperature and precipitation are rapidly changing and creating novel environmental conditions. Forest landscape models (FLM) are used by managers and policy‐makers to make projections of future ecosystem dynamics under alternative management or policy options, but the links between the fundamental drivers and projected responses are weak and indirect, limiting their reliability for projecting the impacts of climate change. We developed and tested a relatively mechanistic method to simulate the effects of changing precipitation on species competition within the LANDIS‐II FLM. Using data from a field precipitation manipulation experiment in a piñon pine (Pinus edulis) and juniper (Juniperus monosperma) ecosystem in New Mexico (USA), we calibrated our model to measurements from ambient control plots and tested predictions under the drought and irrigation treatments against empirical measurements. The model successfully predicted behavior of physiological variables under the treatments. Discrepancies between model output and empirical data occurred when the monthly time step of the model failed to capture the short‐term dynamics of the ecosystem as recorded by instantaneous field measurements. We applied the model to heuristically assess the effect of alternative climate scenarios on the piñon–juniper ecosystem and found that warmer and drier climate reduced productivity and increased the risk of drought‐induced mortality, especially for piñon. We concluded that the direct links between fundamental drivers and growth rates in our model hold great promise to improve our understanding of ecosystem processes under climate change and improve management decisions because of its greater reliance on first principles.     

温室秸秆不同还田量条件下DSSAT-CROPGRO-Tomato模型的调参与验证

为了探讨番茄生长模拟模型DSSAT-CROPGRO-Tomato能否准确模拟秸秆还田条件下北方日光温室番茄的生长发育和产量形成过程,基于2016年和2018年温室番茄小区试验数据对模型进行验证。试验设置4个秸秆还田量处理,分别为0(S₀)、1.5×10⁴(S₁)、3×10⁴(S₂)和4.5×10⁴kg·hm^-2(S₃)。利用GLUE参数估计模块获得不同方案相应的作物遗传参数,通过分析和对比番茄物候期、鲜果产量、最大叶面积指数、土壤水分、土壤无机态氮和地上干物质量的实测值与模拟值,验证模型模拟精度并确定最优方案。结果表明,参数PODUR(最优条件下最终果实负载所需光热时长)和SLAVR(比叶面积)的变异系数较大,分别为28.53%和14.13%。模型在2016年所有处理为参数估计方案时模拟精度最高,其ARE和nRMSE分别为10.33%和7.12%。模型对温室土壤水分、番茄生长和产量的模拟精度较高。留一交叉验证法体现模型对温室番茄产量总体误差在18.68%~21.95%。说明CROPGRO-Tomato模型可以较准确模拟秸秆不同还田量条件下沈阳日光温室番茄生长和产量形成过程。     

Understanding Reaction of Potato (Solanum tuberosum) to Ralstonia solanacearum and Relationship of Wilt Incidence to Latent Infection

Bacterial wilt caused by Ralstonia solanacearum is one of the most important diseases affecting more than 200 plant species, including solanaceous crops. The pathogen is known to cause complicated symptoms ranging from visible to latent ones. Understanding crop's reaction to the pathogen and the underlying relatedness of latent infection to wilt incidence is of paramount importance. Thus, a number of potato cultivars including improved and otherwise were evaluated under greenhouse and field conditions. Accordingly, twenty‐eight of the cultivars tested under greenhouse conditions were resistant to the pathogen with scores ranging from 0.77 to 1.17 of 5. Nonetheless, under field conditions, only 2 of 28 cultivars found to be ‘resistant’ under greenhouse conditions, showed adequate resistance to the pathogen, indicating the significant impact of environment on the activity of the pathogen and reaction of the crop. Percentage wilt incidence and latent infection showed significant (P < 0.05) positive correlation, with r = 0.9438. Thus, evaluation of crop's performance based on the combination of the parameters like field wilt incidence and proportion of latent infection gave us better picture of the overall crop feat, than using wilt incidence as a sole parameter of evaluation as has been the case in most studies. Moreover, the established correlation of latent infection with field wilt incidence will also help us understand the disease epidemiology and design effective management measures, accordingly.     

