Fatalities of migratory bats, many of which use low frequency (<35 kHz; LowF) echolocation calls, have become a primary environmental concern associated with wind energy development. Accordingly, strategies to improve compatibility between wind energy development and conservation of bat populations are needed. We combined results of continuous echolocation and meteorological monitoring at multiple stations to model conditions that explained presence of LowF bats at a wind energy facility in southern California. We used a site occupancy approach to model nightly LowF bat presence while accounting for variation in detection probability among echolocation detectors and heights. However, we transposed the spatial and temporal axes of the conventional detection history matrix such that occupancy represented proportion of nights, rather than monitoring points, on which LowF bats were detected. Detectors at 22 m and 52 m above ground had greater detection probabilities for LowF bats than detectors at 2 m above ground. Occupancy of LowF bats was associated with lower nightly wind speeds and higher nightly temperatures, mirroring results from other wind energy facilities. Nevertheless, we found that building separate models for each season and considering solutions with multiple covariates resulted in better fitting models. We suggest that use of multiple environmental variables to predict bat presence could improve efficiency of turbine operational mitigations (e.g., changes to cut‐in speeds) over those based solely on wind speed. Increased mitigation efficiencies could lead to greater use of mitigations at wind energy facilities with benefits to bat populations. © 2011 The Wildlife Society.
A basic sampling scheme is proposed to estimate the proportion of sampled units (Spotted Owl Habitat Areas (SOHAs) or randomly sampled 1000-acre polygon areas (RSAs)) occupied by spotted owl pairs. A bias adjustment for the possibility of missing a pair given its presence on a SOHA or RSA is suggested. The sampling scheme is based on a fixed number of visits to a sample unit (a SOHA or RSA) in which the occupancy is to be determined. Once occupancy is determined, or the maximum number of visits is reached, the sampling is completed for that unit. The resulting data are summarized as a set of independent Bernoulli trials; a zero (no occupancy) or one (occupancy) is recorded for each unit. The occupancy proportion is the sum of these Bernoulli trials divided by the sample size. The bias adjustment estimates this occupancy proportion for the estimated number of units on which a pair of owls was present but not detected. The bias adjustment requires the recording of the number of the visit during which occupancy was first detected. The distributional assumptions are checked with five different sets of data.
Tropical forests are important storehouses of carbon and biodiversity. In isolated island ecosystems such as the Hawaiian Islands, relative dominance of native and nonnative tree species may influence patterns of forest carbon stocks and biodiversity. We determined aboveground carbon density (ACD) across a matrix of lava flows differing in age, texture, and vegetation composition (i.e., native or nonnative dominated) in wet lowland forests of Hawaii Island. To do this at the large scales necessary to accurately capture the inherent heterogeneity of these forests, we collected LiDAR data across areas of interest and developed relationships between LiDAR metrics and field-based estimates of forest ACD. This approach enabled us to inventory, rather than merely sample, the entire populations (i.e., forests) of interest. Native Hawaiian wet lowland forests exhibited ACD values similar to those of intact tropical forests elsewhere. In general, ACD of these forests increased with increasing lava flow age, but patterns differed between native and nonnative forest stands. On the youngest lavas, native-dominated forest ACD averaged < 60 Mg/ha, compared to -100 Mg C/ha for nonnative-dominated forests. This difference was due to the presence of the nonnative, N2-fixing trees F. moluccana and C. equisetifolia in the nonnative-dominated forest stands, as well as the corresponding absence of N2-fixing trees in native-dominated forest stands. Following -500 years of primary succession and thereafter, however, both forest types exhibited ACD values averaging -130 Mg C/ha, although it took nonnative forests only 75 80 years of post-establishment succession to reach those values. Given the large areas of early-successional M. polymorpha-dominated forest on young lava flows, further spread of F. moluccana and C. equisetifolia populations would likely increase ACD stocks but would constitute a significant erosion of the invaluable contribution of Hawaii's native ecosystems to global biodiversity.
Carnivores are important elements of biodiversity, not only because of their role in transferring energy and nutrients, but also because they influence the structure of the communities where they occur. The fisher Martes pennanti is a mammalian carnivore that is associated with late-successional mixed forests in the Sierra Nevada in California, and is vulnerable to the effects of forest management. As a candidate for endangered species status, it is important to monitor its population to determine whether actions to conserve it are successful. We implemented a monitoring program to estimate change in occupancy of fishers across a 12,240-km2 area in the southern Sierra Nevada. Sample units were about 4 km apart, consisting of six enclosed, baited track-plate stations, and aligned with the national Forest Inventory and Analysis grid. We report here the results of 8 y (2002–2009) of sampling of a core set of 223 sample units. We model the combined effects of probability of detection and occupancy to estimate occupancy, persistence rates, and trend in occupancy. In combined models, we evaluated four forms of detection probability (1-group and 2-group both constant and varying by year) and nine forms of probability of occupancy (differing primarily by how occupancy and persistence vary among years). The best-fitting model assumed constant probability of occupancy, constant persistence, and two detection groups (AIC weight = 0.707). This fit the data best for the entire study area as well as two of the three distinct geographic zones therein. The one zone with a trend parameter found no significant difference from zero for that parameter. This suggests that, over the 8-y period, that there was no trend or statistically significant variations in occupancy. The overall probability of occupancy, adjusted to account for uncertain detection, was 0.367 (SE = 0.033) and estimates were lowest in the southeastern zone (0.261) and highest in the southwestern zone (0.583). Constant and positive persistence values suggested that sample units rarely changed status from occupied to unoccupied or vice versa. The small population of fishers in the southern Sierra (probably <250 individuals) does not appear to be decreasing. However, given the habitat degradation that has occurred in forests of the region, we favor continued monitoring to determine whether fisher occupancy increases as land managers implement measures to restore conditions favorable to fishers.
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