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Evaluating abundance estimates and evidence of breeding for Bobolinks from transect and point‐count surveys
Abstract
en Estimating the abundance and breeding success of territorial songbirds is challenging. Various types of surveys and analyses are available, but all receive some criticism in the literature, and most methods are rarely compared with results obtained using intensive monitoring efforts. We assessed the efficacy of transect and point‐count surveys to estimate the abundance of male Bobolinks (Dolichonyx oryzivorus ) and detect evidence of nesting and fledging by comparing the results of those surveys to results from more intensive monitoring (i.e., spot mapping and nest monitoring). We monitored 36 fields (254 ha) of late‐harvest hay, restored grassland, and fallow fields in the Luther Marsh Wildlife Management Area and on four farms in southern Ontario, Canada, in 2018. Compared to the number of territories identified based on spot mapping (197), distance sampling analysis of transect survey data provided a more accurate estimate of the abundance of male Bobolinks (230, 95% CI: 187, 282) than N‐mixture models of transect (668, 95% CI: 332, 1342) and point‐count (337, 95% CI: 203, 559) data. Three visits to survey transects and five to point counts did not effectively detect evidence of Bobolink breeding (i.e., nesting or fledging) in fields compared to spot mapping and nest monitoring. Distance sampling analysis of transect data appears promising for estimating the number of Bobolink territories in an area, e.g., those impacted by conservation programs. If estimates of the number of nesting Bobolinks and frequency of fledging are of interest, spot mapping and nest monitoring could be implemented at a subset of sampled fields. Our results suggest that additional studies to evaluate model‐based estimates of abundance with the best available information (e.g., from spot mapping of marked or unmarked populations and nest monitoring) would be useful to ensure that robust estimates are provided to support population estimates and conservation actions.
RESUMEN
es Evaluación de los estimadores de abundancia y evidencia de reproducción de Dolichonyx oryzivorus a partir de monitoreo por transectos y puntos de conteo.
Estimar la abundancia y el éxito reproductivo de aves territoriales es un reto. Están disponibles varios tipos de monitoreo y análisis, pero todos reciben algún criticismo en la literatura y la mayoría de los métodos son raramente comparados con resultados obtenidos utilizando esfuerzos intensivos de monitoreo. Determinamos la eficacia de monitoreos por transecto y puntos de conteo para estimar la abundancia de machos de Dolichonyx oryzivorus y detectar evidencia de anidación y la presencia de volantones, comparando los resultados de estos monitoreos con resultados obtenidos por monitoreos más intensivos (i.e. mapeo por puntos y monitoreo de nidos). Monitoreamos 36 campos (254 ha) de heno de recolección tardía, pastizales restaurados y campos de cultivo en recuperación en el área de manejo de vida silvestre Luther Marsh y cuatro granjas en el sur de Ontario en Canadá durante 2018. Comparado con el numero de territorios identificados utilizando mapeo por puntos (197), el análisis de muestreo por distancia de los datos obtenidos utilizando monitoreos por transecto derivaron en un estimador más preciso de la abundancia de machos de Dolichonyx oryzivorus (230, 95% CI: 187, 282) que los modelos de N‐mezclas utilizando datos de transectos (668, 95% CI: 332, 1342) y puntos de conteo (337 95% CI: 203, 559). Las tres visitas de los monitoreos por transectos y los cinco utilizando puntos de conteo no fueron suficientes para detectar evidencia de reproducción en Dolichonyx oryzivorus (i.e. a nidación o presencia de volantones) en los campos comparado con el mapeo por puntos y el monitoreo de nidos. Los análisis de muestreo por distancia de los datos de los transectos parecen ser prometedores para estimar el numero de Dolichonyx oryzivorus en un área, e.g., impactadas por programas de conservación. Si los estimados del número de Dolichonyx oryzivorus anidando y la frecuencia de volantones son las variables de interés, mapeo por puntos y el monitoreo de nidos pueden ser implementados en un subset de los campos muestreados. Nuestros resultados sugieren que estudios adicionales para evaluar los estimados de abundancia basados en modelos con la mejor información disponible (e.g., proveniente de mapeo por puntos de poblaciones marcadas o no marcadas y monitoreo de nidos) pueden ser útiles para asegurar que se provean estimados robustos para soportar estimadores poblacionales y acciones de conservación.
... I used distance sampling (Buckland et al. 2001) with line transects to derive density estimates corrected for species probability of detection, which are typically low for savanna birds (Diefenbach et al. 2003). This method is particularly effective in open terrain (Buckland 2006) and can yield more accurate abundance estimates than other methods, such as point counts with N-mixture models (Campomizzi et al. 2020). Additionally, abundance estimates from distance sampling have shown strong correlations with those from more intensive territory mapping for migrant and breeding birds (Gale et al. 2009, Campomizzi et al. 2020). ...
... This method is particularly effective in open terrain (Buckland 2006) and can yield more accurate abundance estimates than other methods, such as point counts with N-mixture models (Campomizzi et al. 2020). Additionally, abundance estimates from distance sampling have shown strong correlations with those from more intensive territory mapping for migrant and breeding birds (Gale et al. 2009, Campomizzi et al. 2020). ...
... We used spot mapping to assess the breeding status of Bobolink in 2019 and 2020 in grazed and ungrazed fields from 20 to 28 June. We selected this time period to coincide with when most Bobolink in the study area have mature nestlings or young fledglings (Campomizzi et al. 2020). We used detections of Bobolink on the third and fourth transect visit to guide territory sampling and distributed sampled territories across as many fields as possible. ...
... For comparison with results from the distance sampling analysis, we summed the maximum number of males detected ≤75 m on either side of the transect line in each field across the first and second transect visit in 20 fields because Campomizzi et al. (2020) found the maximum number of males detected was a reasonable estimate of the number of Bobolink territories in a surveyed area. ...
Multiple bird species-at-risk nest on the ground in hayfields and pastures, making nests susceptible to inadvertent destruction from agricultural activity (e.g., trampling by livestock). To better understand the impact of Domestic Cattle (Bos taurus) grazing, we assessed the distribution and breeding status of nesting grassland birds in 2019 and 2020 at the Grey Dufferin Community Pasture, a ~234 ha pasture in southern Ontario, Canada. We estimated there were 86 male Bobolink (Dolichonyx oryzivorus) in the community pasture in 2019 and 100 in 2020 before grazing began; observed abundance decreased by 73% in fields after grazing in 2020. Eastern Meadowlark (Sturnella magna) maintained territories after grazing and fledged young in 67% (n = 21) of territories. Savannah Sparrow (Passerculus sandwichensis) was common across the community pasture before and after grazing occurred. We detected evidence of nesting more frequently in Bobolink and Savannah Sparrow territories in ungrazed than in grazed fields. Our results support previous research indicating nesting Bobolink often disperse from moderately to heavily grazed fields, whereas Eastern Meadowlark and Savannah Sparrow largely remain and renest. Despite the inadvertent negative impacts of cattle stepping or laying on nests and consuming vegetative cover, the community pasture provides areas for successful nesting, with Eastern Meadowlark faring better than Bobolink. Flexibility in the timing and duration of grazing in rotational grazing systems may enable strategic management in target fields (e.g., maintaining enough vegetation for nesting Bobolink). Information about the distribution and abundance of birds can be used to target particular fields for conservation.