Efficacy of sulphur on Tuta absoluta and its side effects on the predator Nesidiocoris tenuis

The South American tomato pinworm, Tuta absoluta (Meyrick), is one of the major pests of tomato crop. Since its detection in the Mediterranean basin, it has been commonly controlled using chemical insecticides. However, inoculation and conservation of predatory mirids, integrated with sprays of selective insecticides, has been demonstrated to be a cost‐effective strategy for controlling this pest. In this work, we tested the efficacy of two sulphur formulations, dustable and wettable powder, for controlling T. absoluta on tomato under greenhouse and open‐field conditions. In addition, the side effects of both sulphur formulations on the predator, Nesidiocoris tenuis (Reuter), were evaluated under laboratory conditions. Dustable sulphur, applied weekly on tomato seedlings artificially infested with T. absoluta in greenhouse conditions, significantly reduced the infestation levels and was demonstrated to have a repellent effect on oviposition. Wettable sulphur was not effective for controlling T. absoluta populations in both greenhouse and open‐field experiments. In the side effect trials conducted with N. tenuis, only dustable sulphur resulted in being moderately harmful as a fresh residue and slightly harmful as a 7‐day‐old residue; no effects were recorded exposing the predator to 14‐day‐old sulphur residues. In contrast, wettable sulphur was classified as harmless to N. tenuis. Our results suggest that the use of sulphur, especially as dustable powder, could be considered as a tool in T. absoluta management strategies, although its side effects on N. tenuis should be taken into account. The implications of these results for the use of sulphur formulations in pest and disease management programmes in tomato crops are discussed.     

Tradeoffs between Maize Silage Yield and Nitrate Leaching in a Mediterranean Nitrate-Vulnerable Zone under Current and Projected Climate Scenarios

Future climatic changes may have profound impacts on cropping systems and affect the agronomic and environmental sustainability of current N management practices. The objectives of this work were to i) evaluate the ability of the SALUS crop model to reproduce experimental crop yield and soil nitrate dynamics results under different N fertilizer treatments in a farmer’s field, ii) use the SALUS model to estimate the impacts of different N fertilizer treatments on NO₃^- leaching under future climate scenarios generated by twenty nine different global circulation models, and iii) identify the management system that best minimizes NO₃^- leaching and maximizes yield under projected future climate conditions. A field experiment (maize-triticale rotation) was conducted in a nitrate vulnerable zone on the west coast of Sardinia, Italy to evaluate N management strategies that include urea fertilization (NMIN), conventional fertilization with dairy slurry and urea (CONV), and no fertilization (N0). An ensemble of 29 global circulation models (GCM) was used to simulate different climate scenarios for two Representative Circulation Pathways (RCP6.0 and RCP8.5) and evaluate potential nitrate leaching and biomass production in this region over the next 50 years. Data collected from two growing seasons showed that the SALUS model adequately simulated both nitrate leaching and crop yield, with a relative error that ranged between 0.4% and 13%. Nitrate losses under RCP8.5 were lower than under RCP6.0 only for NMIN. Accordingly, levels of plant N uptake, N use efficiency and biomass production were higher under RCP8.5 than RCP6.0. Simulations under both RCP scenarios indicated that the NMIN treatment demonstrated both the highest biomass production and NO₃^- losses. The newly proposed best management practice (BMP), developed from crop N uptake data, was identified as the optimal N fertilizer management practice since it minimized NO₃^- leaching and maximized biomass production over the long term.     

Bioenergy crop models: descriptions,data requirements,and future challenges

Field studies that address the production of lignocellulosic biomass as a source of renewable energy provide critical data for the development of bioenergy crop models. A literature survey revealed that 14 models have been used for simulating bioenergy crops including herbaceous and woody bioenergy crops, and for crassulacean acid metabolism (CAM) crops. These models simulate field‐scale production of biomass for switchgrass (ALMANAC, EPIC, and Agro‐BGC), miscanthus (MISCANFOR, MISCANMOD, and WIMOVAC), sugarcane (APSIM, AUSCANE, and CANEGRO), and poplar and willow (SECRETS and 3PG). Two models are adaptations of dynamic global vegetation models and simulate biomass yields of miscanthus and sugarcane at regional scales (Agro‐IBIS and LPJmL). Although it lacks the complexity of other bioenergy crop models, the environmental productivity index (EPI) is the only model used to estimate biomass production of CAM (Agave and Opuntia) plants. Except for the EPI model, all models include representations of leaf area dynamics, phenology, radiation interception and utilization, biomass production, and partitioning of biomass to roots and shoots. A few models simulate soil water, nutrient, and carbon cycle dynamics, making them especially useful for assessing the environmental consequences (e.g., erosion and nutrient losses) associated with the large‐scale deployment of bioenergy crops. The rapid increase in use of models for energy crop simulation is encouraging; however, detailed information on the influence of climate, soils, and crop management practices on biomass production is scarce. Thus considerable work remains regarding the parameterization and validation of process‐based models for bioenergy crops; generation and distribution of high‐quality field data for model development and validation; and implementation of an integrated framework for efficient, high‐resolution simulations of biomass production for use in planning sustainable bioenergy systems.     

