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Spring maize (Zea mays L.) is a thermophilic C4 crop which is sensitive to climate change. This paper provides a detailed assessment of the effect of climate change on the crop from a new perspective, by predicting the probability of the potential distribution of spring maize across China. The affected area of spring maize suitability was identified, and then the affected area was subdivided into the improved area and the deteriorated area. Our results confirmed that there was a detrimental consequence for spring maize suitability under observed climate change from 1961&ndash, 1990 to 1981&ndash, 2010. However, our results revealed that warming scenarios of 1.5 &deg, C and 2 &deg, C were helpful for the suitable area expansion of spring maize. The affected area was smaller under warming scenarios than under historical climate change, revealing that temperature rise alone was not enough to trigger a &ldquo, tipping point&rdquo, (a threshold value after which abrupt shifts occur) for spring maize, even if warming is 2 &deg, C above the level of 1961&ndash, 1990. Our results not only benefit China in the design of mitigation and adaptation strategies, but also provide a theoretical judgement that the impact of global warming on the crop ecosystem is not serious if other climate factors remain unchanged.

In the context of climate warming, the varying soil moisture caused by precipitation pattern change will affect the applicability of stomatal conductance models, thereby affecting the simulation accuracy of carbon–nitrogen–water cycles in ecosystems. We studied the applicability of four common stomatal conductance models including Jarvis, Ball-Woodrow-Berry (BWB), Ball-Berry-Leuning (BBL) and unified stomatal optimization (USO) models based on summer maize leaf gas exchange data from a soil moisture consecutive decrease manipulation experiment. The results showed that the USO model performed best, followed by the BBL model, BWB model, and the Jarvis model performed worst under varying soil moisture conditions. The effects of soil moisture made a difference in the relative performance among the models. By introducing a water response function, the performance of the Jarvis, BWB, and USO models improved, which decreased the normalized root mean square error (NRMSE) by 15.7%, 16.6% and 3.9%, respectively; however, the performance of the BBL model was negative, which increased the NRMSE by 5.3%. It was observed that the models of Jarvis, BWB, BBL and USO were applicable within different ranges of soil relative water content (i.e., 55%–65%, 56%–67%, 37%–79% and 37%–95%, respectively) based on the 95% confidence limits. Moreover, introducing a water response function, the applicability of the Jarvis and BWB models improved. The USO model performed best with or without introducing the water response function and was applicable under varying soil moisture conditions. Our results provide a basis for selecting appropriate stomatal conductance models under drought conditions.

It is important research fields of global change ecology to study the influence that global climate change has on ecosystem and agroforestry, environmental factor such as water resources. And it is also important scientific basis on which to cope with climate change, to manage ecosystem adaptively and to make relevant policies. If the change of the earth system’s strength power is the ultimate concern of global climate change study, it will be to focus on questions to recognize the change of ecosystem’s structure, process, and function motivated by climate change and human activities. The earth feeds on massive diverse natural ecosystem, and diverse semi-natural semi-artificial ecosystem, which is already a result of a long-term adaption of the earth to natural environment and human activities. In that case, the adaption research of the ecosystem to the environment change plays a key role in humans getting to know what influence global changes may have on the supporting capacity of earth system. This chapter mainly concerns about the ecosystem’s adaptability. It is defined as the adaptive abilities of lowering environment changes’ negative influence and making good use of favorable opportunities when environment changes but the ecosystem tries to maintain its main functions. And this balance mechanism and adaptability of ecosystem is a basis on which to judge the influence degrees of global changes on ecosystem’s structure and function. To dig into this question, we generally study from two different perspectives, one of which is global changes’ influence on the ecosystem, and the other one is the ecosystem’s responses to these changes, which is the principal framework of this chapter.

To provide scientific support for planning maize production and designing countermeasures against the effects of climate change on the national maize crop, we analyzed the climatic suitability for cultivating maize across China. These analyses were based on annual climate indices at the Chinese national level; these indices influence the geographical distribution of maize cultivation. The annual climate indices, together with geographical information on the current cultivation sites of maize, the maximum entropy (MaxEnt) model, and the ArcGIS spatial analysis technique were used to analyze and predict maize distribution. The results show that the MaxEnt model can be used to study the climatic suitability for maize cultivation. The eight key climatic factors affecting maize cultivation areas were the frost-free period, annual average temperature, ⩾0°C accumulated temperature, ⩾10°C accumulated temperature continuous days, ⩾10°C accumulated temperature, annual precipitation, warmest month average temperature, and humidity index. We classified climatic zones in terms of their suitability for maize cultivation, based on the existence probability determined using the MaxEnt model. Furthermore, climatic thresholds for a potential maize cultivation zone were determined based on the relationship between the dominant climatic factors and the potential maize cultivation area. The results indicated that the importance and thresholds of main climate controls differ for different maize species and maturities, and their specific climatic suitability should be studied further to identify the best cultivation zones. The MaxEnt model is a useful tool to study climatic suitability for maize cultivation.