... Population density is perhaps one of the most useful ecological measurements for understanding the spatial distribution of wild populations and the factors driving variation in their abundance (Andrewartha andBirch 1954, Krebs 2001). Density estimates are particularly important for ecologists and conservationists, as they facilitate the identification of environmental stressors affecting populations (Lloyd 2008, Campomizzi et al. 2020. Calculated periodically, density can be used to monitor population dynamics (Gregory et al. 2004). ...
Abundance measures are almost non-existent for several bird species threatened with extinction, particularly range-restricted Neotropical taxa, for which estimating population sizes can be challenging. Here we use data collected over 9 years to explore the abundance of 11 endemic birds from the Sierra Nevada de Santa Marta (SNSM), one of Earth’s most irreplaceable ecosystems. We established 99 transects in the “Cuchilla de San Lorenzo” Important Bird Area within native forest, early successional vegetation, and areas of transformed vegetation by human activities. A total of 763 bird counts were carried out covering the entire elevation range in the study area (~175–2,650 m). We applied hierarchical distance-sampling models to assess elevation- and habitat-related variation in local abundance and obtain values of population density and total and effective population size. Most species were more abundant in the montane elevational range (1,800–2,650 m). Habitat-related differences in abundance were only detected for 5 species, which were more numerous in either early succession, secondary forest, or transformed areas. Inferences of effective population size indicated that at least 4 endemics likely maintain populations no larger than 15,000–20,000 mature individuals. Inferences of species’ area of occupancy and effective population size were lower than most values previously described, a possible consequence of increasing anthropogenic threats. At least 4 of the endemics exceeded criteria for threatened species listing and a thorough evaluation of their extinction risk should be conducted. Population strongholds for most of the study species were located on the northern and western slopes of the SNSM between 1,500 and 2,700 m. We highlight the urgent need for facilitating effective protection of native vegetation in premontane and montane ecosystems to safeguard critical habitats for the SNSM’s endemic avifauna. Follow-up studies collecting abundance data across the SNSM are needed to obtain precise range-wide density estimations for all species.
... Point counts are another standard methodology used to census wild birds during which an observer stands in a single spot for a specific time period and records the presence and numbers of individuals and species seen or heard within a specified radius (Hutto et al. 1986, Leu et al. 2017, Campomizzi et al. 2020. Despite its popularity in field ornithology, the technique comes with inherent biases and limitations (see Simons et al. 2009). ...
The primary goal of this plan is to provide crucial ecological and biologically relevant data to inform management activities for the Bermuda White-eyed Vireo, as well as layout essential guidelines needed to preserve, protect, and facilitate population growth of this songbird. It is currently recognized as the only avian, terrestrial, endemic subspecies on the island and is thus of extreme conservation importance. It is with hope that this document will also encourage additional research and monitoring, mitigation of threats, and make the public aware of the practices they can adopt that will be beneficial to our local vireo.
... In temperate grasslands, Golding and Dreitz (2016) compared and assessed the efficiency of point counts and transects based on bird detection probabilities and abundance estimates and concluded that transects resulted in more precise detection and abundance estimates. Likewise, Campomizzi et al. (2020) assessed the efficacy of distance sampling analyses of transect and point count surveys to estimate temperate grassland bird abundance and found that distance sampling analyses of transect surveys provided more accurate abundance estimates. In tropical grasslands, Fontana et al. (2018) compared point counts and transects for bird sampling and found that total abundance of birds estimated by the two methods did not differ. ...
Montane desert birds are particularly vulnerable to population declines driven by global climate change that is accelerated at higher elevations. Providing reliable and accurate information about their populations is essential for effective conservation management plans. However, few studies have compared the effectiveness of different survey methods for birds in high altitude arid environments, particularly in the Middle East. Here, we compare the reliability and precision of two sampling methods to estimate densities for two resident bird species in Egypt's Sinai mountains, the white-crowned wheatear (Oenanthe leucopyga) and desert lark (Ammomanes deserti). We conducted surveys for both species in vegetated and unvegetated desert using fixed-width strip transects and line transects using the distance sampling approach, and employed several statistical approaches to compare density estimates. While both methods provided reliable density estimates given sufficient detections of target species, strip transects exhibited more flexibility overall for estimating cryptic and rare species, which comprise a large proportion of this and other montane desert bird communities. Strip transects also entail lower effort and costs, an important consideration given research funding constraints. We therefore recommend strip transects over distance sampling for estimating bird densities in this and other arid montane regions.
Conservation actions for the federally and provincially threatened Bobolink (Dolichonyx oryzivorus) in Ontario, Canada are ongoing in agricultural landscapes, including pastures. However, conditions conducive to Bobolink fledging young from breeding territories in rotationally grazed beef cattle (Bos taurus) pastures are not well understood. We tested two management strategies designed to provide habitat where Bobolink could fledge young in rotationally grazed pastures. We conducted (1) a refuge paddock experiment using a crossover design, comparing fledging success when paddocks were ungrazed in one year to when they were grazed in another year; and (2) a light spring grazing experiment. Additionally, we explored associations between fledging of young from territories with cattle stocking rate and date that cattle first entered paddocks. We used spot mapping and nest monitoring to determine if young fledged in 83 Bobolink territories in 2016 and 72 territories in 2017 on six farms in the Ottawa Valley, Ontario. In the refuge paddock experiment, 54% (N = 28) of Bobolink territories fledged young in eight ungrazed paddocks compared to 16% (N = 25) when these paddocks were grazed in another breeding season. In the light spring grazing experiment, 67% (N = 12) of territories fledged young from four paddocks that were grazed with a low stocking rate between 21 May and 03 June 2017 and not again until after 02 July. Additionally, predictions from a logistic regression model indicated that the probability of young fledging from a territory (N = 118) decreased from 0.53 to 0.04 when mid-season stocking rates increased from 0 to 174 cattle-days/ha. Our results illustrate that paddocks on rotationally grazed beef cattle farms that are ungrazed until the Bobolink breeding season is finished or grazed lightly for a brief duration soon after territories are established can provide areas that enable Bobolink to fledge young.
