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Assessing hunters’ ability to identify shot geese: implications for hunting bag accuracy

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Thomas Kjær Christensen at Aarhus University
Thomas Kjær Christensen
Jesper Madsen at Aarhus University
Jesper Madsen
Tommy Asferg at Aarhus University
Tommy Asferg
Jens Peder Hounisen
Jens Peder Hounisen
Jens Peder Hounisen
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Abstract and Figures

Reliable hunting bag statistics are a prerequisite for sustainable harvest management. Recently, Internet-based hunting bag reporting systems have been introduced in some European countries, e.g. Denmark, which may enable faster and more detailed reporting. However, reporting of waterfowl bags on a species-specific level may be biased from the individual hunters’ ability to correctly identify species, particularly because juvenile birds can only be identified from subtle differences. We assessed hunters’ ability to identify the five goose species huntable in Denmark. Identifications were made from a line-up of ten full-bodied geese including adults and juveniles. From a total of 2160 identifications made by active hunters, 85.5% were correct while 14.5% were assigned to a wrong species. Active hunters had on average an identification accuracy of 76.0%, highest for Canada goose (99.1%) and lowest for white-fronted goose (74.6%) and bean goose (73.7%). Identification accuracy was significantly lower for juvenile than for adult individuals of white-fronted and bean geese. Correcting the official Danish Bag Record (2013/2014) for identification accuracy, the bags of white-fronted and bean geese increase by 56.5 and 104.4%, respectively, while the bags of greylag and pink-footed geese decrease by 6.7 and 9.0%; the bag for Canada goose remains unchanged. Although identification accuracy is probably higher under field conditions, the study documents that inaccurate species identification is a source of bias in national bag statistics. Hence, improving identification skills by hunters is important to improve bag data accuracy when based on Internet reporting.
Age distribution of 196 active hunters that made goose identifications at two hunting fairs and two courses for goose hunters in 2013 and 2014 in Denmark (hunter sample) and the age distribution of 13,297 hunters that have reported at least one bagged goose to the Danish Bag Record in the hunting season 2014/2015
Age distribution of 196 active hunters that made goose identifications at two hunting fairs and two courses for goose hunters in 2013 and 2014 in Denmark (hunter sample) and the age distribution of 13,297 hunters that have reported at least one bagged goose to the Danish Bag Record in the hunting season 2014/2015
… 
Average identification score (±SD) in relation to number of identifications made by 221 active hunters, 21 non-active hunters and 11 respondents with unknown hunting status recorded at two hunting fairs and two courses for goose hunters in 2013 and 2014. The number of respondents is shown inside the bars. The black line shows maximum number of correct IDs that can be given
Average identification score (±SD) in relation to number of identifications made by 221 active hunters, 21 non-active hunters and 11 respondents with unknown hunting status recorded at two hunting fairs and two courses for goose hunters in 2013 and 2014. The number of respondents is shown inside the bars. The black line shows maximum number of correct IDs that can be given
… 
Identification accuracy score (IA score) for hunters that have bagged geese and hunters that not have bagged geese in relation to hunter experience, expressed as hunter age (number of hunters in each age class is shown). Only respondents with ten identifications are included. Data were collected at two hunting fairs and two courses for goose hunters in Denmark in 2013 and 2014
Identification accuracy score (IA score) for hunters that have bagged geese and hunters that not have bagged geese in relation to hunter experience, expressed as hunter age (number of hunters in each age class is shown). Only respondents with ten identifications are included. Data were collected at two hunting fairs and two courses for goose hunters in Denmark in 2013 and 2014
… 
a Total bag sizes of geese obtained from the sampled hunter identification accuracy (hunter sample; this study) and the official Bag Record (mandatory annual reporting). For the hunter sample, the number of incorrect identifications assigned to non-huntable goose species is shown. For the grey geese, black horizontal lines mark the total bag sizes estimated from the relative county-wise distribution of wings forwarded to the Wing Survey and the county-wise goose bag (calculation not shown). b The number of incorrect determinations expressed as the deviation between the Bag Record and the hunter sample (negative scale) separated into adult and juvenile birds and the species-specific allocation of these to other species (positive scale). For example, 3446 misidentified greylag geese (2701 adults and 745 juveniles; negative scale) are wrongly identified as 1526 white-fronted geese, 123 pink-footed geese and 1600 bean geese (positive scale)
a Total bag sizes of geese obtained from the sampled hunter identification accuracy (hunter sample; this study) and the official Bag Record (mandatory annual reporting). For the hunter sample, the number of incorrect identifications assigned to non-huntable goose species is shown. For the grey geese, black horizontal lines mark the total bag sizes estimated from the relative county-wise distribution of wings forwarded to the Wing Survey and the county-wise goose bag (calculation not shown). b The number of incorrect determinations expressed as the deviation between the Bag Record and the hunter sample (negative scale) separated into adult and juvenile birds and the species-specific allocation of these to other species (positive scale). For example, 3446 misidentified greylag geese (2701 adults and 745 juveniles; negative scale) are wrongly identified as 1526 white-fronted geese, 123 pink-footed geese and 1600 bean geese (positive scale)
… 
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ORIGINAL ARTICLE
Assessing hunters’ability to identify shot geese: implications
for hunting bag accuracy
Thomas Kjær Christensen
1
&Jesper Madsen
1
&Tommy Asferg
1
&Jens Peder Hounisen
1
&
Lars Haugaard
1
Received: 18 July 2016 /Revised: 5 January 2017 /Accepted: 6 January 2017 /Published online: 13 January 2017
#Springer-Verlag Berlin Heidelberg 2017
Abstract Reliable hunting bag statistics are a prerequisite for
sustainable harvest management. Recently, Internet-based
hunting bag reporting systems have been introduced in some
European countries, e.g. Denmark, which may enable faster
and more detailed reporting. However, reporting of waterfowl
bags on a species-specific level may be biased from the indi-
vidual hunters’ability to correctly identify species, particular-
ly because juvenile birds can only be identified from subtle
differences. We assessed hunters’ability to identify the five
goose species huntable in Denmark. Identifications were
made from a line-up of ten full-bodied geese including adults
and juveniles. From a total of 2160 identifications made by
active hunters, 85.5% were correct while 14.5% were assigned
to a wrong species. Active hunters had on average an identi-
fication accuracy of 76.0%, highest for Canada goose (99.1%)
and lowest for white-fronted goose (74.6%) and bean goose
(73.7%). Identification accuracy was significantly lower for
juvenile than for adult individuals of white-fronted and bean
geese. Correcting the official Danish Bag Record (2013/2014)
for identification accuracy, the bags of white-fronted and bean
geese increase by 56.5 and 104.4%, respectively, while the
bags of greylag and pink-footed geese decrease by 6.7 and
9.0%; the bag for Canada goose remains unchanged.
