Theodore R. Simons

SPATIAL AUTOCORRELATION AND AUTOREGRESSIVE MODELS IN ECOLOGY

Recognition and analysis of spatial autocorrelation has defined a new par- adigm in ecology. Attention to spatial pattern can lead to insights that would have been otherwise overlooked, while ignoring space may lead to false conclusions about ecological relationships. We used Gaussian spatial autoregressive models, fit with widely available software, to examine breeding habitat relationships for three common Neotropical migrant songbirds in the southern Appalachian Mountains of North Carolina and Tennessee, USA. In preliminary models that ignored space, the abundance of all three species was cor- related with both local- and landscape-scale habitat variables. These models were then modified to account for broadscale spatial trend (via trend surface analysis) and fine-scale autocorrelation (via an autoregressive spatial covariance matrix). Residuals from ordinary least squares regression models were autocorrelated, indicating that the assumption of independent errors was violated. In contrast, residuals from autoregressive models showed little spatial pattern, suggesting that these models were appropriate. The magnitude of habitat effects tended to decrease, and the relative importance of different habitat variables shifted when we incorporated broadscale and then fine-scale space into the analysis. The degree to which habitat effects changed when space was added to the models was roughly correlated with the amount of spatial structure in the habitat variables. Spatial pattern in the residuals from ordinary least squares models may result from failure to include or adequately measure autocorrelated habitat variables. In addition, con- tagious processes, such as conspecific attraction, may generate spatial patterns in species abundance that cannot be explained by habitat models. For our study species, spatial patterns in the ordinary least squares residuals suggest that a scale of 500-1000 m would be ap- propriate for investigating possible contagious processes.

A REMOVAL MODEL FOR ESTIMATING DETECTION PROBABILITIES FROM POINT-COUNT SURVEYS

Abstract Use of point-count surveys is a popular method for collecting data on abundance and distribution of birds. However, analyses of such data often ignore potential differences in detection probability. We adapted a removal model to directly estimate detection probability during point-count surveys. The model assumes that singing frequency is a major factor influencing probability of detection when birds are surveyed using point counts. This may be appropriate for surveys in which most detections are by sound. The model requires counts to be divided into several time intervals. Point counts are often conducted for 10 min, where the number of birds recorded is divided into those first observed in the first 3 min, the subsequent 2 min, and the last 5 min. We developed a maximum-likelihood estimator for the detectability of birds recorded during counts divided into those intervals. This technique can easily be adapted to point counts divided into intervals of any length. We applied this method to unlimited-radius counts conducted in Great Smoky Mountains National Park. We used model selection criteria to identify whether detection probabilities varied among species, throughout the morning, throughout the season, and among different observers. We found differences in detection probability among species. Species that sing frequently such as Winter Wren (Troglodytes troglodytes) and Acadian Flycatcher (Empidonax virescens) had high detection probabilities (∼90%) and species that call infrequently such as Pileated Woodpecker (Dryocopus pileatus) had low detection probability (36%). We also found detection probabilities varied with the time of day for some species (e.g. thrushes) and between observers for other species. We used the same approach to estimate detection probability and density for a subset of the observations with limited-radius point counts.

ESTIMATING SITE OCCUPANCY AND SPECIES DETECTION PROBABILITY PARAMETERS FOR TERRESTRIAL SALAMANDERS

Recent, worldwide amphibian declines have highlighted a need for more extensive and rigorous monitoring programs to document species occurrence and detect population change. Abundance estimation methods, such as mark–recapture, are often expensive and impractical for large-scale or long-term amphibian monitoring. We apply a new method to estimate proportion of area occupied using detection/nondetection data from a terrestrial salamander system in Great Smoky Mountains National Park. Estimated species-specific detection probabilities were all <1 and varied among seven species and four sampling methods. Time (i.e., sampling occasion) and four large-scale habitat characteristics (previous disturbance history, vegetation type, elevation, and stream presence) were important covariates in estimates of both proportion of area occupied and detection probability. All sampling methods were consistent in their ability to identify important covariates for each salamander species. We believe proportion of area occupie...

EXPERIMENTAL ANALYSIS OF THE AUDITORY DETECTION PROCESS ON AVIAN POINT COUNTS

Abstract We have developed a system for simulating the conditions of avian surveys in which birds are identified by sound. The system uses a laptop computer to control a set of amplified MP3 players placed at known locations around a survey point. The system can realistically simulate a known population of songbirds under a range of factors that affect detection probabilities. The goals of our research are to describe the sources and range of variability affecting point-count estimates and to find applications of sampling theory and methodologies that produce practical improvements in the quality of bird-census data. Initial experiments in an open field showed that, on average, observers tend to undercount birds on unlimited-radius counts, though the proportion of birds counted by individual observers ranged from 81% to 132% of the actual total. In contrast to the unlimited-radius counts, when data were truncated at a 50-m radius around the point, observers overestimated the total population by 17% to 122%. Results also illustrate how detection distances decline and identification errors increase with increasing levels of ambient noise. Overall, the proportion of birds heard by observers decreased by 28 ± 4.7% under breezy conditions, 41 ± 5.2% with the presence of additional background birds, and 42 ± 3.4% with the addition of 10 dB of white noise. These findings illustrate some of the inherent difficulties in interpreting avian abundance estimates based on auditory detections, and why estimates that do not account for variations in detection probability will not withstand critical scrutiny. Análisis Experimentales del Proceso de Detección Auditiva en Puntos de Conteo de Aves

