A conceptual framework for evaluation of climate effects on tree diseases is presented. Climate can exacerbate tree diseases by favouring pathogen biology, including reproduction and infection processes. Climatic conditions can also cause abiotic disease—direct stress or mortality when trees’ physiological limits are exceeded. When stress is sublethal, weakened trees may subsequently be killed by secondary organisms. To demonstrate climate's involvement in disease, associations between climatic conditions and disease expression provide the primary evidence of atmospheric involvement because experimentation is often impractical for mature trees. This framework tests spatial and temporal relationships of climate and disease at several scales to document climate effects, if any. The presence and absence of the disease can be contrasted with climate data and models at geographic scales: stand, regional and species range. Temporal variation in weather, climate and climate change is examined during onset, development and remission of the disease. Predisposing factors such as site and stand conditions can modify the climate effects of some diseases, especially at finer spatial scales. Spatially explicit climate models that display temperature and precipitation or derivative models such as snow and drought stress provide useful data, and however, information on disease extent at different spatial scales and monitoring through time are often incomplete. The framework can be used to overcome limitations in other disease causality approaches, such as Koch's postulates, and allow for the integration of vegetation, pathogen and environmental data into causality determinations.

中文翻译：

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评估气候对林木病害影响的框架

提出了评估气候对树木病害影响的概念框架。气候有利于病原体生物学，包括繁殖和感染过程，从而加剧树木疾病。气候条件也可能导致非生物疾病——当树木超出生理极限时直接压力或死亡。当压力是亚致死的时，弱化的树木可能随后被次生生物杀死。为了证明气候与疾病的关系，气候条件和疾病表达之间的关联提供了大气参与的主要证据，因为对于成熟的树木进行实验通常是不切实际的。该框架在多个尺度上测试气候和疾病的时空关系，以记录气候影响（如果有的话）。该疾病的存在和不存在可以与地理尺度上的气候数据和模型进行对比：林分、区域和物种范围。在疾病的发生、发展和缓解期间检查天气、气候和气候变化的时间变化。场地和林分条件等诱发因素可以改变某些疾病的气候影响，尤其是在更精细的空间尺度上。显示温度和降水的空间明确气候模型或雪和干旱胁迫等衍生模型提供了有用的数据，但是，关于不同空间尺度的疾病范围和随时间监测的信息往往不完整。该框架可用于克服其他疾病因果关系方法的局限性，例如科赫假设，并允许整合植被，