scholarly journals Landbird Counting Techniques: Current Practices and an Alternative

The Auk ◽  
2002 ◽  
Vol 119 (1) ◽  
pp. 46-53 ◽  
Author(s):  
Steven S. Rosenstock ◽  
David R. Anderson ◽  
Kenneth M. Giesen ◽  
Tony Leukering ◽  
Michael F. Carter

AbstractCounting techniques are widely used to study and monitor terrestrial birds. To assess current applications of counting techniques, we reviewed landbird studies published 1989–1998 in nine major journals and one symposium. Commonly used techniques fell into two groups: procedures that used counts of bird detections as an index to abundance (index counts), and procedures that used empirical models of detectability to estimate density. Index counts rely upon assumptions concerning detectability that are difficult or impossible to meet in most field studies, but nonetheless remain the technique of choice among ornithologists; 95% of studies we reviewed relied upon point counts, strip transects, or other index procedures. Detectability-based density estimates were rarely used and deserve wider application in landbird studies. Distance sampling is a comprehensive extension of earlier detectability-based procedures (variable-width transects, variable circular plots) and a viable alternative to index counts. We provide a conceptual overview of distance sampling, specific recommendations for applying this technique to studies of landbirds, and an introduction to analysis of distance sampling data using the program DISTANCE.

2018 ◽  
Author(s):  
D. A. Gómez-Hoyos ◽  
O. H. Marín-Gómez ◽  
Y. L. Caicedo Ortiz

AbstractMultinomial-Poisson mixture models reveal unexpected higher density estimates of an Andean threatened bird.Distance sampling and repeated counts are important tools to estimate population density of birds with low detectability. Here we use model based approach to assess the population density of a threatened bird, the Multicolored Tanager (Chlorochrysa nitidissima). We conducted 144 fixed point counts samplings to record all the individuals of the Multicolored Tanager detected by visual and aural observations from different habitats (forest edge, mature, secondary, and riparian forest), during four months in an Important Bird Area of Central Andes of Colombia. We used spatially replicated counts, distance sampling, and multinomial- Poisson mixture models to estimate the population density of the Multicolored Tanager. Accumulated sampling effort was of 576 repetitions in 144 point counts with 96 h of observation. The Multinomial-Poisson mixture model showed the best fit due low variance of density estimations in comparison to the conventional distance sampling and the spatially replicated counts. Results of this model evidenced a remarkable higher density estimates (1.3 – 2.05 individuals/ha) of the Multicolored Tanager, particularly in mature and secondary forest, as a result of detection correction, instead of sampling effort, by our model based analysis in contrast to index density used in previous studies. We discuss the advantages of model based methods over density indexes in designs monitoring programs of endangered species as the Multicolored Tanager, in order to obtain better and comparable assessment of density estimations along multiple localities.ResumenLa combinación de modelos multi-nominales y Poisson revelan estimaciones de densidad altas inesperadas en un ave amenazada Andina. Los muestreos por distancias y los conteos repetidos son herramientas importantes para estimar la densidad de población de aves con baja detección. Aquí utilizamos un enfoque basado en modelos para evaluar la densidad de población de un ave amenazada, la tangara multicolor (Chlorochrysa nitidissima). Realizamos 144 muestreos de conteos de puntos fijos para registrar todos los individuos de la tangara multicolor detectados por observaciones visuales y auditivas en diferentes hábitats (borde del bosque, bosque maduro, bosque secundario y bosque ribereño), durante cuatro meses en un Área Importante para la Conservación de las Aves en los Andes centrales de Colombia. Utilizamos conteos replicados espacialmente, muestreos de distancia y la combinación de modelos multi-nominales y Poisson para estimar la densidad de población de la tangara multicolor. El esfuerzo de muestreo acumulado fue de 576 repeticiones en 144 puntos de conteo con 96 h de observación. La combinación de modelos multi-nominales y Poisson mostró el mejor ajuste debido a la baja varianza de las estimaciones de densidad en comparación con el muestreo de distancias y los conteos replicados espacialmente. Los resultados de este modelo evidenciaron una notable estimación de mayor densidad (1.3 – 2.05 individuos / ha) de la tangara multicolor, principalmente en bosques maduros y secundarios, como resultado de la corrección de la detección por nuestro análisis basado en modelos, en lugar del esfuerzo de muestreo, en contraste con los índices de densidad utilizados en estudios previos. Discutimos las ventajas de los métodos basados en modelos sobre los índices de densidad en los diseños de programas de monitoreo de especies en peligro como la tangara multicolor, con el fin de obtener una evaluación mejor y comparable de las estimaciones de densidad a lo largo de múltiples localidades.


