Neighborhood and habitat effects on vital rates: expansion of the Barred Owl in the Oregon Coast Ranges

Abstract

In this paper, we modify dynamic occupancy models developed for detection-nondetection data to allow for the dependence of local vital rates on neighborhood occupancy, where neighborhood is defined very flexibly. Such dependence of occupancy dynamics on the status of a relevant neighborhood is pervasive, yet frequently ignored. Our framework permits joint inference about the importance of neighborhood effects and habitat covariates in determining colonization and extinction rates. Our specific motivation is the recent expansion of the Barred Owl (Strix varia) in western Oregon, USA, over the period 1990-2010. Because the focal period was one of dramatic range expansion and local population increase, the use of models that incorporate regional occupancy (sources of colonists) as determinants of dynamic rate parameters is especially appropriate. We began our analysis of 21 years of Barred Owl presence/nondetection data in the Tyee Density Study Area (TDSA) by testing a suite of six models that varied only in the covariates included in the modeling of detection probability. We then tested whether models that used regional occupancy as a covariate for colonization and extinction outperformed models with constant or year-specific colonization or extinction rates. Finally we tested whether habitat covariates improved the AIC of our models, focusing on which habitat covariates performed best, and whether the signs of habitat effects are consistent with a priori hypotheses. We conclude that all covariates used to model detection probability lead to improved AIC, that regional occupancy influences colonization and extinction rates, and that habitat plays an important role in determining extinction and colonization rates. As occupancy increases from low levels toward equilibrium, colonization increases and extinction decreases, presumably because there are more and more dispersing juveniles. While both rates are affected, colonization increases more than extinction decreases. Colonization is higher and extinction is lower in survey polygons with more riparian forest. The effects of riparian forest on extinction rates are greater than on colonization rates. Model results have implications for management of the invading Barred Owl, both through habitat alteration and removal.

Local Weather, Regional Climate, and Annual Survival of The Northern Spotted Owl

“…The 2-species approach used in our occupancy analysis allowed us to investigate the effects of Barred Owl presence on colonization and extinction rates of territorial Northern Spotted Owls while accounting for both Barred Owl and Spotted Owl detection rates (Bailey et al 2009, Yackulic et al 2012. Our results suggested that Barred Owls were having substantial negative effects on occupancy dynamics of Northern Spotted Owls, which was consistent with previous findings (Kelly et al 2003, Forsman et al 2011, Sovern et al 2014, Yackulic et al 2014.…”

Markov models for community dynamics allowing for observation error

“…In our model, the simplified assumption of the observation process would be relaxed easily because species distribution is calculated as a derived parameter. The effect of local community structure on sampling processes could be incorporated, for example, by altering the definition of species frequency such that species frequency ''near a fixed point'' is influenced or determined by occupancy states of neighboring points (e.g., Bled et al 2011a, b, Yackulic et al 2012.…”

“…Some of these processes (e.g., the dependence on environmental gradients mentioned in the previous paragraph) can be accommodated as relationships defining the probabilities of the community transition matrix as functions of environmental covariates. In addition, the species-specific transition probabilities may be written as time-specific functions of the species composition of the local neighborhood, where the neighborhood is defined by the grid points occurring within some specified distance of the focal point (e.g., Bled et al 2011a, b, Yackulic et al 2012. The motivation underlying such a model is that persistence of a species in a focal grid point may depend on the frequency of this species (rescue effect, Brown and Kodric-Brown 1977) or of competitor species in neighboring points.…”

Full Issue

“…In addition, the resulting Northern Spotted Owl habitat map performed reasonably well in map accuracy tests (Area Under the Curve (AUC) values of 0.78 to 0.88, and Spearman rank correlations .0.9; ). Thus, while caution is advised when using modeled habitat maps of this sort because it is difficult to derive precise representations of all of the habitat characteristics that are important to a species (Yackulic et al 2012, Loehle et al 2015, we believe that the map that we used in this analysis represented the best available range-wide map of Northern Spotted Owl nesting and roosting habitat.…”

“…The 2-species approach used in our occupancy analysis allowed us to investigate the effects of Barred Owl presence on colonization and extinction rates of territorial Northern Spotted Owls while accounting for both Barred Owl and Spotted Owl detection rates (Bailey et al 2009, Yackulic et al 2012, 2014. Our results suggested that Barred Owls were having substantial negative effects on occupancy dynamics of Northern Spotted Owls, which was consistent with previous findings (Kelly et al 2003, Forsman et al 2011, Sovern et al 2014, Yackulic et al 2014.…”