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Climex Dymex—— 物种分布潜在区域预测软件

CLIMEX利用模拟和建模技术预测气候变化对物种分布的影响。CLIMEX试图模仿限制物种地理分布的生物机制,并确定它们的季节物候和相对丰度。

DYMEX是一个模块化的建模包,允许用户快速开发和运行生物种群的确定性种群模型。这些种群模型是围绕物种的生命周期来构造的,而生命周期又是个体在其一生中经历的生长阶段。

CLIMEX有助于您了解气候变化对物种分布的影响以及外来物种入侵农业区的潜在风险。CLIMEX使您能够评估在新的位置建立害虫的风险和生物控制剂的潜在成败,除了知道它们所发生的当前位置外,并不知道具体物种的存在。在世界上大约四十个国家,CLIMEX被用来模拟、预测和帮助控制入侵的昆虫。虫害每年毁坏数十亿美元的商业作物,在这个变暖的世界里监测和控制入侵昆虫变得越来越重要。


DYMEX使您能够交互式地建立和运行变化环境中的生物体波动种群模型。生态学家可以创建一个广泛的基于过程的人口模型,而不需要知道编程语言。模型是围绕生命周期构造的,而生命周期又是由个体在其一生中经历的阶段构成的。DYMEX生命周期描述了个体的队列和影响队列中个体的大小、年龄和数量的过程。


新版的特征
运行速度提高了10倍;
改进的自动参数拟合;
比较位置模型现在可以创建每周的应力和生长指数的输出图;
添加了一个新模型,CLIMEX Compare Locations/Years,这使得气候适宜性的年际变化得以探索;
现在你可以制作季节性和年际气候适宜性的影片;
自动参数敏感性和模型不确定性分析是可用的;
区域气候匹配函数现在可以处理更大的数据集;
批量参数运行现在可以被排序,自动化一些高度重复的任务;
CLIMEX现在可以运行在64位Windows系统的计算机上;
新的User Guide包含建模技巧和详细资源;
对输出流、灵敏度分析、匹配气候(区域)、比较位置进行了改进;


系统需求
CLIMEX-DYMEX只适用于Windows系统。

Introduction

CLIMEX helps you understand the impact of climate change on species distribution and the potential risk from invasive species to an agricultural region.

CLIMEX enables you to assess the risk of a pest establishing in a new location and the potential success or failure of a biological control agent with no knowledge of the species, except for knowing the current locations they do occur.

In almost forty countries around the world, Climex is used to model, predict and help control invasive insects. Insect infestation destroys billions of dollars worth of commercial crops annually and monitoring and controlling invasive insects in a warming world is increasingly important.

The CLIMEX software contains two quite different climate-matching tools. There is the CLIMEX model (referred to as ‘CLIMEX’ or as the ‘CLIMEX model’), and the CLIMEX ‘Match Climates’ function. The latter is a tool for comparing the meteorological data of different places without reference to any particular species.
The CLIMEX simulation model was first described by Sutherst and Maywald (1985) and a number of enhancements and further caveats and insights into using the model have been described in a series of publications listed at the end of the user manual, particularly (Sutherst et al 1995, Sutherst 1998). The model is based on the assumption that if you know where a species lives you can infer what climatic conditions it can tolerate. In other words, CLIMEX attempts to mimic the mechanisms that limit species’ geographical distributions and determine their seasonal phenology and to a lesser extent their relative abundance.

CLIMEX enables the user to estimate the potential geographical distribution and seasonal abundance of a species in relation to climate. It does not try to match the patterns of climate and species’ distribution in the same way that a statistical fitting would seek to achieve.

CLIMEX is applied to a species by selecting values for a set of parameters that describe its response to temperature, moisture and light. The term ‘population’ is used as the target entity, representing an average population of an animal or plant species or biotype for example. An Annual Growth Index (GIA) describes the potential for growth of a population during the favourable season. Four stress indices (Cold, Hot, Wet and Dry), and in some cases their interactions, describe the extent to which the population is reduced during the unfavourable season. The Growth and Stress Indices are combined into an Ecoclimatic Index (EI), to give an overall measure of favourableness of the location or year for permanent occupation by the target species. Two limiting conditions, ie the length of the growing season and obligate diapause, act as overall constraints to the EI value where relevant. Results are presented as tables, graphs, or maps.

A species’ climatic requirements are inferred from its known geographical distribution (either in its native range or in another region where it has been established for a long time), relative abundance and seasonal phenology. Some laboratory data, such as developmental threshold temperatures, can be used to fit or fine tune CLIMEX parameter values. Initial estimates of parameter values are fine-tuned by comparing the indices with the known presence or absence, seasonal phenology and, preferably, relative abundance of the species in each location.
Once the parameter values have been estimated and where possible validated against independent data, CLIMEX can be used to make predictions for other, independent locations. Independent data means that there is no connection between the data and those data used for fitting the model, hence it is not appropriate to sub-sample a geographical distribution and then use the remaining data to test the model.

New Features The following list includes the major differences between Version 2 and Version 3. In addition, a large number of minor improvements have been made to the program.

Two species can now be fitted with interactions between them (either competition or synergy) specified via parameters.
Radiation is available as an additional component to the Growth Index.
Two non-specific components (definable by the user) can be added to the Growth Index. These are the Physical Substrate Index and the Biotic Substrate Index. The variables determining these indices can either be specified as a single value for all locations or they can be location specific and read from the MetManager.
Automatic fitting of the parameter values that determine the Stress indices is available via a genetic algorithm based fitting routine.
The MetManager application has been extended to allow the importation of up to 5 user-defined location constants as well as up to 5 user-defined variables.