Effective species management and conservation benefit from knowledge of species distribution and status. Surveys to obtain that information often involve replicate sampling, which increases survey effort and costs. We simultaneously modeled species distribution, abundance and spatial correlation, and compared the uncertainty in replicate abundance estimates of the endangered palila (Loxioides bailleui) using hierarchical generalized additive models with a soap film smoother that incorporated random effects for visit. Based on survey coverage and detections, we selected the 2017 point-transect distance sampling survey on Mauna Kea, Hawai'i Island, for our modeling. Our modeling approach allowed us to account for imperfect detections, control the effects of boundary features, and generate visit-specific density surface maps. We found that visit-specific smooths were nearly identical, indicating that little information was gained from a subsequent visit, and that most of the estimator uncertainty was derived from within-visit variability. Scaling back the palila survey to a single visit would halve the survey effort and logistical costs and increase efficiencies in data management and processing. Changing the sampling protocol warrants careful consideration and our findings may help management and regulatory agencies by maximizing efficiency and minimizing costs of surveying protocols, while providing guidelines on how to best collect information critical to species' conservation.

The Samoan swallowtail butterfly (Papilio godeffroyi) has become restricted to Tutuila Island, American Samoa. Factors driving its extirpation on other islands may be partly due to the availability and suitability of habitat, given the singular association we observed of P. godeffroyi with its host plant, Micromelum minutum. We expected that as a host plant specialist, P. godeffroyi might respond to variation in the physical traits and habitat context of M. minutum, which could help identify conservation opportunities throughout its present and former range. Because the ecology of P. godeffroyi is largely unknown, we conducted systematic surveys during 15 months in 2013 and 2014 on Tutuila to investigate its reproductive response to the physical and phenological variability of individual host trees and to the structural and geographical variability of the stands in which they occurred. We searched foliage for eggs, larvae, and pupae and monitored seasonal trends in herbivory and production of leaves, flowers, and fruits on 117 host trees in 8 rainforest stands, mostly within the National Park of American Samoa (NPSA), starting in March 2013 and ending in August 2014. We observed high variability in butterfly reproductive output between individual trees and stands, due largely to a strong negative relationship between leaf biomass (at both tree and stand levels) and oviposition density (number of eggs per foliar biomass) and frequency (number of eggs per survey). Distribution patterns of larvae and pupae were less distinct but generally followed trends in oviposition. Our findings indicate that the butterfly is reproducing widely across Tutuila and is likely to respond positively to management to increase the availability of small host trees in low-density stands. Thus, the species is a good candidate for conservation management focusing on habitat.

Effective species management and conservation require knowledge of species distribution and status. We used point-transect distance sampling surveys of the endangered palila (Loxioides bailleui), a honeycreeper currently found only on the Island of Hawai'i, USA, to generate robust estimates of total abundance and simultaneously model the distribution, abundance, and spatial correlation of the species as a density surface model (DSM). Point-transect distance sampling is a widely applied method to estimate bird densities accounting for imperfect detection probability. For the DSM we used a generalized additive model framework and soap film smoothers to control the effects of boundary features. This modeling approach allowed us to account for imperfect detection and propagate detection probability uncertainty. We compared the uncertainty in palila abundance estimates using standard point-transect distance sampling to estimates from the DSM. The DSM, accounting for both distance-sampling-derived detection probability variance and the generalized additive model density estimate variance, did not improve population estimator precision; however, it provided insight into the species' distribution, density, and uncertainty. We also applied excursion sets analysis to objectively identify areas where the species occurs in high densities. The 2017 global population of <2,000 individuals was limited to an excursion area of 1,500 ha. Our findings can help management and regulatory agencies by simultaneously mapping a species' distribution and density, improving survey protocols, and providing information important to species conservation.

Abstract A major advancement in the use of radio telemetry has been the development of automated radio tracking systems (ARTS), which allow animal movements to be tracked continuously. A new ARTS approach is the use of a network of simple radio receivers (nodes) that collect radio signal strength (RSS) values from animal‐borne radio transmitters. However, the use of RSS‐based localization methods in wildlife tracking research is new, and analytical approaches critical for determining high‐quality location data have lagged behind technological developments. We present an analytical approach to optimize RSS‐based localization estimates for a node network designed to track fine‐scale animal movements in a localized area. Specifically, we test the application of analytical filters (signal strength, distance among nodes) to data from real and simulated node networks that differ in the density and configuration of nodes. We evaluate how different filters and network configurations (density and regularity of node spacing) may influence the accuracy of RSS‐based localization estimates. Overall, the use of signal strength and distance‐based filters resulted in a 3‐ to 9‐fold increase in median accuracy of location estimates over unfiltered estimates, with the most stringent filters providing location estimates with a median accuracy ranging from 28 to 73 m depending on the configuration and spacing of the node network. We found that distance filters performed significantly better than RSS filters for networks with evenly spaced nodes, but the advantage diminished when nodes were less uniformly spaced within a network. Our results not only provide analytical approaches to greatly increase the accuracy of RSS‐based localization estimates, as well as the computer code to do so, but also provide guidance on how to best configure node networks to maximize the accuracy and capabilities of such systems for wildlife tracking studies.