Staggering decline of bird populations
Because birds are conspicuous and easy to identify and count, reliable records of their occurrence have been gathered over many decades in many parts of the world. Drawing on such data for North America, Rosenberg et al. report wide-spread population declines of birds over the past half-century, resulting in the cumulative loss of billions of breeding individuals across a wide range of species and habitats. They show that declines are not restricted to rare and threatened species—those once considered common and wide-spread are also diminished. These results have major implications for ecosystem integrity, the conservation of wildlife more broadly, and policies associated with the protection of birds and native ecosystems on which they depend.
Science , this issue p. 120
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.
Differences among observers in ability to detect and identify birds has been long recognized as a potential source of error when surveying terrestrial birds. However, few published studies address that issue in their methods or study design. We used distance sampling with line transects to investigate differences in detection probabilities among observers and among three species of grassland songbirds: Henslow's Sparrow (Ammodramus henslowii), Grasshopper Sparrow (A. savannarum), and Savannah Sparrow (Passerculus sandwichensis). Our review of 75 papers published in 1985–2001 found that the most commonly used methods were fixed-width transects (31%, 23 papers) and fixed-radius point counts (20%, 15 papers). The median half-width of fixed-width strip transects used by researchers was 50 m, but our results indicated detection probabilities were <1.0 at distances >25 m for most observers and species. Beyond 50 m from the transect line, we found that as many as 60% of birds were missed by observers and that the proportion missed differed among observers and species. Detection probabilities among observers ranged from 0.43 to 1.00 for Henslow's Sparrow, from 0.44 to 0.66 for Grasshopper Sparrow, and from 0.60 to 0.72 for Grasshopper Sparrow for birds detected within 58–100 m of the transect line. Using our estimates of detection probabilities for Henslow's Sparrows among six observers in a computer simulation of a monitoring program, we found that bird counts from fixed-width transects required an additional 2–3 years of monitoring to detect a given decline in abundance compared to density estimates that used a method to correct for missed birds. We recommend that researchers employ survey methods that correct for detection probabilities <1.0.
Estimating the abundance and spatial distribution of animal and plant populations is essential for conservation and management. We introduce the R package Distance that implements distance sampling methods to estimate abundance. We describe how users can obtain estimates of abundance (and density) using the package as well as documenting the links it provides with other more specialized R packages. We also demonstrate how Distance provides a migration pathway from previous software, thereby allowing us to deliver cutting-edge methods to the users more quickly.
Avian monitoring strategies are usually linked to bird singing or calling behavior. Individual availability for detection can change as a result of conspecific factors affecting bird behavior, though the magnitude of these effects is difficult to quantify. We evaluated behavioral and temporal factors affecting Northern Bobwhite (Colinus virginianus) breeding season individual availability for detection during three common survey times (3 min, 5 min, 10 min). We conducted 10-minute surveys associated with radio-collared male Northern Bobwhites on Peabody Wildlife Management Area, Kentucky, from 2010–2011. We homed to within 50 m of radio-collared males and recorded number of distinct Northern Bobwhite whistles (singing rate) per 1-minute interval, number of other males calling during the survey, minutes-since-sunrise, and day-of-season. We also recorded the number of minutes during a 10-minute survey that radio-collared male Northern Bobwhites called. We used logistic regression to estimate availability of radio-collared individuals for 3-minute, 5-minute, and 10-minute surveys. We also modeled number of minutes during 10-minute surveys that radio-collared Northern Bobwhites called, and we modeled singing rate. Individual availability for detection of radio-collared individuals during a 10-minute survey increased by 100% when at least 1 other Northern Bobwhite called during a survey (6.5% to 13.1%) and by 626% when 6 other Northern Bobwhites were calling (6.5% to 47.6%). Individual availability was 30% greater for 10-minute surveys than 5-minute surveys or 55% greater for 10-minute surveys than 3-minute surveys. Northern Bobwhite called most (2.8 ± 0.66 minutes/10-min survey) and at a greater rate (11.8 ± 1.3 calls/10-min period) when at least 5 other Northern Bobwhites called. Practitioners risk biasing population estimates low if individual availability is unaccounted for because species with low populations will not be stimulated by other calling males, are less likely to call, call less frequently, and call fewer times per minute, reducing their individual availability and likelihood to be counted on a survey even when they are present.
The vision of Chandler (Chan) S. Robbins for a continental-scale omnibus survey of breeding birds led to the development of the North American Breeding Bird Survey (BBS). Chan was uniquely suited to develop the BBS. His position as a government scientist had given him experience with designing and implementing continental-scale surveys, his research background made him an effective advocate of the need for a survey to monitor pesticide effects on birds, and his prominence in the birding community gave him connections to infrastructure—a network of qualified volunteer birders who could conduct roadside surveys with standardized point counts. Having started in the eastern United States and the Atlantic provinces of Canada in 1966, the BBS now provides population change information for ∼546 species in the continental United States and Canada, and recently initiated routes in Mexico promise to greatly expand the areas and species covered by the survey. Although survey protocols have remained unchanged for 50 years, the BBS remains relevant in a changing world. Several papers that follow in this Special Section of The Condor: Ornithological Advances review how the BBS has been applied to conservation assessments, especially in combination with other large-scale survey data. A critical feature of the BBS program is an active research program into field and analytical methods to enhance the quality of the count data and to control for factors that influence detectability. Papers in the Special Section also present advances in BBS analyses that improve the utility of this expanding and sometimes controversial survey. In this Perspective, we introduce the Special Section by reviewing the history of the BBS, describing current analyses, and providing summary trend results for all species, highlighting 3 groups of conservation concern: grassland-breeding birds, aridland-breeding birds, and aerial insectivorous birds.
In a recent paper, Hutto (2016a) challenges the need to account for detectability when interpreting data from point counts. A number of issues with model-based approaches to deal with detectability are presented, and an alternative suggested: surveying an area around each point over which detectability is assumed certain. The article contains a number of false claims and errors of logic, and we address these here. We provide suggestions about appropriate uses of distance sampling and occupancy modeling, arising from an intersection of design- and model-based inference. This article is protected by copyright. All rights reserved.
The most popular method used to gain an understanding of population trends or of differences in bird abundance among land condition categories is to use information derived from point counts. Unfortunately, various factors can affect one's ability to detect birds, and those factors need to be controlled or accounted for so that any difference in one's index among time periods or locations is an accurate reflection of differences in bird abundance and not differences in detectability. Avian ecologists could use appropriately sized fixed-area surveys to minimize the chance that they might be deceived by distance-based detectability bias, but the current method of choice is to use a modeling approach that allows one to account for distancebased bias by modeling the effects of distance on detectability or occupancy. I challenge the idea that modeling is the best approach to account for distance-based effects on the detectability of birds because the most important distance-based modeling assumptions can never be met. The use of a fixed-area survey method to generate an index of abundance is the simplest way to control for distance-based detectability bias and should not be universally condemned or be the basis for outright rejection in the publication process.