ESTIMATING DETECTION PROBABILITY PARAMETERS FOR PLETHODON SALAMANDERS USING THE ROBUST CAPTURE–RECAPTURE DESIGN

Abstract Recent concern over global amphibian population declines has highlighted a need for more extensive, rigorous monitoring programs. Two sources of variation, spatial variation and variation in detection probability, make the design and implementation of effective monitoring programs difficult. We used Pollocks robust design in a 3-year capture–recapture study to estimate detection probability and temporary emigration for Plethodon salamanders in Great Smoky Mountains National Park (Tennessee/North Carolina), USA. We used 12 competing models to determine the importance of temporary emigration, and we explored temporal and behavioral effects on conditional capture probabilities. The top 4 models all included random temporary emigration, and Akaike model weights indicated that this parameter was the most important. Models that contained behavioral effects in capture probabilities were selected more often than models with equal capture probabilities for marked and previously unmarked individuals. The “best” model contained random emigration and behavioral effects and was selected 4 times as often as any other model. When we included Markovian emigration, the probability of emigrating from the surface usually was less than the probability of remaining an emigrant (73% of site-years). Markovian emigration estimates often were similar and always had overlapping confidence intervals, thus the Markovian model rarely was chosen over the random emigration models (only 9.6% of site-years). Our study is the first to formally estimate temporary emigration in terrestrial salamander populations, and our results verify that significant proportions of terrestrial salamander populations are subterranean. We determined that the probability of capturing salamanders on the surface may also vary temporally within a sampling season. Therefore, we caution against using unadjusted count indices to compare salamander populations over time or space unless detection probabilities are estimated. Temporary emigration models will improve abundance estimates when a large proportion of the population is unavailable for capture during a given sampling period.

FACTORS AFFECTING AURAL DETECTIONS OF SONGBIRDS

Many factors affect the number of birds detected on point count surveys of breeding songbirds. The magnitude and importance of these factors are not well understood. We used a bird song simulation system to quantify the effects of detection distance, singing rate, species differences, and observer differences on detection probabilities of birds detected by ear. We simulated 40 point counts consisting of 10 birds per count for five primary species (Black-and-white Warbler Mniotilta varia, Black-throated Blue Warbler Dendroica caerulescens, Black-throated Green Warbler Dendroica virens, Hooded Warbler Wilsonia citrina, and Ovenbird Seiurus aurocapillus) over a range of 15 distances (34-143 m). Songs were played at low (two songs per count) and high (13-21 songs per count) singing rates. Detection probabilities averaged across observers ranged from 0.60 (Black-and-white Warbler) to 0.83 (Hooded Warbler) at the high singing rate and 0.41 (Black-and-white Warbler) to 0.67 (Hooded Warbler) at the low singing rate. Logistic regression analyses indicated that species, singing rate, distance, and observer were all significant factors affecting detection probabilities. Singing rate x species and singing rate X distance interactions were also significant. Simulations of expected counts, based on the best logistic model, indicated that observers detected between 19% (for the worst observer, lowest singing rate, and least detectable species) and 65% (for the best observer, highest singing rate, and most detectable species) of the true population. Detection probabilities on actual point count surveys are likely to vary even more because many sources of variability were controlled in our experiments. These findings strongly support the importance of adjusting measures of avian diversity or abundance from auditory point counts with direct estimates of detection probability.

LANDSCAPE EFFECTS ON BREEDING SONGBIRD ABUNDANCE IN MANAGED FORESTS

We examined the relationship between songbird relative abundance and local and landscape-scale habitat variables in two predominately mid- to late-successional man- aged National Forests in the southern Appalachian Mountains, USA. We used partial- regression analysis to remove correlations between habitat variables measured at different spatial scales (local habitat and square landscape regions with sides of 0.5, 1, and 2 km) and between landscape composition (proportion of different land cover types) and pattern (spatial arrangement of land cover) variables. To account for spatial autocorrelation, we used autoregressive models that incorporated information on bird abundance in the spatial neighborhood surrounding each sample point. Most species, especially Neotropical mi- grants, were significantly correlated with at least one landscape variable. These correlations included both composition and pattern variables at 0.5-2 km scales. However, landscape effects explained only a small amount of the variation in bird abundance that could not be explained by local habitat. Our results are consistent with other studies of songbird abun- dance in large managed forests that have found weak or moderate landscape effects. These studies suggest that songbird abundance in forested landscapes will primarily reflect the quantity of different habitats in the landscape rather than the spatial arrangement of those habitats. Although some studies have suggested consolidating clearcuts in large managed forests to reduce edge and landscape heterogeneity, much of the current evidence does not support this management recommendation. An important future challenge in avian con- servation is to better understand how the importance of landscape effects varies in relation to (1) the amount of suitable habitat in the landscape, and (2) land use patterns at broader spatial scales.

