Northern Spotted Owl Suitable Habitat

These data are derived using analysis described in Glenn et al. (2017). The authors have **** developed a landscape-scale model to predict the distribution and density of the (territorial species) northern spotted owl (Strix occidentalis caurina ) . This model results in a rangewide relative habitat suitability estimates, on a pixel by pixel basis, using forest vegetation, topographic, and climate data. The ability to adequately predict territorial species distributions and densities across landscapes and through time is important for implementing effective conservation strategies as well as monitoring the success of those strategies in a spatially extensive and cost'€“effective manner.

This method and the resulting data have been developed by the Northwest Forest Plan (NWFP) Monitoring Program , a federal interagency monitoring program. The NWFP is governed by the Regional Interagency Executive Committee (RIEC), a consortium of federal land and resource management agencies in the Pacific Northwest, with support from agency personnel appointed to the Senior Managers Group and Regional Ecosystem Office staff.

The Northern Spotted Owl (NSO) Monitoring Program conducts long-term monitoring of NSO populations, forests, and habitat to determine the effectiveness of federal forest management on maintaining and restoring habitat conditions necessary to support viable populations of NSO on federally-administered forests throughout its range. Main objectives are to:

  • Track status and trends of NSO populations on federal forests within its geographic range in the United States.
  • Track status and trends in the amount and distribution of NSO forest cover types and habitat on federal forests.

This subspecies is found in the Northern California Region.

Data and Resources

Additional Info

Field Value
Last Updated January 17, 2025, 06:42 (UTC)
Created January 17, 2025, 06:42 (UTC)
category /Biodiversity Conservation/Focal Species/Birds
collection_name California Landscape Metrics
creation_method The authors used the program MaxEnt, version 3.3.3k (Phillips et al. 2006) to produce relative habitat suitability models and maps for the six modeling regions (two which include the northern California portion of the range of this subspecies). MaxEnt estimates relative environmental suitability for species presence by using a machine learning process to develop algorithms that model the most uniform distribution (maximum entropy) of averaged environmental conditions at known species locations compared to a large randomly generated sample of available locations from within the modeling region (Phillips et al. 2006; Phillips and Dudik 2008). Owl presence data for model training and testing was based on thousands of nest or day roost locations from 1993. These data were compiled from standardized survey protocols developed to identify spotted owl territorial sites in forested landscapes. The authors identified 9 environmental predictor variables for inclusion in the model that have demonstrated support for influencing spotted owl habitat selection and site occupancy. Amount and spatial arrangement of nesting/roosting forest cover are known to influence owl space use and fitness, thus four of our variables quantified amount and configuration of nesting/roosting cover at the nest patch (200 m radius) and territory scale (600'€“1900 m radii). The remaining 5 variables were abiotic: elevation, topographic position, average minimum January temperature, average maximum August temperature, and average annual precipitation. The modeled output covers the entire range of Northern Spotted Owls: Washington, Oregon, and northern California within the Northwest Forest Plan (NWFP) boundary. See Glenn et al. 2017 for more details on the methods.
data_units Binary; 0 = not suitable, 1 = suitable.
data_vintage 2023
encoding utf8
file_name NSO_SuitableHabitat_2023_202401_T2_v5
format GeoTiff
harvest_object_id d4f080b4-ef9a-4d94-87a6-bcae7a480f99
harvest_source_id a2637971-af12-457f-ae4a-831d2202a539
harvest_source_title WIFIRE Commons
maximum_value 1.0
metric_definition_and_relevance These data are derived using analysis described in Glenn et al. (2017). The authors have **** developed a landscape-scale model to predict the distribution and density of the (territorial species) northern spotted owl _(Strix occidentalis caurina_ ) . This model results in a rangewide relative habitat suitability estimates, on a pixel by pixel basis, using forest vegetation, topographic, and climate data. The ability to adequately predict territorial species distributions and densities across landscapes and through time is important for implementing effective conservation strategies as well as monitoring the success of those strategies in a spatially extensive and cost'€“effective manner. This method and the resulting data have been developed by the Northwest Forest Plan (NWFP) Monitoring Program , a federal interagency monitoring program. The NWFP is governed by the Regional Interagency Executive Committee (RIEC), a consortium of federal land and resource management agencies in the Pacific Northwest, with support from agency personnel appointed to the Senior Managers Group and Regional Ecosystem Office staff. The Northern Spotted Owl (NSO) Monitoring Program conducts long-term monitoring of NSO populations, forests, and habitat to determine the effectiveness of federal forest management on maintaining and restoring habitat conditions necessary to support viable populations of NSO on federally-administered forests throughout its range. Main objectives are to: * Track status and trends of NSO populations on federal forests within its geographic range in the United States. * Track status and trends in the amount and distribution of NSO forest cover types and habitat on federal forests. This subspecies is found in the Northern California Region.
minimum_value 0.0
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tier 2