Accurate estimates of fledging age are needed in field studies to avoid inducing premature fledging or missing the fledging event. Both may lead to misinterpretation of nest fate. Correctly assessing nest fate and length of the nestling period can be critical for accurate calculation of nest survival rates. For researchers who mark nestlings, knowing the age at which their activities may cause young to leave nests prematurely could prevent introducing bias to their studies. We estimated fledging ages from grassland passerine nests monitored from hatching through fledging with miniature video cameras in North Dakota and Minnesota during 1996-2001. We compared these values to those obtained from traditional nest visits and from the literature. Mean and modal fledging ages for video-monitored nests were generally similar to those for visited nests, although Clay-colored Sparrows (Spizella pallida) typically fledged 1 day earlier from visited nests. Average fledging ages from both video and nest visits occurred within ranges reported in the literature, but expanded by 1-2 days the upper age limit for Clay-colored Sparrows and the lower age limit for Bobolinks (Dolichonyx oryzivorus). Video showed that eggs hatched throughout the day, whereas most young fledged in the morning (06:30-12:30 CDT). Length of the hatching period for a clutch was usually >1 day and was positively correlated with clutch size. Length of the fledging period for a brood was usually < 1 day, and in nearly half the nests fledging was completed within
In the northeastern United States, grassland birds regularly use agricultural fields as nesting habitat. However, birds that nest in these fields regularly experience nest failure as a result of agricultural practices, such as mowing and grazing. Therefore, information on both spatial and temporal patterns of habitat use is needed to effectively manage these species. We addressed these complex habitat use patterns by conducting point counts during three time intervals between May 21, 2002 and July 2, 2002 in agricultural fields across the Champlain Valley in Vermont and New York. Early in the breeding season, Bobolinks (Dolichonyx oryzivorus) used fields in which the landscape within 2500 m was dominated by open habitats. As mowing began, suitable habitat within 500 m became more important. Savannah Sparrows (Passerculus sandwichensis) initially used fields that contained a high proportion of suitable habitat within 500 m. After mowing, features of the field (i.e., size and amount of woody edge) became more important. Each species responded differently to mowing: Savannah Sparrows were equally abundant in mowed and uncut fields, whereas Bobolinks were more abundant in uncut fields. In agricultural areas in the Northeast, large areas (2000 ha) that are mostly nonforested and undeveloped should be targeted for conservation. Within large open areas, smaller patches (80 ha) should be maintained as high-quality, late-cut grassland habitat.
The North American Breeding Bird Survey is a roadside, count-based survey conducted by volunteer observers. Begun in 1966, it now is a primary source of information on spatial and temporal patterns of population change for North American birds. We analyze population change for states, provinces, Bird Conservation Regions, and the entire survey within the contiguous United States and southern Canada for 426 species using a hierarchical log-linear model that controls for observer effects in counting. We also map relative abundance and population change for each species using a spatial smoothing of data at the scale of survey routes. We present results in accounts that describe major breeding habitats, migratory status, conservation status, and population trends for each species at several geographic scales. We also present composite results for groups of species categorized by habitats and migratory status. The survey varies greatly among species in percentage of species' range covered and precision of results, but consistent patterns of decline occur among eastern forest, grassland, and aridland obligate birds while generalist bird species are increasing.
Detection in studies of species abundance and distribution is often imperfect. Assuming perfect detection introduces bias into estimation that can weaken inference upon which understanding and policy are based. Despite availability of numerous methods designed to address this assumption, many refereed papers in ecology fail to account for non-detection error. We conducted a quantitative literature review of 537 ecological articles to measure the degree to which studies of different taxa, at various scales, and over time have accounted for imperfect detection. Overall, just 23% of articles accounted for imperfect detection. The probability that an article incorporated imperfect detection increased with time and varied among taxa studied; studies of vertebrates were more likely to incorporate imperfect detection. Among articles that reported detection probability, 70% contained per-survey estimates of detection that were less than 0.5. For articles in which constancy of detection was tested, 86% reported significant variation. We hope that our findings prompt more ecologists to consider carefully the detection process when designing studies and analyzing results, especially for sub-disciplines where incorporation of imperfect detection in study design and analysis so far has been lacking.
In North America, grassland bird abundances have declined, likely as a result of loss and degradation of prairie habitat. Given the expense and limited opportunity to procure new grasslands, managers are increasingly focusing on ways to improve existing habitat for grassland birds, using techniques such as tree removal. To examine the potential for tree removal to benefit grassland birds, we conducted 446 point counts on 35 grassland habitat patches in the highly fragmented landscape of west-central Minnesota during 2009–2011. We modeled density of four grassland bird species in relation to habitat composition at multiple scales, focusing on covariates that described grass, woody vegetation (trees and large shrubs), or combinations of grass and woody vegetation. The best-supported models for all four grassland bird species incorporated variables measured at multiple scales, including local features such as grass height, litter depth, and local tree abundance, as well as landscape-level measures of grass and tree cover. Savannah Sparrows (Passerculus sandwichensis), Sedge Wrens (Cistothorus platensis), and Bobolinks (Dolichonyx oryzivorus) responded consistently and negatively to woody vegetation, but response to litter depth, grass height, and grassland extent were mixed among species. Our results suggest that reducing shrub and tree cover is more likely to increase the density of grassland birds than are attempts to improve grass quality or quantity. In particular, tree removal is more likely to increase density of Savannah Sparrows and Sedge Wrens than any reasonable changes in grass quality or quantity. Yet tree removal may not result in increased abundance of grassland birds if habitat composition is not considered at multiple scales. Managers will need to either manage at large scales (80–300 ha) or focus their efforts on removing trees in landscapes that contain some grasslands but few nearby wooded areas.
Conservation actions are ongoing for the federally and provincially threatened bobolink ( Dolichonyx oryzivorus ) in Ontario, Canada because of population declines. One conservation action being implemented in agricultural grasslands is the delay of hay harvesting and livestock grazing until 15 July, a general guideline for when bobolink finish breeding. Efficient methods to assess when breeding ceases could benefit bobolink and farmers engaged in conservation by ensuring nesting is finished before agricultural activity occurs and enabling agricultural activity earlier when breeding is finished before 15 July. We conducted field surveys to assess if low‐intensity surveys (i.e., transect surveys, point counts, roadside counts) could accurately detect when bobolink finish breeding compared to intensive monitoring (i.e., spot mapping and nest monitoring). We monitored 29 pastures in 2017 in eastern Ontario and 9 hay fields, 10 restored grasslands, and 6 fallow fields in 2018 in southern Ontario. The date breeding finished varied across fields in 2017 from 13 June to 29 July and in 2018 from 24 June to 30 July, based on spot mapping and nest monitoring. Transect surveys and point counts were good predictors of breeding in a field, as confirmed through spot mapping and nest monitoring, based on generalized linear mixed models. We recommend using transect surveys or point counts as an efficient field method to assess when bobolink finish breeding in a field targeted for bobolink conservation. Our results suggest that 2 consecutive visits that fail to detect evidence of breeding in early July are needed to reasonably infer that breeding has likely finished, leaving a small probability (i.e., <0.01) that breeding may still be occurring. Determining when bobolink finish breeding in fields intended to provide nesting refuges can help maximize conservation benefits and minimize negative effects on agricultural production. © 2020 The Wildlife Society.