Sampling plethodontid salamanders : Sources of variability

Recent evidence of possible worldwide amphibian population declines has highlighted the need for a better understanding of species-specific habitat associations and methodologies for monitoring long-term population trends. Great Smoky Mountains National Park is committed to incorporating salamander population monitoring into the parks long-term inventory and monitoring program because of the large number of unique species in the park, and evidence that salamanders are finely tuned indicators of environmental quality. We present data on spatial and temporal patterns in salamander diversity and abundance in Great Smoky Mountains National Park and compare the bias and effectiveness of 4 common sampling techniques. We found that large-scale habitat characteristics, including disturbance history, proximity of streams, and elevation are useful to explain patterns of salamander distribution and abundance. With the exception of soil moisture, microhabitat variables were not helpful in understanding variations in salamander relative abundance. Data collected over 2 years suggest that common salamander sampling techniques vary significantly in their effectiveness, and they may often violate assumptions required for comparing salamander population indices over space or time. Salamander counts on our sites were highly variable. Neither sampling variability nor detectability were constant across habitat types or species. These characteristics reduce power for detecting long-term population trends and suggest that some common sampling methods may not provide indices suitable for long-term population monitoring.

A Field Evaluation of Distance Measurement Error in Auditory Avian Point Count Surveys

Abstract Detection distance is an important and common auxiliary variable measured during avian point count surveys. Distance data are used to determine the area sampled and to model the detection process using distance sampling theory. In densely forested habitats, visual detections of birds are rare, and most estimates of detection distance are based on auditory cues. Distance sampling theory assumes detection distances are measured accurately, but empirical validation of this assumption for auditory detections is lacking. We used a song playback system to simulate avian point counts with known distances in a forested habitat to determine the error structure of distance estimates based on auditory detections. We conducted field evaluations with 6 experienced observers both before and after distance estimation training. We conducted additional studies to determine the effect of height and speaker orientation (toward or away from observers) on distance estimation error. Distance estimation errors for all evaluations were substantial, although training reduced errors and bias in distance estimates by approximately 15%. Measurement errors showed a nonlinear relationship to distance. Our results suggest observers were not able to differentiate distances beyond 65 m. The height from which we played songs had no effect on distance estimation errors in this habitat. The orientation of the song source did have a large effect on distance estimation errors; observers generally doubled their distance estimates for songs played away from them compared with distance estimates for songs played directly toward them. These findings, which we based on realistic field conditions, suggest measures of uncertainty in distance estimates to auditory detections are substantially higher than assumed by most researchers. This means aural point count estimates of avian abundance based on distance methods deserve careful scrutiny because they are likely biased.

TIME-OF-DETECTION METHOD FOR ESTIMATING ABUNDANCE FROM POINT-COUNT SURVEYS

Abstract Point-count surveys are often used to collect data on the abundance and distribution of birds, generally as an index of relative abundance. Valid comparison of these indices assumes that the detection process is comparable over space and time. These restrictive assumptions can be eliminated by estimating detection probabilities directly. We generalize a recently proposed removal model for estimating detection probabilities using a time-of-detection approach, which can account for more sources of variation in point-count data. This method is specifically designed to account for variation in detection probabilities associated with singing rates of birds. Our model accounts for both availability bias and detection bias by modeling the combined probability that a bird sings during the count, and the probability that it is detected given that it sings. The model requires dividing the count into several intervals and recording detections of individual birds in each interval. We develop maximum-likelihood estimators for this approach and provide a full suite of models based on capture-recapture models, including covariate models. We present two examples of this method: one for four species of songbirds surveyed in Great Smoky Mountains National Park using three unequal intervals, and one for the Pearly-eyed Thrasher (Margarops fuscatus) surveyed in Puerto Rico using four equal intervals. Models incorporating individual heterogeneity were selected for all data sets using information-theoretic model-selection techniques. Detection probabilities varied among count-time intervals, which suggests that birds may be responding to observers. We recommend applying this method to surveys with four or more equal intervals to reduce assumptions and to take full advantage of standard capture-recapture software. The time-of-detection approach provides a better understanding of the detection process, especially when singing rates of individual birds affect detection probabilities. Estimación de la Abundancia en Puntos de Conteo Mediante el Método del Tiempo de Detección