Climate change may have limited effect on global risk of potato late blight

Weather affects the severity of many plant diseases, and climate change is likely to alter the patterns of crop disease severity. Evaluating possible future patterns can help focus crop breeding and disease management research. We examined the global effect of climate change on potato late blight, the disease that caused the Irish potato famine and still is a common potato disease around the world. We used a metamodel and considered three global climate models for the A2 greenhouse gas emission scenario for three 20‐year time‐slices: 2000–2019, 2040–2059 and 2080–2099. In addition to global analyses, five regions were evaluated where potato is an important crop: the Andean Highlands, Indo‐Gangetic Plain and Himalayan Highlands, Southeast Asian Highlands, Ethiopian Highlands, and Lake Kivu Highlands in Sub‐Saharan Africa. We found that the average global risk of potato late blight increases initially, when compared with historic climate data, and then declines as planting dates shift to cooler seasons. Risk in the agro‐ecosystems analyzed, varied from a large increase in risk in the Lake Kivu Highlands in Rwanda to decreases in the Southeast Asian Highlands of Indonesia.     

TMV-Infection syndromes in potato cultivars Erika and Krasava

Tre potato cultivars Erika and Krasava are unable to reproduce two strains of TMV systemically except when in graft symbiosis under normal greenhouse conditions with tomato which has been infected with the virus. The escape resistance of potato to TMV infection due to slight hypersensitivity was not changed either by long-lasting non-infectious symbiosis with TMV-sensitive tomato or in a constant environment (32±2 °C, 9 700 lx) which was adequate to change the hypersensitive reaction of some other TMV-hosts. On the contrary, enhanced temperature provoked a still more severe local and necrotic response in the potato varieties. This led to systemic necrosis and the quick death of potato components systemically infected in graft symbiosis with tomato under normal greenhouse conditions when transferred into an environment of enhanced temperature.     

Assessing long-term impacts of cover crops on soil organic carbon in the central US Midwestern agroecosystems

Cover crops have been reported as one of the most effective practices to increase soil organic carbon (SOC) for agroecosystems. Impacts of cover crops on SOC change vary depending on soil properties, climate, and management practices, but it remains unclear how these control factors affect SOC benefits from cover crops, as well as which management practices can maximize SOC benefits. To address these questions, we used an advanced process-based agroecosystem model, ecosys, to assess the impacts of winter cover cropping on SOC accumulation under different environmental and management conditions. We aimed to answer the following questions: (1) To what extent do cover crops benefit SOC accumulation, and how do SOC benefits from cover crops vary with different factors (i.e., initial soil properties, cover crop types, climate during the cover crop growth period, and cover crop planting and terminating time)? (2) How can we enhance SOC benefits from cover crops under different cover crop management options? Specifically, we first calibrated and validated the ecosys model at two long-term field experiment sites with SOC measurements in Illinois. We then applied the ecosys model to six cover crop field experiment sites spanning across Illinois to assess the impacts of different factors on SOC accumulation. Our modeling results revealed the following findings: (1) Growing cover crops can bring SOC benefits by 0.33 ± 0.06 MgC ha⁻¹ year⁻¹ in six cover crop field experiment sites across Illinois, and the SOC benefits are species specific to legume and non-legume cover crops. (2) Initial SOC stocks and clay contents had overall small influences on SOC benefits from cover crops. During the cover crop growth period (i.e., winter and spring in the US Midwest), high temperature increased SOC benefits from cover crops, while the impacts from larger precipitation on SOC benefits varied field by field. (3) The SOC benefits from cover crops can be maximized by optimizing cover crop management practices (e.g., selecting cover crop types and controlling cover crop growth period) for the US Midwestern maize–soybean rotation system. Finally, we discussed the economic and policy implications of adopting cover crops in the US Midwest, including that current economic incentives to grow cover crops may not be sufficient to cover costs. This study systematically assessed cover crop impacts for SOC change in the US Midwest context, while also demonstrating that the ecosys model, with rigorous validation using field experiment data, can be an effective tool to guide the adaptive management of cover crops and quantify SOC benefits from cover crops. The study thus provides practical tools and insights for practitioners and policy-makers to design cover crop related government agricultural policies and incentive programs for farmers and agri-food related industries.     