Four endemic species of wetland-dependent waterbirds occur on the main Hawaiian Islands, all of which have experienced sharp population declines and are listed as endangered species. Twice per year, state-wide surveys are conducted to count waterbirds, but these surveys are evaluated only infrequently. We used a state-space approach to evaluate long-term (1986-2016) and short-term (2006-2016) trends and current distribution and abundance of endemic Hawaiian waterbirds. The most numerous species was the Ae'o, or Hawaiian Stilt (Himantopus mexicanus knudseni), with a 5-year estimated average abundance of 1,932 individuals, followed by 'Alae Ke'oke'o, or Hawaiian Coot (Fulica alai), with 1,815 individuals, Alae 'Ula, or Hawaiian Common Gallinule (Gallinula galeata sandvicensis) with 927 individuals, and the Koloa Maoli, or Hawaiian Duck (Anas wyvilliana) with 931 individuals. All four species had positive trends over the long-term, but short-term and island specific trends were more variable, and in some cases negative. These results provide valuable information to help guide management of Hawaii's threatened and endangered endemic waterbirds.

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Questions (a) Have Metrosideros polymorpha trees become re-established in Hawaiian forests previously impacted by canopy dieback in the 1970s? (b) Has canopy dieback expanded since the 1970s? (c) Can spatial patterns from this dieback be correlated with habitat factors to model future dieback in this area? Study Site An 83,603 ha study area on the eastern slopes of Mauna Loa and Mauna Kea volcanoes on the island of Hawaii, USA. Methods We analyzed very-high-resolution imagery to assess status of Metrosideros polymorpha forests across the eastern side of the island of Hawaii. We generated 1,170 virtual vegetation plots with a 100-m radius; 541 plots in areas mapped in 1977 with trees dead or mostly defoliated (dieback), and 629 plots in adjacent wet forest habitat, previously mapped as non-dieback condition. In each plot we estimated the frequency of M. polymorpha trees that were dead or mostly defoliated, and the frequency of trees with healthy crowns. These results were combined with habitat data to produce a spatial model depicting probability of canopy dieback within the study area. Results Seventy-nine percent of plots mapped in 1977 in dieback condition recovered their canopy and were now considered in non-dieback condition. Ninety-one percent of plots in previous non-dieback areas were found to still have a healthy M. polymorpha canopy in 2015. A spatial model allowed us to identify areas within the study area with high, medium, and low probability of experiencing this same type of canopy dieback in the future. Conclusions Most former dieback areas mapped within the study area in 1977 now show recovery of the tree canopy through growth of new cohorts of young M. polymorpha trees. This suggests these forest communities are resilient to this type of canopy loss and tree death so long as other factors do not disrupt the natural regeneration process.

ABSTRACT In Hawaii and other oceanic islands with few native land mammals, black rats (Rattus rattus) are among the most damaging invasive vertebrate species to native forest bird populations and habitats, due to their arboreal behavior and generalist foraging habits and habitat use. We evaluated the nesting response of Hawaii Elepaio (Chasiempis sandwichensis; Monarchidae), a generalist insectivore, to the removal of black rats using rodenticide in a before-after-control-impact study in high- and low-elevation mesic montane habitat recovering from long-term damage from introduced ungulates and weeds. We monitored nesting success and rat abundance during 2015–2016 before applying rodenticide bait in 2017 to remove rats from two 700 × 700 m treatment plots that were paired with 2 nontreatment plots of the same size. Rat abundance was reduced by 90% during treatment, with combined variables treatment and elevation best explaining the change using GLM methods and AIC model selection. The daily survival rate (DSR) of nests (n = 191) was greater on treated plots after rodenticide application (mean ± SE = 0.980 ± 0.004 treatment; 0.964 ± 0.004 nontreatment), modeled nest success increased from 29% to 50%, and apparent nest success (number of successful nests per total nests) increased from 37% to 52%. The most informative model for predicting DSR included the effect of treatment. Predation by rats was documented at 3 of 16 nests using video surveillance, and we observed additional evidence of rat predation during in-person nest monitoring. Rats targeted adults on the nest and sometimes removed intact eggs, leaving little trace of their activity. Our results demonstrate that reducing rat predation can immediately improve the nesting success of even a common bird species in habitat with a long history of forest restoration. Sustained predator control may be critical to accelerating the recovery of native forest bird communities.

