Pale Kangaroo Mouse Predicted Habitat - CWHR M098 [ds2553]

CWHR Predicted Habitat Models represent areas of predicted suitable habitat for each species within its range. These models are built from the following principal inputs: 1) a statewide, best-available vegetation map (FVEG); 2) GIS data representing a species’ range; 3) the CWHR database of habitat suitability values for over 700 terrestrial vertebrate species. Habitat suitability ranks of Low (non-zero values less than 0.34), Medium (0.34-0.66), and High (greater than 0.66) are based on the maximum suitability value across the 3 species life requisites: reproduction, feeding, and cover. Note that previous versions of these Predicted Habitat Models used an average across the 3 life requisites in order to obtain an overall suitability score for each habitat type and stage class. Habitat suitability scores were developed based on habitat patch sizes greater than 40 acres in size and are best interpreted for habitat patches greater than 200 acres in size. The FVEG landcover dataset is an aggregation of multiple statewide landcover and regional vegetation mapping efforts, conducted at different points in time (approximately 1990 up to time of publishing) and at various resolutions, compiled by the California Department of Forestry and Fire Protection (CALFIRE). FVEG uses the most current and consistent data available for each region of the state. Decision rules were developed that controlled which layers were given priority in areas of overlap. Crosswalks were used to attribute the various data sources according to the CWHR habitat-type classification system. Attributing FVEG with CWHR habitat types allows for the extraction of areas with non-zero suitability values for each species within the bounds of its range, creating a series of maps of predicted suitable habitat which are species-specific. Because FVEG is an amalgam of disparate landcover assessment efforts across the state, the predictive power for determining suitable habitat will vary between species, and possibly even regionally for species which are widely distributed. While these maps represent CDFW’s best estimate of the presence of suitable habitat for any given species in the CWHR system, these maps are also limited by several factors: 1) the accuracy and resolution of vegetation maps in a given region; 2) the dynamic nature of the landscape in which fire and other disturbance events alter conditions at a greater frequency than mapping efforts can track; 3) the currency of expert knowledge, particularly as species adapt to changing land and climate conditions and the shifting of other species’ ranges; 4) the frequency of species-specific surveys across a representative sample of a species’ entire range; 5) metapopulation dynamics, which describes the shifting of populations within their environment as result of numerous types of interactions and responses. CWHR GIS data representing predicted suitable habitat should not be used to indicate the presence or absence of a particular species at any specific site. CWHR predicted habitat models are named according to the 4-character alpha-numeric CWHR ID assigned to each species (5 characters in the case of subspecies or other sub-taxa). There is also a “CWHR Revision Tracking Table” containing a record for each species, its CWHR ID, scientific name, common name, and range and habitat model data revision history. CWHR species range models, predicted habitat models, and GIS data of the statewide distribution of all CWHR habitat types, along with the CWHR revision tracking table, are available for download at https://www.wildlife.ca.gov/Data/CWHR.CWHR预测栖息地模型用于表征各物种种群分布范围内的潜在适宜栖息地区域。该模型基于以下核心输入构建：1）全州最优可用植被地图（FVEG）；2）表征物种种群分布范围的地理信息系统（GIS）数据；3）涵盖700余种陆生脊椎动物栖息地适宜性分值的CWHR数据库。 栖息地适宜性等级分为低（非零分值小于0.34）、中（0.34~0.66）和高（大于0.66）三类，其划分依据为物种三大生命必需条件——繁殖、觅食与隐蔽——对应的适宜性分值的最大值。需注意，此前版本的预测栖息地模型曾以三大生命必需条件的平均分值，作为各栖息地类型与阶段类别的整体适宜性评分依据。 本次模型的栖息地适宜性分值基于面积大于40英亩的栖息地斑块测算得出，其适用解读的最优场景为面积大于200英亩的栖息地斑块。FVEG土地覆盖数据集由加州林业与消防局（CALFIRE）整合多项全州及区域植被测绘项目成果编制而成，这些测绘项目的实施时间跨度约为1990年至发布当日，且采用了不同的空间分辨率。FVEG针对加州各区域采用了当前可获取的最新且一致性最优的数据。研究人员制定了决策规则，用于明确重叠区域中各数据图层的优先级，并采用跨源映射表（Crosswalks），依据CWHR栖息地类型分类体系为各类数据源匹配对应的分类属性。 将FVEG数据集匹配CWHR栖息地类型后，即可提取各物种种群分布范围内具有非零适宜性分值的区域，从而生成一系列针对特定物种的预测适宜栖息地地图。由于FVEG数据集整合了加州境内多项不同的土地覆盖评估项目成果，其在判定适宜栖息地方面的预测能力会因物种而异，对于分布范围广泛的物种，其预测能力甚至可能因区域不同而存在差异。 尽管上述地图代表了加州鱼类与野生动物局（CDFW）针对CWHR体系内各物种适宜栖息地分布的最优估算结果，但该类地图仍受以下若干因素限制：1）特定区域内植被地图的精度与空间分辨率；2）景观的动态变化特性：火灾与其他干扰事件对生境条件的改变频率，高于植被测绘项目的更新频率；3）专家知识库的时效性：尤其当物种适应土地与气候条件变化、以及其他物种种群分布发生迁移时，现有专家知识可能滞后；4）针对物种种群全分布范围代表性样区的专项调查频率；5）集合种群动态：该机制指种群在环境中因各类交互作用与响应而发生的分布迁移现象。 不得使用表征预测适宜栖息地的CWHR GIS数据，来判定某一特定点位是否存在特定物种。CWHR预测栖息地模型的命名依据为各物种所分配的4位字母数字混合CWHR标识符（亚种或其他亚分类单元的标识符为5位）。此外还设有"CWHR修订追踪表"，其中包含各物种的相关记录，包括其CWHR标识符、学名、通用名、种群分布范围以及栖息地模型数据的修订历史。 CWHR物种种群分布模型、预测栖息地模型、涵盖所有CWHR栖息地类型的全州分布GIS数据，以及"CWHR修订追踪表"，均可从https://www.wildlife.ca.gov/Data/CWHR下载获取。