Responses of soil carbon sequestration to climate‐smart agriculture practices: A meta‐analysis

Climate‐smart agriculture (CSA) management practices (e.g., conservation tillage, cover crops, and biochar applications) have been widely adopted to enhance soil organic carbon (SOC) sequestration and to reduce greenhouse gas emissions while ensuring crop productivity. However, current measurements regarding the influences of CSA management practices on SOC sequestration diverge widely, making it difficult to derive conclusions about individual and combined CSA management effects and bringing large uncertainties in quantifying the potential of the agricultural sector to mitigate climate change. We conducted a meta‐analysis of 3,049 paired measurements from 417 peer‐reviewed articles to examine the effects of three common CSA management practices on SOC sequestration as well as the environmental controlling factors. We found that, on average, biochar applications represented the most effective approach for increasing SOC content (39%), followed by cover crops (6%) and conservation tillage (5%). Further analysis suggested that the effects of CSA management practices were more pronounced in areas with relatively warmer climates or lower nitrogen fertilizer inputs. Our meta‐analysis demonstrated that, through adopting CSA practices, cropland could be an improved carbon sink. We also highlight the importance of considering local environmental factors (e.g., climate and soil conditions and their combination with other management practices) in identifying appropriate CSA practices for mitigating greenhouse gas emissions while ensuring crop productivity.     

Association of Bactericera cockerelli (Homoptera: Psyllidae) with "zebra chip," a new potato disease in southwestern United States and Mexico

A new defect of potato, Solanum tuberosum L., "zebra chip," so named for the characteristic symptoms that develop in fried chips from infected potato tubers, has recently been documented in several southwestern states of the United States, in Mexico, and in Central America. This defect is causing millions of dollars in losses to both potato producers and processors. Zebra chip plant symptoms resemble those caused by potato purple top and psyllid yellows diseases. Experiments were conducted to elucidate the association between the psyllid Bactericera cockerelli (Sulc) (Homoptera: Psyllidae) and zebra chip by exposing clean potato plants to this insect under greenhouse and field conditions. Potato plants and tubers exhibiting zebra chip symptoms were tested for phytoplasmas by polymerase chain reaction. Potato psyllids collected from infected potato fields also were tested. Results indicated that there was an association between the potato psyllid and zebra chip. Plants exposed to psyllids in the greenhouse and field developed zebra chip. In the greenhouse, 25.8 and 59.2% of tubers exhibited zebra chip symptoms in the raw tubers and fried chips, respectively. In the field, 15 and 57% of tubers showed symptoms in raw tubers and chips, respectively. No zebra chip was observed in tubers from plants that had not been exposed to psyllids, either in the greenhouse or field. No phytoplasmas were detected from potato plants or tubers with zebra chip symptoms, suggesting that these pathogens are not involved in zebra chip. Of the 47 samples of potato psyllids tested, only two tested positive for the Columbia Basin potato purple top phytoplasma.     

Using ecosystem models to assess potential consequences of global climatic change

Predicting ecosystem response to climate change is a dynamic version of the classic problem of understanding vegetation-climate interrelations. Computer models can synthesize current knowledge and are important tools for understanding possible ecosystem dynamics under changed conditions. Models based on individual plant biology and natural history have been tested with respect to their ability to simulate vegetation response to changed climate, and are being applied to assess the potential effects of future climate change.     

Crop connectivity under climate change: future environmental and geographic risks of potato late blight in Scotland

The impact of climate change on dispersal processes is largely ignored in risk assessments for crop diseases, as inoculum is generally assumed to be ubiquitous and nonlimiting. We suggest that consideration of the impact of climate change on the connectivity of crops for inoculum transmission may provide additional explanatory and predictive power in disease risk assessments, leading to improved recommendations for agricultural adaptation to climate change. In this study, a crop‐growth model was combined with aerobiological models and a newly developed infection risk model to provide a framework for quantifying the impact of future climates on the risk of disease occurrence and spread. The integrated model uses standard meteorological variables and can be easily adapted to various crop pathosystems characterized by airborne inoculum. In a case study, the framework was used with data defining the spatial distribution of potato crops in Scotland and spatially coherent, probabilistic climate change data to project the future connectivity of crop distributions for Phytophthora infestans (causal agent of potato late blight) inoculum and the subsequent risk of infection. Projections and control recommendations are provided for multiple combinations of potato cultivar and CO₂ emissions scenario, and temporal and spatial averaging schemes. Overall, we found that relative to current climatic conditions, the risk of late blight will increase in Scotland during the first half of the potato growing season and decrease during the second half. To guide adaptation strategies, we also investigated the potential impact of climate change‐driven shifts in the cropping season. Advancing the start of the potato growing season by 1 month proved to be an effective strategy from both an agronomic and late blight management perspective.     