2021 ◽  
Vol 13 (6) ◽  
pp. 1102
Author(s):  
Julia Witczuk ◽  
Stanisław Pagacz

The rapidly developing technology of unmanned aerial vehicles (drones) extends to the availability of aerial surveys for wildlife research and management. However, regulations limiting drone operations to visual line of sight (VLOS) seriously affect the design of surveys, as flight paths must be concentrated within small sampling blocks. Such a design is inferior to spatially unrestricted randomized designs available if operations beyond visual line of sight (BVLOS) are allowed. We used computer simulations to assess whether the VLOS rule affects the accuracy and precision of wildlife density estimates derived from drone collected data. We tested two alternative flight plans (VLOS vs. BVLOS) in simulated surveys of low-, medium- and high-density populations of a hypothetical ungulate species with three levels of effort (one to three repetitions). The population density was estimated using the ratio estimate and distance sampling method. The observed differences in the accuracy and precision of estimates from the VLOS and BVLOS surveys were relatively small and negligible. Only in the case of the low-density population (2 ind./100 ha) surveyed once was the VLOS design inferior to BVLOS, delivering biased and less precise estimates. These results show that while the VLOS regulations complicate survey logistics and interfere with random survey design, the quality of derived estimates does not have to be compromised. We advise testing alternative survey variants with the aid of computer simulations to achieve reliable estimates while minimizing survey costs.


2011 ◽  
Vol 2 (1) ◽  
pp. 117-121 ◽  
Author(s):  
Roger D. Applegate ◽  
Robert E. Kissell ◽  
E. Daniel Moss ◽  
Edward L. Warr ◽  
Michael L. Kennedy

Abstract Point count data are used increasingly to provide density estimates of bird species. A favored approach to analyze point count data uses distance sampling theory where model selection and model fit are important considerations. We used uniform and half normal models and assessed model fit using χ2 analysis. We were unsuccessful in fitting models to 635 northern bobwhite Colinus virginianus observations from 85 avian point locations spanning 6 y (P ≤ 0.05). Most observations (74%) occurred in the outermost (>100-m) distance radius. Our results violated the assumptions that all observations at the point are detected. The assumption that birds were assigned to the correct distance interval also was probably violated. We caution managers in implementing avian point counts with distance sampling when estimating northern bobwhite population density. We recommend exploring other approaches such as occupancy-estimation and modeling for estimating detection probabilities.


2012 ◽  
Vol 3 (1) ◽  
pp. 158-163 ◽  
Author(s):  
Michael F. Small ◽  
Joseph A. Veech ◽  
John T. Baccus

Abstract Surveying bird populations through visual observation is generally limited to morning. The focus on morning surveys is based on the reasonable assumption that detection is more likely when birds are most active. However, population surveys could become more time- and cost-efficient if both morning and evening sampling were equally effective, particularly for game birds, such as white-winged dove Zenaida asiatica. Texas Parks and Wildlife Department has recently implemented distance sampling to estimate population sizes and monitor an ongoing range expansion of this species. We compared morning vs. evening density estimates for white-winged doves sampled in Mason, Texas, on six separate occasions during summer 2006. Program DISTANCE (version 5.0) calculated similar detection probabilities and density estimates between paired morning and evening sampling periods. Probability of detection ranged from 0.27 to 0.46 for both morning and evening samples. Densities, in individuals/ha, ranged from 2.54 to 4.02 for morning sampling and 2.48 to 4.31 for evening sampling. In addition, variables (number of observations, cluster size, distance to cluster) used by DISTANCE did not vary substantially between morning and evening surveys. Our results suggest evening surveys are as effective as the conventional protocol of surveying white-winged doves only in the morning. Additional studies, using Program DISTANCE, should be conducted to similarly evaluate other species.


