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* Metric Name: Northern Spotted Owl Habitat Suitability Index  

* Tier: 2  

* Data Vintage: 2023  

* Unit Of Measure: 0−1; an index of habitat suitability  

* 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.

  

* 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. For RRK purposes, it has been clipped to the Northern
California region.

See Glenn et al. 2017 for more details on the methods.

  

* Credits: Regional Ecosystem Office (REO) - Northwest Forest Plan  Glenn, E.M., Lesmeister, D.B., Davis, R.J., Hollen, B., Poopatanpong, A. 2017. Estimating density of a territorial species in a dynamic landscape. Landscape Ecol. 32:563–579. Davis, Raymond J.; Lesmeister, Damon B.; Yang, Zhiqiang; Hollen, Bruce; Tuerler, Bridgette; Hobson, Jeremy; Guetterman, John; Stratton, Andrew. 2022. Northwest Forest Plan—the first 25 years (1994–2018): status and trends of northern spotted owl habitats. Gen. Tech. Rep. PNW-GTR-1003. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 38 p. . Phillips, S.J.; Anderson, R.P.; Shapire, R.E. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling. 190(3–4): 231–259. . Phillips, S.J.; Anderson, R.P.; Dudik, M.; Shapire, R.E.; Blair, M.E. 2017. Opening the black box: an open-source release of Maxent. Ecography. 40(7): 887–893. . Phillips, S.J.; Dudík, M.; Shapire, R.E. 2021. Maxent software for modeling species niches and distributions (Version 3.4.1). http://biodiversityinformatics.amnh.org/open_source/maxent. (31 January 2021).