Although point counts are frequently used in ornithological studies, basic assumptions about detection probabilities often are untested. We apply a double-observer approach developed to estimate detection probabilities for aerial surveys (Cook and Jacobson 1979) to avian point counts. At each point count, a designated “primary” observer indicates to another (“secondary”) observer all birds detected. The secondary observer records all detections of the primary observer as well as any birds not detected by the primary observer. Observers alternate primary and secondary roles during the course of the survey. The approach permits estimation of observer-specific detection probabilities and bird abundance. We developed a set of models that incorporate different assumptions about sources of variation (e.g. observer, bird species) in detection probability. Seventeen field trials were conducted, and models were fit to the resulting data using program SURVIV. Single-observer point counts generally miss varying proportions of the birds actually present, and observer and bird species were found to be relevant sources of variation in detection probabilities. Overall detection probabilities (probability of being detected by at least one of the two observers) estimated using the double-observer approach were very high (>0.95), yielding precise estimates of avian abundance. We consider problems with the approach and recommend possible solutions, including restriction of the approach to fixed-radius counts to reduce the effect of variation in the effective radius of detection among various observers and to provide a basis for using spatial sampling to estimate bird abundance on large areas of interest. We believe that most questions meriting the effort required to carry out point counts also merit serious attempts to estimate detection probabilities associated with the counts. The double-observer approach is a method that can be used for this purpose.
N‐mixture models provide an appealing alternative to mark‐recapture models, in that they allow for estimation of detection probability and population size from count data, without requiring that individual animals be identified. There is, however, a cost to using the N‐mixture models: inference is very sensitive to the model's assumptions. We consider the effects of three violations of assumptions which might reasonably be expected in practice: double counting, unmodeled variation in population size over time, and unmodeled variation in detection probability over time. These three examples show that small violations of assumptions can lead to large biases in estimation. The violations of assumptions we consider are not only small qualitatively, but are also small in the sense that they are unlikely to be detected using goodness‐of‐fit tests. In cases where reliable estimates of population size are needed, we encourage investigators to allocate resources to acquiring additional data, such as recaptures of marked individuals, for estimation of detection probabilities. This article is protected by copyright. All rights reserved.
Monitoring animal populations is central to wildlife and fisheries management, and the use of N-mixture models toward these efforts has markedly increased in recent years. Nevertheless, relatively little work has evaluated estimator performance when basic assumptions are violated. Moreover, diagnostics to identify when bias in parameter estimates from N-mixture models is likely is largely unexplored. We simulated count data sets using 837 combinations of detection probability, number of sample units, number of survey occasions, and type and extent of heterogeneity in abundance or detectability. We fit Poisson N-mixture models to these data, quantified the bias associated with each combination, and evaluated if the parametric bootstrap goodness-of-fit (GOF) test can be used to indicate bias in parameter estimates. We also explored if assumption violations can be diagnosed prior to fitting N-mixture models. In doing so, we propose a new model diagnostic, which we term the quasi-coefficient of variation (QCV). N-mixture models performed well when assumptions were met and detection probabilities were moderate (i.e., ≥0.3), and the performance of the estimator improved with increasing survey occasions and sample units. However, the magnitude of bias in estimated mean abundance with even slight amounts of unmodeled heterogeneity was substantial. The parametric bootstrap GOF test did not perform well as a diagnostic for bias in parameter estimates when detectability and sample sizes were low. The results indicate the QCV is useful to diagnose potential bias and that potential bias associated with unidirectional trends in abundance or detectability can be diagnosed using Poisson regression. This study represents the most thorough assessment to date of assumption violations and diagnostics when fitting N-mixture models using the most commonly implemented error distribution. Unbiased estimates of population state variables are needed to properly inform management decision making. Therefore, we also discuss alternative approaches to yield unbiased estimates of population state variables using similar data types, and we stress that there is no substitute for an effective sample design that is grounded upon well-defined management objectives.
Binomial N-mixture models have proven very useful in ecology, conservation and monitoring: they allow estimation and modeling of abundance separately from detection probability using simple counts. Recently, doubts about parameter identifiability have been voiced. I conducted a large-scale screening test with 137 bird data sets from 2,037 sites. I found virtually no identifiability problems for Poisson and zero-inflated Poisson (ZIP) binomial N-mixture models, but negative-binomial (NB) models had problems in 25% of all data sets. The corresponding multinomial N-mixture models had no problems. Parameter estimates under Poisson and ZIP binomial and multinomial N-mixture models were extremely similar. Identifiability problems became a little more frequent with smaller sample sizes (267 and 50 sites), but were unaffected by whether the models did or did not include covariates. Hence, binomial N-mixture model parameters with Poisson and ZIP mixtures typically appeared identifiable. In contrast, NB mixtures were often unidentifiable, which is worrying since these were often selected by AIC. Identifiability of binomial N-mixture models should always be checked. If problems are found, simpler models, integrated models which combine different observation models or the use of external information via informative priors or penalized likelihoods may help. This article is protected by copyright. All rights reserved.
N-mixture models describe count data replicated in time and across sites in terms of abundance N and detectability p. They are popular because they allow inference about N while controlling for factors that influence p without the need for marking animals. Using a capture-recapture perspective, we show that the loss of information that results from not marking animals is critical, making reliable statistical modeling of N and p problematic using just count data. One cannot reliably fit a model in which the detection probabilities are distinct among repeat visits as this model is overspecified. This makes uncontrolled variation in p problematic. By counter example, we show that even if p is constant after adjusting for covariate effects (the "constant p" assumption) scientifically plausible alternative models in which N (or its expectation) is non-identifiable or does not even exist as a parameter, lead to data that are practically indistinguishable from data generated under an N-mixture model. This is particularly the case for sparse data as is commonly seen in applications. We conclude that under the constant p assumption reliable inference is only possible for relative abundance in the absence of questionable and/or untestable assumptions or with better quality data than seen in typical applications. Relative abundance models for counts can be readily fitted using Poisson regression in standard software such as R and are sufficiently flexible to allow controlling for p through the use covariates while simultaneously modeling variation in relative abundance. If users require estimates of absolute abundance, they should collect auxiliary data that help with estimation of p.