The Auk ◽  
2007 ◽  
Vol 124 (1) ◽  
pp. 96-106 ◽  
Author(s):  
Duane R. Diefenbach ◽  
Matthew R. Marshall ◽  
Jennifer A. Mattice ◽  
Daniel W. Brauning

Abstract Several bird-survey methods have been proposed that provide an estimated detection probability so that bird-count statistics can be used to estimate bird abundance. However, some of these estimators adjust counts of birds observed by the probability that a bird is detected and assume that all birds are available to be detected at the time of the survey. We marked male Henslow's Sparrows (Ammodramus henslowii) and Grasshopper Sparrows (A. savannarum) and monitored their behavior during May-July 2002 and 2003 to estimate the proportion of time they were available for detection. We found that the availability of Henslow's Sparrows declined in late June to <10% for 5- or 10-min point counts when a male had to sing and be visible to the observer; but during 20 May-19 June, males were available for detection 39.1% (SD = 27.3) of the time for 5-min point counts and 43.9% (SD = 28.9) of the time for 10-min point counts (n = 54). We detected no temporal changes in availability for Grasshopper Sparrows, but estimated availability to be much lower for 5-min point counts (10.3%, SD = 12.2) than for 10-min point counts (19.2%, SD = 22.3) when males had to be visible and sing during the sampling period (n = 80). For distance sampling, we estimated the availability of Henslow's Sparrows to be 44.2% (SD = 29.0) and the availability of Grasshopper Sparrows to be 20.6% (SD = 23.5). We show how our estimates of availability can be incorporated in the abundance and variance estimators for distance sampling and modify the abundance and variance estimators for the double-observer method. Methods that directly estimate availability from bird counts but also incorporate detection probabilities need further development and will be important for obtaining unbiased estimates of abundance for these species. Incorporación de la Disponibilidad para la Detección en las Estimaciones de Abundancia de Aves


The Auk ◽  
2007 ◽  
Vol 124 (4) ◽  
pp. 1229-1243 ◽  
Author(s):  
Tiago A. Marques ◽  
Len Thomas ◽  
Steven G. Fancy ◽  
Stephen T. Buckland

Abstract Inferences based on counts adjusted for detectability represent a marked improvement over unadjusted counts, which provide no information about true population density and rely on untestable and unrealistic assumptions about constant detectability for inferring differences in density over time or space. Distance sampling is a widely used method to estimate detectability and therefore density. In the standard method, we model the probability of detecting a bird as a function of distance alone. Here, we describe methods that allow us to model probability of detection as a function of additional covariates—an approach available in DISTANCE, version 5.0 (Thomas et al. 2005) but still not widely applied. The main use of these methods is to increase the reliability of density estimates made on subsets of the whole data (e.g., estimates for different habitats, treatments, periods, or species), to increase precision of density estimates or to allow inferences about the covariates themselves. We present a case study of the use of multiple covariates in an analysis of a point-transect survey of Hawaii Amakihi (Hemignathus virens). Amélioration des estimations de densité d’oiseaux par l’utilisation de l’échantillonnage par la distance avec covariables multiples


2010 ◽  
Vol 32 (2) ◽  
pp. 197 ◽  
Author(s):  
G. R. Finlayson ◽  
A. N. Diment ◽  
P. Mitrovski ◽  
G. G. Thompson ◽  
S. A. Thompson

A reliable estimate of population size is of paramount importance for making management decisions on species of conservation significance that may be impacted during development. The western ringtail possum (Pseudocheirus occidentalis) is regularly encountered during urban development and is the subject of numerous surveys to estimate its abundance. A variety of techniques have been used for this species with mixed results. This paper reports on a case study using distance sampling to estimate density of P. occidentalis in a small habitat remnant near Busselton, Western Australia. Density estimates obtained were within the range of previous studies of this species and we suggest that this technique should be employed in future surveys to improve the accuracy of population estimates for this species before development.


2014 ◽  
Vol 25 (3) ◽  
pp. 322-334 ◽  
Author(s):  
KATHLEEN E. GREEN ◽  
BRONWEN M. DANIEL ◽  
SAMUEL P. LLOYD ◽  
ISHAKA SAID ◽  
AMELAID HOUMADI ◽  
...  