Soil Carbon and Nitrogen Fractions and Crop Yields Affected by Residue Placement and Crop Types

Soil labile C and N fractions can change rapidly in response to management practices compared to non-labile fractions. High variability in soil properties in the field, however, results in nonresponse to management practices on these parameters. We evaluated the effects of residue placement (surface application [or simulated no-tillage] and incorporation into the soil [or simulated conventional tillage]) and crop types (spring wheat [Triticum aestivum L.], pea [Pisum sativum L.], and fallow) on crop yields and soil C and N fractions at the 0–20 cm depth within a crop growing season in the greenhouse and the field. Soil C and N fractions were soil organic C (SOC), total N (STN), particulate organic C and N (POC and PON), microbial biomass C and N (MBC and MBN), potential C and N mineralization (PCM and PNM), NH₄-N, and NO₃-N concentrations. Yields of both wheat and pea varied with residue placement in the greenhouse as well as in the field. In the greenhouse, SOC, PCM, STN, MBN, and NH₄-N concentrations were greater in surface placement than incorporation of residue and greater under wheat than pea or fallow. In the field, MBN and NH₄-N concentrations were greater in no-tillage than conventional tillage, but the trend reversed for NO₃-N. The PNM was greater under pea or fallow than wheat in the greenhouse and the field. Average SOC, POC, MBC, PON, PNM, MBN, and NO₃-N concentrations across treatments were higher, but STN, PCM and NH₄-N concentrations were lower in the greenhouse than the field. The coefficient of variation for soil parameters ranged from 2.6 to 15.9% in the greenhouse and 8.0 to 36.7% in the field. Although crop yields varied, most soil C and N fractions were greater in surface placement than incorporation of residue and greater under wheat than pea or fallow in the greenhouse than the field within a crop growing season. Short-term management effect on soil C and N fractions were readily obtained with reduced variability under controlled soil and environmental conditions in the greenhouse compared to the field. Changes occurred more in soil labile than non-labile C and N fractions in the greenhouse than the field.     

Why does phenology drive species distribution?

Despite the numerous studies which have been conducted during the past decade on species ranges and their relationship to the environment, our understanding of how environmental conditions shape species distribution is still far from complete. Yet, some process-based species distribution models have been able to simulate plants and insects distribution at a global scale. These models strongly rely on the completion of the annual cycle of the species and therefore on their accomplished phenology. In particular, they have shown that the northern limit of species'' ranges appears to be caused mainly by the inability to undergo full fruit maturation, while the southern limit appears to be caused by the inability to flower or unfold leaves owing to a lack of chilling temperatures that are necessary to break bud dormancy. I discuss here why phenology is a key adaptive trait in shaping species distribution using mostly examples from plant species, which have been the most documented. After discussing how phenology is involved in fitness and why it is an adaptive trait susceptible to evolve quickly in changing climate conditions, I describe how phenology is related to fitness in species distribution process-based models and discuss the fate of species under climate change scenarios using model projections and experimental or field studies from the literature.     

Effect of acidic electrolyzed water on the viability of bacterial and fungal plant pathogens and on bacterial spot disease of tomato

Acidic electrolyzed water (AEW), known to have germicidal activity, was obtained after electrolysis of 0.045% aqueous solution of sodium chloride. Freshly prepared AEW (pH 2.3-2.6, oxidation-reduction potential 1007-1025 mV, and free active chlorine concentration 27-35 ppm) was tested in vitro and (or) on tomato foliage and seed surfaces for its effects on the viability of plant pathogen propagules that could be potential seed contaminants. Foliar sprays of AEW were tested against bacterial spot disease of tomato under greenhouse and field conditions. The viability of propagules of Xanthomonas campestris pv. vesicatoria (bacterial spot pathogen), Streptomyces scabies (potato scab pathogen), and Fusarium oxysporum f.sp. lycopersici (root rot pathogen) was significantly reduced 4-8 log units within 2 min of exposure to AEW. Immersion of tomato seed from infected fruit in AEW for 1 and 3 min significantly reduced the populations of X. campestris pv. vesicatoria from the surface of the seed without affecting seed germination. Foliar sprays of AEW reduced X. campestris pv. vesicatoria populations and leaf spot severity on tomato foliage in the greenhouse. In the field, multiple sprays of AEW consistently reduced bacterial spot severity on tomato foliage. Disease incidence and severity was also reduced on fruit, but only in 2003. Fruit yield was either enhanced or not affected by the AEW sprays. These results indicate a potential use of AEW as a seed surface disinfectant or contact bactericide.     