Applied Hierarchical Modeling in Ecology: Distribution, Abundance, Species Richness offers a new synthesis of the state-of-the-art of hierarchical models for plant and animal distribution, abundance, and community characteristics such as species richness using data collected in metapopulation designs. These types of data are extremely widespread in ecology and its applications in such areas as biodiversity monitoring and fisheries and wildlife management. This first volume explains static models/procedures in the context of hierarchical models that collectively represent a unified approach to ecological research, taking the reader from design, through data collection, and into analyses using a very powerful class of models. Applied Hierarchical Modeling in Ecology, Volume 1 serves as an indispensable manual for practicing field biologists, and as a graduate-level text for students in ecology, conservation biology, fisheries/wildlife management, and related fields. Provides a synthesis of important classes of models about distribution, abundance, and species richness while accommodating imperfect detection Presents models and methods for identifying unmarked individuals and species Written in a step-by-step approach accessible to non-statisticians and provides fully worked examples that serve as a template for readers' analyses Includes companion website containing data sets, code, solutions to exercises, and further information
Estimating species abundance is important for land managers, especially for monitoring conservation efforts. The two main survey methods for estimating avian abundance are point counts and transects. Previous comparisons of these two methods have either been limited to a single species or have not included detection probability. During the 2012 breeding season, we compared and assessed the efficiency (precision for amount of effort) of point count time of detection (PCTD) and dependent double-observer transect (TRMO) methods based on detection probabilities and abundance estimates of five species of songbirds that use a range of habitats in a prairie system in Montana dominated by sagebrush and grassland vegetation. Our focal species included Vesper Sparrows (Pooecetes gramineus), a generalist species found in both shrub and grassland habitat, shrub-obligate Brewer's Sparrows (Spizella breweri), and McCown's Longspurs (Rhynchophanes mccownii), Horned Larks (Eremophila alpestris), and Western Meadowlarks (Sturnella neglecta), three species of grassland obligates that prefer different grass heights. Detection probabilities were significantly higher for TRMO surveys, with less variation for all five species and differences most pronounced for Brewer's Sparrows and Horned Larks. PCTD surveys required less field effort (~8–20 fewer people minutes per plot) than TRMO surveys because the TRMO surveys required two people. However, time spent on TRMO surveys provided between 0.38 and 87 times more precision per people minute than PCTD surveys. Our results suggest that TRMO surveys provide a more efficient (measured as time spent per unit of standard error) field-based technique in sagebrush prairie systems for the species we investigated, resulting in more precise detection and abundance estimates.
We briefly outline the information-theoretic (I-T) approaches to valid inference including a review of some simple methods for making formal inference from all the hypotheses in the model set (multimodel inference). The I-T approaches can replace the usual t tests and ANOVA tables that are so inferentially limited, but still commonly used. The I-T methods are easy to compute and understand and provide formal measures of the strength of evidence for both the null and alternative hypotheses, given the data. We give an example to highlight the importance of deriving alternative hypotheses and representing these as probability models. Fifteen technical issues are addressed to clarify various points that have appeared incorrectly in the recent literature. We offer several remarks regarding the future of empirical science and data analysis under an I-T framework.
Introduction Monitoring is a critically important activity for assessing the status of a system, such as the health of an individual, the balance in one's checking account, profits and losses of a business, the economic activity of a nation, or the size of an animal population. Monitoring is especially vital for evaluating changes in the system associated with specific known impacts occurring to the system. It is also valuable for detecting unanticipated changes in the system and identifying plausible causes of such changes, all in time to take corrective action. Before proceeding, we should define “monitoring.” One definition of “monitor” (Microsoft Corporation 2009) is “to check something at regular intervals in order to find out how it is progressing or developing.” The key point here is “at regular intervals,” suggesting a continuing process. Some definitions do not indicate the repetitive nature of monitoring and are basically synonymous with “observing.” Most monitoring, in the strict sense of the word, is intended to persist for long periods of time, perhaps indefinitely or permanently. Similarly, Thompson et al. (1998: 3) referred to the “repeated assessment of status” of something, but noted that the term “monitor” is sometimes used for analogous activities such as collecting baseline information or evaluating projects for either implementation or effectiveness. For their purposes, they restricted the term to involve repeated measurements collected at a specified frequency of time units. Let us adopt that definition, recognizing that repeated measurements imply collecting comparable information on each occasion.
Researchers often use fixed-radius point counts to estimate density (absolute or relative) of territorial male grassland birds, but in doing so they must assume that detectability of birds is constant (or nearly so) among habitats, years, and/or species. If the assumption is violated, comparisons of density among species and/or habitats are invalid because counts are confounded by changes in both detectability and density. Recent advances in the theory and methods of distance sampling allow biologists to estimate detection probabilities and may provide more accurate estimates of density than other techniques. We conducted 450 point counts at 150 points in Lostwood National Wildlife Refuge, North Dakota, in 1994, estimated the distance to each male detected aurally, and estimated density for the 10 most abundant species with two methods: (1) using data from 50- or 75-meter-radius plots (estimates based on the average number of males heard per point count) and (2) using program DISTANCE and a maximum detection distance of 400 meters (estimates based on number of males heard and the detectability of males). We felt we were able to meet the assumptions of distance sampling and reliably estimate absolute density. Results generated by program DISTANCE suggested that males of some species went undetected on 50- and/or 75-meter plots. Density estimates from the two analysis methods were similar, however, and did not differ for any species (P > 0.05). Estimates from fixed-radius point counts in our study thus appeared to provide valid estimates of density (absolute and relative). In other habitats or for other species, the problem of undetected males may be more pronounced. In such cases, distance-sampling techniques may provide an important alternative for collecting and analyzing density data if adequate samples are obtained and unbiased distance data can be collected.
This chapter describes a variety of counting techniques for birds so that the reader may choose the technique that best fits his or her research objectives and requirements. It covers index methods for use in an index monitoring program (gathering general information on species status) as well as techniques for obtaining valid estimates of spatial distribution and abundance/density for use in an inferential monitoring program (that is, one in which some average change in population can be reliably detected). This chapter concentrates on methods for counting breeding birds because these are the most common survey situations. In theory, similar methods could be applied to winter populations of birds, but a number of methods need an adequate number of observations to produce reliable estimates, which may or may not be the case in winter surveys. A complete count or census of birds within a specified area is rarely possible in most field situations. Possible exceptions to this may include counts of birds in roosts, nesting colonies, or large, visible flocks. However, conditions affecting visibility and detectability of individuals or nests will determine if a true census is realistic.
