Factors Associated with the Detectability of Owls in South American Temperate Forests: Implications for Nocturnal Raptor Monitoring
Total Page：16
File Type：pdf, Size：1020Kb
The Journal of Wildlife Management 78(6):1078–1086; 2014; DOI: 10.1002/jwmg.740 Research Article Factors Associated with the Detectability of Owls in South American Temperate Forests: Implications for Nocturnal Raptor Monitoring JOSE´ TOMA´ S IBARRA,1 Centre for Applied Conservation Research, Department of Forest and Conservation Sciences, University of British Columbia, 2424 Main Mall, Vancouver, British Columbia, Canada V6T 1Z4; and The Peregrine Fund, 5668 W Flying Hawk Lane, Boise, ID 83709, USA KATHY MARTIN, Centre for Applied Conservation Research, Department of Forest and Conservation Sciences, University of British Columbia, 2424 Main Mall, Vancouver, British Columbia, Canada V6T 1Z4; and Environment Canada, Pacific Wildlife Research Centre, 5421 Robertson Road, R.R. 1, Delta, British Columbia, Canada V4K 3N2 TOMA´ S A. ALTAMIRANO, Fauna Australis Wildlife Laboratory, Department of Ecosystems and the Environment, Pontificia Universidad Cato´lica de Chile, Vicun˜a Mackenna 4860 P.O. Box 306-22, Macul, Santiago, Chile F. HERNA´ N VARGAS, The Peregrine Fund, 5668 W Flying Hawk Lane, Boise, ID 83709, USA CRISTIA´ N BONACIC, Fauna Australis Wildlife Laboratory, Department of Ecosystems and the Environment, Pontificia Universidad Cato´lica de Chile, Vicun˜a Mackenna 4860 P.O. Box 306-22, Macul, Santiago, Chile ABSTRACT Owls occur at relatively low densities and are cryptic; thus, monitoring programs that estimate variation in detectability will improve inferences about their presence. We investigated temporal and abiotic sources of variation associated with detection probabilities of rufous-legged owls (Strix rufipes), a threatened forest specialist, and austral pygmy-owls (Glaucidium nana), a habitat generalist, in temperate forests of southern Chile. We also assessed whether detection of 1 species was related to the detection of the other species. During 2011–2013, we conducted 1,145 broadcast surveys at 101 sampling units established along an elevational gradient located inside and outside protected areas. We used a multi-season occupancy framework for modeling occupancy (c) and detection (p), and ranked models using an information-theoretic approach. We recorded 292 detections of rufous-legged owls and 334 detections of austral pygmy-owls. Occupancy was positively associated with elevation for rufous-legged owls but constant (i.e., did not vary with covariates) for pygmy-owls. Detectability for both owls increased with greater moonlight and decreased with environmental noise, and for pygmy-owls greater wind speed decreased detectability. The probability of detecting pygmy- owls increased nonlinearly with number of days since the start of surveys and peaked during the latest surveys of the season (23 Jan–7 Feb). Detection of both species was positively correlated with the detection of the other species. We suggest both species should be surveyed simultaneously for a minimum of 3–4 times during a season, survey stations should be located away from noise, and observers should record the moon phase and weather conditions for each survey. Ó 2014 The Wildlife Society. KEY WORDS austral pygmy-owl, Chile, Glaucidium nana, moonlight, occupancy, Patagonia, rufous-legged owl, Strix rufipes. Compared with other avian groups, owls are difficult to study et al. 1991, Hardy and Morrison 2000, Kissling et al. 2010). and are typically not covered by land-bird monitoring Unfavorable detection conditions such as wind speed, programs because of their low densities, elusive behavior, and environmental noise, and cloud cover can influence the nocturnal habits (Fuller and Mosher 1987). As a result, ability of researchers to detect owls (Fisher et al. 2004, inferences about the spatial and temporal variation in owl Andersen 2007) and lunar cycles appear to influence occurrence could be misleading if researchers do not account communication and activity patterns of owls and their prey for incomplete detectability or false absences (Wintle et al. (Clarke 1983, Penteriani et al. 2010). Furthermore, the calling 2005, MacKenzie et al. 2006). Detectability of owls may be rates of owls may be affected by the risk of being detected by affected by several temporal, abiotic, and biotic factors an intraguild predator (Lourenc¸o et al. 2013), or by the (Andersen 2007). For example, intraseasonal breeding presence of a dominant owl in the area (Olson et al. 2005). phenology and social status, which are commonly correlated Thus the number of sampling units occupied by an owl species with prey availability, can affect calling rates of owls (Morrell of interest and their detection probabilities can be under- estimated if environmental or social factors are not considered. Few studies have investigated habitat use and abundance of Received: 15 August 2013; Accepted: 21 April 2014 Published: 7 July 2014 owls in the temperate forests of South America and none have examined occupancy and detectability (but see Martı´nez and 1E-mail: [email protected] Jaksic 1996, Ibarra et al. 2012). Two species, the rufous-legged 