Multi-state occupancy modeling can often improve assessments of habitat use and site quality when animal activity or behavior data are available. We examine the use of the approach for evaluating foraging habitat suitability of the endangered Hawaiian hoary bat (Lasiurus cinereus semotus) from classifications of site occupancy based on flight activity levels and feeding behavior. In addition, we used data from separate visual and auditory sources, namely thermal videography and acoustic (echolocation) detectors, jointly deployed at sample sites to compare the effectiveness of each method in the context of occupancy modeling. Video-derived observations demonstrated higher and more accurate estimates of the prevalence of high bat flight activity and feeding events than acoustic sampling methods. Elevated levels of acoustic activity by Hawaiian hoary bats were found to be related primarily to beetle biomass in this study. The approach may have a variety of applications in bat research, including inference about species-resource relationships, habitat quality and the extent to which species intensively use areas for activities such as foraging.

Accurate estimates of the distribution and abundance of endangered species are crucial to determine their status and plan recovery options, but such estimates are often difficult to obtain for species with low detection probabilities or that occur in inaccessible habitats. The Puaiohi (Myadestes palmeri) is a cryptic species endemic to Kauaʻi, Hawai‘i, and restricted to high elevation ravines that are largely inaccessible. To improve current population estimates, we developed an approach to model distribution and abundance of Puaiohi across their range by linking occupancy surveys to habitat characteristics, territory density, and landscape attributes. Occupancy per station ranged from 0.17 to 0.82, and was best predicted by the number and vertical extent of cliffs, cliff slope, stream width, and elevation. To link occupancy estimates with abundance, we used territory mapping data to estimate the average number of territories per survey station (0.44 and 0.66 territories per station in low and high occupancy streams, respectively), and the average number of individuals per territory (1.9). We then modeled Puaiohi occupancy as a function of two remote-sensed measures of habitat (stream sinuosity and elevation) to predict occupancy across its entire range. We combined predicted occupancy with estimates of birds per station to produce a global population estimate of 494 (95% CI 414–580) individuals. Our approach is a model for using multiple independent sources of information to accurately track population trends, and we discuss future directions for modeling abundance of this, and other, rare species.

SummaryEstimating population abundances and patterns of change over time are important in both ecology and conservation. Trend assessment typically entails fitting a regression to a time series of abundances to estimate population trajectory. However, changes in abundance estimates from year-to-year across time are due to both true variation in population size (process variation) and variation due to imperfect sampling and model fit. State-space models are a relatively new method that can be used to partition the error components and quantify trends based only on process variation. We compare a state-space modelling approach with a more traditional linear regression approach to assess trends in uncorrected raw counts and detection-corrected abundance estimates of forest birds at Hakalau Forest National Wildlife Refuge, Hawai‘i. Most species demonstrated similar trends using either method. In general, evidence for trends using state-space models was less strong than for linear regression, as measured by estimates of precision. However, while the state-space models may sacrifice precision, the expectation is that these estimates provide a better representation of the real world biological processes of interest because they are partitioning process variation (environmental and demographic variation) and observation variation (sampling and model variation). The state-space approach also provides annual estimates of abundance which can be used by managers to set conservation strategies, and can be linked to factors that vary by year, such as climate, to better understand processes that drive population trends.

Both of the 2 passerines endemic to Nihoa Island, Hawai'i, USA-the Nihoa Millerbird (Acrocephalus familiaris kingi) and Nihoa Finch (Telespiza ultima)-are listed as endangered by federal and state agencies. Their abundances have been estimated by irregularly implemented fixed-width strip-transect sampling from 1967 to 2012, from which area-based extrapolation of the raw counts produced highly variable abundance estimates for both species. To evaluate an alternative survey method and improve abundance estimates, we conducted variable-distance point-transect sampling between 2010 and 2014. We compared our results to those obtained from strip-transect samples. In addition, we applied state-space models to derive improved estimates of population size and trends from the legacy time series of strip-transect counts. Both species were fairly evenly distributed across Nihoa and occurred in all or nearly all available habitat. Population trends for Nihoa Millerbird were inconclusive because of high within-year variance. Trends for Nihoa Finch were positive, particularly since the early 1990s. Distance-based analysis of point-transect counts produced mean estimates of abundance similar to those from strip-transects but was generally more precise. However, both survey methods produced biologically unrealistic variability between years. State-space modeling of the long-term time series of abundances obtained from strip-transect counts effectively reduced uncertainty in both within-and between-year estimates of population size, and allowed short-term changes in abundance trajectories to be smoothed into a long-term trend.