This chapter gives results from some illustrative exploration of the performance of information-theoretic criteria for model selection and methods to quantify precision when there is model selection uncertainty. The methods given in Chapter 4 are illustrated and additional insights are provided based on simulation and real data. Section 5.2 utilizes a chain binomial survival model for some Monte Carlo evaluation of unconditional sampling variance estimation, confidence intervals, and model averaging. For this simulation the generating process is known and can be of relatively high dimension. The generating model and the models used for data analysis in this chain binomial simulation are easy to understand and have no nuisance parameters. We give some comparisons of AIC versus BIC selection and use achieved confidence interval coverage as an integrating metric to judge the success of various approaches to inference.
Many investigators begin field studies by using convenience sampling and then collect only index values (i.e., raw counts). This combination of poor field practices is nearly certain to yield untrustworthy results. Numbers (i.e., index values) are not always data, and many numbers (large sample size) do not always mean good data. Instead, the word data implies an information content with respect to some objective. Often numbers can be collected, but they may not represent data because they have little meaning and cannot be interpreted without making critical, but very unrealistic, assumptions. Such numbers are not trustworthy and cannot lead to valid inferences about the population of interest. We have made serious errors in ad hoc surveys of many terrestrial populations; efforts are underway to try to alter survey protocol to lessen these deficiencies in some cases. However, new surveys are being planned for reptile, amphibian, and insect populations, and the same fundamental errors may be repeated. Convenience samples are being relied upon without a way to make valid inferences about populations of interest. Index values are being taken without regard for highly variable and perhaps time-trending detection probabilities. Numbers from such surveys will not provide a basis for reliable knowledge and will represent only wasted resources. We must improve our understanding of these 2 fundamental issues and obtain reliable information or professionals in other disciplines will not take us seriously. Delury (1954: 293) commented,"...it is an expensive impropriety to maintain that an untrustworthy estimate is better than none." Professors ought to instill in their students the importance of probabilistic sampling in field studies. Similarly, the use of index values ought to be discouraged strongly because alternatives exist that will provide, under given assumptions, meaningful parameter estimates, measures of their precision, and other forms of reliable hfformation (see Thompson et al. 1998, Seber and Schwarz 1999). Editors and referees must begin to ask whether the sample data were taken in such a way as to allow a formal inductive inference to the population of interest. Such information should appear clearly in the Methods section of papers submitted for publication. Data resulting from convenience sampling are not acceptable on fundamental grounds. Similarly, raw counts as index values are not reliable and should be published only in unusual circumstances. In my opinion, we need a much higher standard for what is intrinsically acceptable in our profession.
Abundance estimators that account for imperfect detection, such as N-mixture models, assume that detection of individuals is independent of abundance. Using spot-mapping and N-mixture models applied to point-count data, we estimated abundance of Golden-cheeked Warblers (Setophaga chrysoparia) in two years at six study sites at the Balcones Canyonlands Preserve, Austin, Texas. N-mixture model estimates deviated from spot-mapping estimates at the site level by overestimating at low abundances, and at the survey-station level by underestimating at high abundance, which suggests that model assumptions may have been violated. We tested whether detection of individuals is influenced by abundance by assessing per capita song rate in relation to abundance. Per capita song rate increased with abundance, illustrating how the behavior of a territorial passerine may violate the independent-detectability assumption. We next explored violation of this assumption at the survey-station level by applying N-mixture models to simulated data exhibiting heterogeneity in detection. This exercise revealed a slight but increasingly negative bias (underestimation of abundance) in the estimator as the actual abundance increased, given positive density-dependent detection. The simulations also revealed a potential effect of sampling variation on misestimation by N-mixture model estimators. Assessing the strength, basis, and prevalence of density-dependent detection; further analyzing the effects of nonrandom heterogeneity in producing estimator bias; and accounting for nonrandom detection heterogeneity in abundance estimators are fruitful areas for further study.
A detailed study of seasonal changes in bird populations was made at the Patuxent Research Refuge, located between Bowie and Laurel, Maryland, during the years 1936-1949. The history of the Refuge is reviewed and its physical and biological characteristics summarized. The methods of study used during the investigation included: periodic censuses of a representative 304-acre study area over a two-year period; a census of the breeding population of the entire Refuge during one year; detailed population studies of representative habitats during the breeding season; censuses of the wintering population of the entire Refuge during two years; general surveys of wintering populations for seven years; and general observations of seasonal changes in bird populations over a fourteen-year period, including data from an extensive banding program and from many special types of censuses. The phenology of the Refuge is described in considerable detail throughout the year, with special attention given to major fluctuations in bird populations as correlated with climatic, changes and with seasonal aspection of the vegetation. The component species of birds in the more important migration waves are listed. Figures approximating the Refuge breeding and wintering populations are given, while indices representing the relative abundance of bird populations, based on figures from the two-year seasonal population study, were obtained for the entire year. The greatest variety of species as well as the greatest number of individuals occurred on the Refuge during the migration periods in spring and fall, the variety of species being slightly higher in spring than in fall, while the population of individuals was considerably higher in fall. Wintering and breeding populations were low and relatively stable compared to the populations at other seasons. The ecological affinities of the bird populations differed greatly from one season to another. Species characteristic of edge habitats were much more numerous in winter, while forest species were predominant in summer. Insectivorous species comprised a large proportion (40 to 60 percent) of the total population during the warmer months, but were of minor importance in winter. The greatest number of species of birds on the Refuge occurred during the population peaks of insectivorous species, while the largest number of individuals was found during the population peaks of omnivorous and herbivorous species. The population peaks of insectivorous species were found to occur much later in spring and considerably earlier in fall than the corresponding peaks of omnivorous and herbivorous species. The Fringillidae contributed the greatest number of individuals in winter, while the Parulidae was the most important family (numerically) in summer. Water birds and marsh birds were relatively unimportant throughout the year, due to the scarcity of suitable habitats. Permanent resident species were found to vary from about one-fifth to slightly less than one-half of the total population throughout the year, although many individuals of these species were either transients or part-time residents. Summer residents and winter residents were more abundant than permanent residents during their respective periods of occurrence. During the greater part of the migration period, transient species were found to comprise only 10 to 20 percent of the total population. However, transient individuals of all species would account for a much larger proportion of the population at this time. After comparing the results of these investigations with similar studies in other areas; it is believed that the seasonal population changes on the Patuxent Research Refuge are fairly representative of those occurring throughout the Middle Atlantic and East-central States. Yearly variations in seasonal population Changes are described and the causative factors indicated, when known. Of these, food supply and weather conditions were generally the most important. The data from the seasonal population studies on the Refuge support; certain conclusions made by Kendeigh (1934) regarding the migratory movements of birds. These are: "The regulation of migration as to time is controlled in the spring by rising daily maximum and night temperatures and changing relative proportions daily of light and darkness. In the autumn, decreasing temperatures, particularly at night, longer nights and shorter days, and for some species, decreasing food supply, are most important." The seasonal distribution of the population of each of the 229 species of birds that have been recorded on the Refuge is described in detail. This includes data on migration periods such as earliest dates of arrival, latest dates of departure, median dates of arrival and departure, and migration peaks. Population indices are also listed for many of the more common species throughout their periods of occurrence, and the numerical status of wintering and breeding populations is indicated as well. In many cases, the highest numbers of individuals observed in one day during the migration periods are given and the size of flocks at different seasons described.
