遇见数据集

Black Bear Predicted Habitat - CWHR M151 [ds2602]

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ArcGIS Hub2026-03-03 更新2026-07-28 收录
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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预测生境模型(CWHR Predicted Habitat Models)表征了各物种种群分布范围内的潜在适宜生境区域。该类模型基于以下核心输入项构建:1)全州范围内可获取的最优植被地图(FVEG);2)地理信息系统(Geographic Information System, GIS)数据,用于表征物种种群分布范围;3)CWHR数据库中收录的700余种陆生脊椎动物的生境适宜性数值。 生境适宜性等级划分为低(非零值小于0.34)、中(0.34~0.66)与高(大于0.66),该划分基于物种3类生存必需条件(繁殖、觅食与隐蔽)的最大适宜性数值。请注意,此前版本的该类预测生境模型曾采用3类生存必需条件的平均值,以计算每种生境类型与发育阶段类别的综合适宜性得分。生境适宜性得分的生成基于面积大于40英亩的生境斑块,其解读最优适配于面积大于200英亩的生境斑块。 FVEG土地覆盖数据集由加州林业与消防局(California Department of Forestry and Fire Protection, CALFIRE)汇编整合,整合了多项全州尺度与区域尺度的土地覆盖及植被测绘工作,这些工作开展于1990年左右至发布当日的不同时段,且采用了多种分辨率。FVEG采用加州各区域可获取的最新且一致的数据集。研究人员制定了决策规则,用于管控重叠区域中各数据图层的优先级。研究人员采用跨源属性映射表(Crosswalks),依据CWHR生境类型分类系统为各类数据源赋予对应属性。将FVEG数据集关联CWHR生境类型后,即可提取各物种种群分布范围内具有非零适宜性值的区域,从而生成一系列针对特定物种的预测适宜生境地图。 由于FVEG数据集整合了全州范围内多项不同的土地覆盖评估工作,因此其判定适宜生境的预测能力会因物种而异,对于分布范围广泛的物种,甚至可能因区域不同而存在差异。尽管此类地图代表了加州鱼类与野生动物部(California Department of Fish and Wildlife, CDFW)针对CWHR系统内任一物种的适宜生境存在情况所做出的最优评估,但该类地图仍受多项因素限制:1)特定区域内植被地图的精度与分辨率;2)景观的动态性:火灾与其他干扰事件改变生境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:尤其是在物种适应土地与气候条件变化、其他物种种群分布发生转移的背景下;4)针对物种种群全分布范围代表性样地的专项调查频率;5)集合种群动态:该概念指种群因各类相互作用与响应而在其生存环境中发生的分布转移。 表征预测适宜生境的CWHR地理信息系统数据不得用于判定某一特定地点是否存在某一物种。CWHR预测生境模型的命名依据为分配给各物种的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”,其中收录了各物种的相关记录,包括其CWHR标识符、学名、通用名以及种群分布与生境模型数据的修订历史。 CWHR物种种群分布模型、预测生境模型、覆盖全州所有CWHR生境类型分布的地理信息系统数据,以及CWHR修订追踪表,均可从https://www.wildlife.ca.gov/Data/CWHR 下载获取。

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2026-03-03
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