马铃薯生育期进程的动态模拟研究

本研究系统解析和改进了前人关于作物生长温度效应的非线性模型,并对修改后的模型进行了解释,结合4年的田间试验数据和本研究提出的基于高斯方程的作物生长温度效应模型,建立了不同生态条件下马铃薯生育期进程的模拟模型．模型解析了地膜覆盖条件下土壤温度增加对马铃薯生育期进程的数值贡献,模拟了不同生态条件下马铃薯的生育期进展,结果表明模拟值与实测值具有良好的一致性。     

Agronomic Practices for Improving Gentle Remediation of Trace Element-Contaminated Soils

The last few decades have seen the rise of Gentle soil Remediation Options (GRO), which notably include in situ contaminant stabilization (“inactivation”) and plant-based (generally termed “phytoremediation”) options. For trace element (TE)-contaminated sites, GRO aim to either decrease their labile pool and/or total content in the soil, thereby reducing related pollutant linkages. Much research has been dedicated to the screening and selection of TE-tolerant plant species and genotypes for application in GRO. However, the number of field trials demonstrating successful GRO remains well below the number of studies carried out at a greenhouse level. The move from greenhouse to field conditions requires incorporating agronomical knowledge into the remediation process and the ecological restoration of ecosystem services. This review summarizes agronomic practices against their demonstrated or potential positive effect on GRO performance, including plant selection, soil management practices, crop rotation, short rotation coppice, intercropping/row cropping, planting methods and plant densities, harvest and fertilization management, pest and weed control and irrigation management. Potentially negative effects of GRO, e.g., the introduction of potentially invasive species, are also discussed. Lessons learnt from long-term European field case sites are given for aiding the choice of appropriate management practices and plant species.     

Models meet data: Challenges and opportunities in implementing land management in Earth system models

As the applications of Earth system models (ESMs) move from general climate projections toward questions of mitigation and adaptation, the inclusion of land management practices in these models becomes crucial. We carried out a survey among modeling groups to show an evolution from models able only to deal with land‐cover change to more sophisticated approaches that allow also for the partial integration of land management changes. For the longer term a comprehensive land management representation can be anticipated for all major models. To guide the prioritization of implementation, we evaluate ten land management practices—forestry harvest, tree species selection, grazing and mowing harvest, crop harvest, crop species selection, irrigation, wetland drainage, fertilization, tillage, and fire—for (1) their importance on the Earth system, (2) the possibility of implementing them in state‐of‐the‐art ESMs, and (3) availability of required input data. Matching these criteria, we identify “low‐hanging fruits” for the inclusion in ESMs, such as basic implementations of crop and forestry harvest and fertilization. We also identify research requirements for specific communities to address the remaining land management practices. Data availability severely hampers modeling the most extensive land management practice, grazing and mowing harvest, and is a limiting factor for a comprehensive implementation of most other practices. Inadequate process understanding hampers even a basic assessment of crop species selection and tillage effects. The need for multiple advanced model structures will be the challenge for a comprehensive implementation of most practices but considerable synergy can be gained using the same structures for different practices. A continuous and closer collaboration of the modeling, Earth observation, and land system science communities is thus required to achieve the inclusion of land management in ESMs.     

APSIM 模型的发展与应用

土壤-作物模拟模型已成为向农业生产管理决策提供科学依据的一个有效工具,APSIM（Agricultural Production System Simulator)模型是澳大利亚科学家开发研制的,用于模拟农业系统穰生物过程,特别是气候风险下系统各组分生态和经济输出的机理模型,APSIM已在温带大 陆性气候,温带海洋性气候,亚热带干旱气候和地中海气候带下的粘土,胀缩土（duplex),变性土（vertisol),粉粒砂壤,粉粒壤土和粉粒粘壤土等土壤上进行了验证和应用。可以用于小麦等20余种作物的模拟,APSIM模型在作物结构和轮作序列调整,作物产量,质量预测和控制及不同种植方式下水土流失调控等方面具有良好的描述能力。