Piute Ground Squirrel Predicted Habitat - CWHR M069 [ds2527]

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（CWHR Predicted Habitat Models）表征了各物种在其分布范围内的潜在适宜栖息地区域。此类模型基于以下核心输入构建：1）全州范围内可获得的最优植被地图（FVEG）；2）表征物种分布范围的地理信息系统（GIS, Geographic Information System）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）与高（大于0.66），该分级基于物种三大生存必需条件——繁殖、觅食与遮蔽——的最大适宜性分值得出。需注意，此前版本的预测栖息地模型采用三大生存必需条件的平均分值，以获取各栖息地类型与群落阶段的综合适宜性评分。栖息地适宜性分值基于面积大于40英亩的栖息地斑块开发，其最优应用场景为面积大于200英亩的栖息地斑块。FVEG土地覆盖数据集整合了多项全州土地覆盖与区域植被测绘成果，这些成果于不同时期（大致为1990年至发布时）以不同分辨率完成，由加州林业与消防局（CALFIRE, California Department of Forestry and Fire Protection）汇编而成。FVEG采用该州各区域当前可得的最一致数据，并制定决策规则以处理重叠区域的图层优先级问题。同时通过跨源映射对照表，依据CWHR栖息地类型分类系统为各数据源赋予属性。将CWHR栖息地类型属性赋予FVEG数据集后，即可在物种分布范围内提取各物种的非零适宜栖息地区域，进而生成一系列物种专属的预测适宜栖息地地图。由于FVEG是全州各类土地覆盖评估成果的整合集合，其确定适宜栖息地的预测能力会因物种而异，对于分布广泛的物种甚至可能存在区域差异。尽管这些地图代表了加州鱼类与野生动物部（CDFW, California Department of Fish and Wildlife）对于CWHR系统内任意物种适宜栖息地存在情况的最优估算，但它们仍受限于若干因素：1）特定区域植被地图的精度与分辨率；2）景观的动态性——火灾与其他干扰事件改变栖息地条件的频率高于测绘工作的更新频率；3）专家知识的时效性，尤其是在物种适应不断变化的土地与气候条件以及其他物种分布范围发生转移的背景下；4）针对物种完整分布范围的代表性样本开展的物种专属调查频率；5）集合种群动态——即种群因各类相互作用与响应在环境中发生的位移。CWHR预测适宜栖息地的地理信息系统数据不可用于判定特定地点是否存在某一物种。CWHR预测栖息地模型以赋予各物种的4位字母数字式CWHR ID命名（亚种或其他亚分类单元的物种为5位）。此外还设有“CWHR修订跟踪表”，其中包含各物种的CWHR ID、学名、通用名、分布范围与栖息地模型数据的修订历史记录。CWHR物种分布模型、预测栖息地模型、涵盖所有CWHR栖息地类型全州分布的地理信息系统数据，以及CWHR修订跟踪表，均可从https://www.wildlife.ca.gov/Data/CWHR下载获取。