We studied variation in density estimates from spot mapping that was attributable to analysts and observers, using expert birders with little or no prior experience with spot mapping. Three observers independently spot mapped one 42-ha plot (Markwood) in mixed-conifer forest, and four others independently spot mapped another (Teakettle). All observers analyzed all maps. Consistency among analysts and observers in estimating the numbers of territories of breeding species on each plot was generally poor. Across all combinations of analysts and maps, 71% of all ANOVAs had significant analyst and/or observer effects. Observer effects were generally greater than analyst effects. When observers analyzed their own species maps, CVs of individual species ranged from 0% to 173% (mean 41%) at Markwood and from 0% to 188% (mean 60%) at Teakettle. As in similar studies, mean CVs from pooled totals of all species were less than those from individual species and were within the range of variation found by other researchers. Based on the range of CVs observed among species in this study, the number of sample plots needed to detect a statistical difference in density of a given species between samples is probably prohibitive for most studies. Instead, practitioners need to design studies to control observer and analyst variability.
Research that yields conflicting results rightly causes controversy. Where methodological weaknesses are apparent, there is ready opportunity for discord within the scientific community, which may undermine the entire study.
We use the debate about the role of dingoes C anis dingo in conservation in A ustralia as a case study for a phenomenon that is relevant to all applied ecologists, where conflicting results have been published in high‐quality journals and yet the problems with the methods used in these studies have led to significant controversy.
To alleviate such controversies, scientists need to use robust methods to ensure that their results are repeatable and defendable. To date, this has not occurred in A ustralia's dingo debate due to the use of unvalidated indices that rely on unsupported assumptions.
We highlight the problems that poor methods have caused in this debate. We also reiterate our recommendations for practitioners, statisticians and researchers to work together to develop long‐term, multi‐site experimental research programmes using robust methods to understand the impacts of dingoes on mesopredators.
Synthesis and applications . Incorporating robust methods and appropriate experimental designs is needed to ensure that conservation actions are appropriately focused and are supported with robust results. Such actions will go a long way towards resolving the debate about the role of dingoes in conservation in A ustralia, and other, ecological debates.
Intensive monitoring of bird nests to measure reproductive success is time-consuming and may influence the fate of nests. Reproductive indices that do not require searching for and visiting nests may be reasonable alternatives to nest monitoring if they provide results similar to nest-searching efforts. We evaluated the reproductive index of Vickery et al. (1992) for estimating reproductive success of the dickcissel (Spiza americana) in northeast Kansas, USA. We used nest searching and Vickery et al.'s (1992) reproductive index to compare reproductive success on 20 plots (200 × 200 m). Daily nest survival (DNS) rates averaged 0.911 (SE = 0.011, n = 72 nests), and brown-headed cowbirds (Molothrus ater) accounted for 21% of all nest failures. Surveyors underestimated reproductive index ranks when compared to nest-searching efforts and were inaccurate in their assignment of reproductive success. In particular, surveyors reported successful nests on 3 study plots that fledged no young, probably because young dickcissels moved onto plots after fledging from their natal territories. Our results indicate that the reproductive index of Vickery et al. (1992) may be inappropriate for wary species or those heavily parasitized by brood parasites. We suggest that before relying on the index alone, investigators should use pilot trials to determine whether results from this index are concordant with results from intensive nest-searching efforts for species of interest.
The density and distribution of territories were determined for 21 species in a 48-ha Sierran subalpine forest study plot by an intensive program of spot-mapping and nest monitoring. About 10% of the total breeding individuals were color-banded and about 75% of the nests of all species were found. Variable circular-plot (VCP) censuses were simultaneously conducted in the same study plot. The VCP method, with minimum effort (48 stations), could describe community parameters reasonably well and could distinguish common from rare species, but could not correctly determine the relative abundances of the common species, could not correctly describe the distribution of territories within the study plot, and produced errors in density estimates for the common species that ranged from -57% to +65%. When the effort was increased threefold (144 stations), the accuracy of the method was improved so that it produced more or less acceptable relative abundances for even the common species and was marginally capable of describing the distribution of territories for 37% of the species, particularly for those species whose distributions were markedly non-uniform, but it still produced errors in density estimates for the common species that ranged from -67% to +96%. Interestingly, VCP total count often performed nearly as well as the calculated VCP density in determining relative abundances. The accuracy of the VCP method may be expected to be poor for species with low population densities, large territory sizes, high mobilities, and ventriloqual vocalizations, and for habitats that are dense and highly three-dimensional.
Introduction.- Data management and software.- Advice for teachers.- Exploration.- Linear regression.- Generalised linear modelling.- Additive and generalised additive modelling.- Introduction to mixed modelling.- Univariate tree models.- Measures of association.- Ordination--first encounter.- Principal component analysis and redundancy analysis.- Correspondence analysis and canonical correspondence analysis.- Introduction to discriminant analysis.- Principal coordinate analysis and non-metric multidimensional scaling.- Time series analysis--Introduction.- Common trends and sudden changes.- Analysis and modelling lattice data.- Spatially continuous data analysis and modelling.- Univariate methods to analyse abundance of decapod larvae.- Analysing presence and absence data for flatfish distribution in the Tagus estuary, Portugual.- Crop pollination by honeybees in an Argentinean pampas system using additive mixed modelling.- Investigating the effects of rice farming on aquatic birds with mixed modelling.- Classification trees and radar detection of birds for North Sea wind farms.- Fish stock identification through neural network analysis of parasite fauna.- Monitoring for change: using generalised least squares, nonmetric multidimensional scaling, and the Mantel test on western Montana grasslands.- Univariate and multivariate analysis applied on a Dutch sandy beach community.- Multivariate analyses of South-American zoobenthic species--spoilt for choice.- Principal component analysis applied to harbour porpoise fatty acid data.- Multivariate analysis of morphometric turtle data--size and shape.- Redundancy analysis and additive modelling applied on savanna tree data.- Canonical correspondence analysis of lowland pasture vegetation in the humid tropics of Mexico.- Estimating common trends in Portuguese fisheries landings.- Common trends in demersal communities on the Newfoundland-Labrador Shelf.- Sea level change and salt marshes in the Wadden Sea: a time series analysis.- Time series analysis of Hawaiian waterbirds.- Spatial modelling of forest community features in the Volzhsko-Kamsky reserve.