SummaryAlthough birds are among the best studied taxa, many of the globally threatened species lack the information required to fully assess their conservation status and needs. One such species is the Anjouan Scops Owl Otus capnodes which was presumed extinct until its rediscovery to science in 1992. Based on the limited extent and decline of the moist forests in the highlands of Anjouan in the Comoro Islands, a population size of only 100–200 pairs was estimated and the species was classified as ‘Critically Endangered’. The current study is the first comprehensive survey ever conducted on this species, and aimed to establish the current distribution and population size. Point counts with distance sampling were conducted across the agroforestry and forest zones of Anjouan in both a dry and wet season. A niche suitability model predicted the species distribution to be wider than expected with owls observed as low as 300 m altitude and in highly modified agroforestry habitats. However, the encounter rate in natural relatively undisturbed forest was significantly greater than in other habitats. The wider than expected geographic range of O. capnodes supports a possible downlisting of this species on the IUCN Red List to ‘Endangered’. Population size was found to be far greater than previously thought, at approximately 3,450 individual owls in the dry season and 5,450 in the wet season. These results show the importance of investing in robust surveys of poorly known and cryptic bird species, and provide up to date and important information for landscape scale conservation planning in the Comoros Islands.


Geosphere ◽  
2021 ◽  
Author(s):  
Pierre-Simon Ross ◽  
Bernard Giroux ◽  
Benjamin Latutrie

Quantifying the proportions of certain components in rocks and deposits (modal analysis or componentry) is important in earth sciences. Relevant methods for cross-sections (two- dimensional exposures) of clastic rocks include point counts or line counts. The accuracy of these methods has been supposed to be good in the literature but not necessarily verified empirically. Natural materials are inappropriate for assessing accuracy because the true proportions of each component are unknown. The precision of modal analysis methods has traditionally been evaluated from statistical models (primarily the normal approximation to the binomial distribution) but again rarely verified in practice because it is also extremely difficult to obtain different slices through the same material at outcrop scale. Here we create a set of numerical models of red and blue spheres with different proportions and sizes and cut 60 slices through the models, on which we perform point counts and line counts. We show that both of these methods are indeed able to retrieve the correct volumetric proportions of components, on average, when enough fragments are counted or intersected. As already known, precision is controlled by component abundance and the number of points counted or clasts intersected. However, we show that other important factors include differences between slices, which are relevant for our unequal-size models, and the proportion of voids, matrix, and/or cement in the rock. We present empirical precision charts for clast counts and line counts based on our models and make recommendations for future field studies.


2018 ◽  
Author(s):  
Douglas B Sigourney ◽  
Samuel Chavez-Rosales ◽  
Paul Conn ◽  
Lance Garrison ◽  
Elizabeth Josephson ◽  
...  

Species distribution models (SDMs) have proven to be an integral tool in the conservation and management of cetaceans. Many applications have adopted a two-step approach where a detection function is estimated using conventional distance sampling in the first step and subsequently used as an offset to a density-habitat model in the second step. A drawback to this approach, hereafter referred to as the conventional species distribution model (CSDM), is the difficulty in propagating the uncertainty from the first step to the final density estimates. We describe a Bayesian hierarchical species distribution model (BHSDM) which has the advantage of simultaneously propagating multiple sources of uncertainty. Our framework includes 1) a mark-recapture distance sampling observation model that can accommodate two team line transect data, 2) an informed prior for surface availability 3) spatial smoothers using spline-like bases and 4) a compound Poisson-gamma likelihood which is a special case of the Tweedie distribution. We compare our approach to the CSDM method using a simulation study and a case study of fin whales (Balaenoptera physalus) off the East Coast of the USA. Simulations showed that the BHSDM method produced estimates with lower precision but with confidence interval coverage closer to the nominal 95% rate (94% for the BSHDM vs 85% for the CSDM). Results from the fin whale analysis showed that density estimates and predicted distribution patterns were largely similar among methods. Abundance estimates were also similar though modestly higher for the CSDM (4700, CV=0.13) than the BHSDM (4526, CV=0.26). Estimated sampling error differed substantially among the two methods where the average CV for density estimates from BHSDM method was approximately 3.5 times greater than estimates from the CSDM method. Successful wildlife management hinges on the ability to properly quantify uncertainty. Underestimates of uncertainty can result in ill-informed management decisions. Our results highlight the additional sampling uncertainty that is propagated in a hierarchical framework. Future applications of SDMs should consider techniques that allow all sources of error to be fully represented in final density predictions.


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