Merriam's Kangaroo Rat Predicted Habitat - CWHR M110 [ds2564]

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预测栖息地模型代表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）全州范围内可获取的最优植被地图（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。 栖息地适宜性等级划分为低（非零分值小于0.34）、中（0.34~0.66）与高（大于0.66），其划分依据为物种3类生存必需条件——繁殖、觅食与遮蔽——对应的最大适宜性分值。请注意，此前版本的预测栖息地模型曾采用3类生存必需条件的平均分值，以生成每种栖息地类型与阶段类别的整体适宜性评分。 栖息地适宜性评分基于面积大于40英亩的栖息地斑块制定，其最优解读场景为面积大于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，这些工作于不同时期（大致为1990年至发布之时）开展，分辨率各不相同，由加州森林与消防局（CALFIRE）汇编完成。FVEG采用加州各区域当前可获取的最新、最一致的数据，并制定了决策规则以处理重叠区域中各数据图层的优先级问题。通过映射对照表（Crosswalks），依据CWHR栖息地类型分类系统为各类数据源赋予属性。将FVEG与CWHR栖息地类型进行属性关联后，即可提取物种分布范围内具有非零适宜性分值的区域，进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整合了全州范围内多种不同的土地覆盖评估成果，因此其在确定适宜栖息地方面的预测能力会因物种而异，对于分布广泛的物种甚至可能因区域不同而存在差异。 尽管这些地图体现了加州鱼类与野生动物部（CDFW）针对CWHR体系内任意物种的适宜栖息地存在情况的最优估算结果，但它们仍受到多项因素的限制：1）特定区域内植被地图的精度与分辨率；2）景观的动态特性——火灾与其他干扰事件改变环境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、以及其他物种种群分布发生转移的背景下；4）针对物种整个分布范围的代表性样本开展的物种特异性调查频率；5）集合种群动态（metapopulation dynamics），即各类相互作用与响应导致物种种群在其栖息环境中发生的迁移变化。 CWHR预测适宜栖息地的地理信息系统数据不应被用于判定某一特定地点是否存在某一物种。 CWHR预测栖息地模型以分配给每个物种的4位字母数字CWHR ID命名（亚种或其他亚分类群的物种则使用5位ID）。 此外还设有“CWHR修订跟踪表”，其中包含每个物种的相关记录，包括其CWHR ID、学名、通用名、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栖息地类型全州分布的地理信息系统数据，以及CWHR修订跟踪表，均可在https://www.wildlife.ca.gov/Data/CWHR 网站下载。