1078 The Journal of Wildlife Management 78(6) owls (Strix rufipes) and austral pygmy-owls (Glaucidium nana), estimates for addressing research questions and may improve inhabit an eco-region that is among the most threatened on earth because nearly 60% of forest cover has been lost because monitoring programs for owls in the region (e.g., Andersen of large-scale farming and plantation forestry (Lara 1996, 2007, Manning 2011). Myers et al. 2000). In Chile, the great majority of remaining forests inhabited by these owls are located in high-elevation STUDY AREA protected areas, whereas forests in lowland areas have varying We conducted our fieldwork within the Araucarias levels of degradation and fragmentation (Armesto et al. 1998). Biosphere Reserve (UNESCO 2010). Specifically, we We examined factors associated with the probability of studied owls in the Villarrica watershed in the Andean detecting rufous-legged and austral pygmy-owls in southern zone of the Araucanı´a Region (398150S718W), northern Chile to improve monitoring protocols for these raptors. Patagonia, Chile (Fig. 1). We chose this watershed because Rufous-legged owls and austral pygmy-owls are the most accessibility was good and its landscapes were representative abundant of the 5 species of owls occurring in the Andean of Andean temperate forests. The climate was temperate portion of temperate forests; therefore, we anticipated we could with a short dry season (<4 months) and a mean annual obtain a sufficient number of detections to model detectability precipitation of 1,945 mm (Di Castri and Hajek 1976). for these 2 species. Rufous-legged owls are medium-sized forest Forests in the area ranged from 200 m to 1,500 m in elevation specialists that hunt and nest only within forests (Trejo and were dominated by deciduous Nothofagus species at lower et al. 2006). They also are one of the least known owls in South altitudes and mixed deciduous with coniferous Araucaria America and are declining because of increased habitat alteration araucana at higher elevations (Gajardo 1993). Most public (Martı´nez 2005). Austral pygmy-owls are small habitat protected areas at high elevations (>700 m) were forested, generaliststhathuntand/ornestwithinforests,shrublands, whereas lowlands (<700 m) were dominated by agriculture andaroundhumanhabitation(Jime´nez and Jaksic 1989, Trejo and human settlement. However, several private protected et al. 2006). They are abundant and common throughout their areas were established during recent decades in the lowland distribution in Chile (Jime´nez and Jaksic 1989). Despite their areas. wide distribution and local abundance, the ecology of austral pygmy-owls is still poorly known. We estimated owl METHODS detectability a s a function of survey-specific temporal, abiotic, and biotic conditions (MacKenzie et al. 2006). Quantifying sour- Nocturnal Raptor Surveys We assessed detectability of owls during 2 nesting seasons ces of variation in detection rates can provide more reliable (mid-Oct to early Feb) at 95 sampling units during Figure 1. Distribution of 101 sampling units in the Villarrica watershed used to survey rufous-legged owls and austral pygmy-owls in a mountainous landscape in Andean temperate forests of the Araucanı´a Region (398S), Chile. Ibarra et al. Owl Detectability in South America 1079 2011–2012 and 101 units during 2012–2013 (i.e., 6 new study period (MacKenzie et al. 2003). We modeled the data units) in an area of 2,585 km2 (Fig. 1). Sampling units for each owl species independently (i.e., single-species spanned the gradient of the forest elevational range from occupancy models; MacKenzie et al. 2006). We estimated 221 m to 1,361 m (near the tree line). This gradient probabilities of occupancy (c) and detection (p) using the represented a variety of habitat conditions from degraded program unmarked, which allowed the response variables to and patchy forests to zones comprising continuous forests at be functions of covariates (Fiske and Chandler 2011). For c, higher elevations (Ibarra et al. 2012). We defined the we considered 2 covariates across the altitudinal gradient: sampling unit as the area within a 500-m detection radius of mean elevation of the unit (meters above sea level/1,000), the sampling point, which corresponded to the area within and Pa, a binary covariate indicating the sampling unit was which an owl could have heard a vocal lure during a survey located within 500 m of a protected area (1) or not (0). To (Sutherland et al. 2010). Using ArcGIS 10.1 (Environmental identify potential covariates that may be associated with Systems Research Institute, Inc., Redlands, CA), we detectability, we used covariates that were correlated with identified all the headwaters of smaller basins that were owl detection in other studies (Morrell et al. 1991; Clark and accessible by rural roads or hiking trails within the Villarrica Anderson 1997; Hardy and Morrison 2000; Crozier et al. watershed. We randomly selected 13 of these 19 basins and 2005, 2006; Wintle et al. 2005). We modeled the probability placed the first sampling unit within all basins near the of detection (p) assessing 9 temporal, abiotic, and biotic headwater (within 1 km of the tree line).