Although identification accuracy is probably higher under
field conditions, the study documents that inaccurate species
identification is a source of bias in national bag statistics.
Hence, improving identification skills by hunters is important
to improve bag data accuracy when based on Internet
reporting.
Keywords Hunting .Bag size .Wate r f owl .Goose hunting .
Species identification
Introduction
For wildlife populations subject to hunting, information of
hunting bags and of population sizes and trends are of key
importance to ensure sustainable exploitation (Brainerd
2007, European Commission 2008). For migratory species,
clear population and/or flyway delineation is likewise needed,
in order to define the population unit subject to exploitation
and the geographical range of exploitation (see Scott and Rose
1996, Boere and Stroud 2006).
Internationally coordinated inventories on the wintering
grounds (Nagy et al. 2014,2015) provide estimates of most
populations of migratory waterfowl in the West Palaearctic
region which are otherwise difficult to obtain via surveys in
the vast breeding areas in northern Scandinavia and Russia.
However, with few exceptions, internationally coordinated
bag statistics do not exist, making total hunting exploitation
difficult to assess properly, especially for trans-border migra-
tory species. National bag statistic programs exist in most
European countries, but these are not harmonized and differ
in geographical and species coverage, methodology and
timing, often with years of delay between sample year and
reporting. So far, relatively few studies have attempted to pro-
vide a full overview of hunting exploitation of waterfowl
within the European Union (Tamisier 1985, Hirschfeld and
Heyd 2005,Mooij2005),butsuchdataneedtobestandard-
ized and reported on a regular and up-to-date basis if interna-
tional management of migratory species shall be effective and
*Thomas Kjær Christensen
tk@dmu.dk
1
Department of Bioscience, Aarhus University, Grenåvej 14,
DK-8410 Rønde, Denmark
Eur J Wildl Res (2017) 63: 20
DOI 10.1007/s10344-017-1080-y
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
... For example, in Kansas, USA, waterfowl hunters are asked to report the species (via an online reporting platform) they harvested whilst hunting on state-owned sites. It is unrealistic to assume that all waterfowl hunters have perfect waterfowl identification skills (see Wilson & Rohwer 1995;Christensen et al. 2017) and this imperfect knowledge may introduce biases into self-reported hunter harvest data. ...
... Given that past research (e.g. Wilson & Rohwer 1995;Christensen et al. 2017) and anecdotal information (e.g. posts on social media, news stories, conversations with hunters and waterfowl managers in the field) suggests that hunters may find it difficult to correctly identify particular waterfowl species and sex, we predicted that our population of respondents would also have imperfect identification skills. ...
... Thus, waterfowl hunters in different regions of the North American Central Flyway may have a more difficult time identifying female Lesser Scaup. Indeed, hunters are more likely to identify waterfowl species successfully if they are commonly encountered in the region in which they hunt (Wilson & Rohwer 1995;Christensen et al. 2017). Future studies should identify flywayspecific patterns in species misidentification and latitudinal variation in waterfowl identification skills. ...
Testing waterfowl hunters' waterfowl identification skills
Article
Full-text available
  • Dec 2019
Waterfowl management in North America is partially informed by hunter harvest data, which includes the number and sex of each species harvested. Self-reporting harvest via online surveys or paper forms is common for many agencies and at wildlife management areas. For these data to be useful to managers, however, it is critical that self-reported harvest data are precise and accurate. If this assumption is violated, harvest data may be biased and subsequent management efforts misinformed. We surveyed waterfowl hunters (n = 149) in Kansas, USA, immediately after the regular waterfowl hunting season in autumn-winter 2017/2018 to assess their ability to identify waterfowl to species and sex. In particular, participants attending events focused on waterfowl hunting and wetland conservation were asked to complete a survey that tested their ability to identify Northern Pintail Anas acuta, Lesser Scaup Aythya affinis, Canvasback Aythya valisineria and Redhead Aythya americana from colour photographs of breeding-plumage waterbirds commonly encountered in North America's Central Flyway. Respondents' average number of days spent hunting waterfowl during the 2017/2018 Kansas waterfowl season was 22 days-almost six times greater than the average Kansas waterfowl hunter during the same season. Seventy-nine percent of respondents misidentified at least one photograph. The number of days that an individual hunted during the 2017/2018 waterfowl season was generally a good predictor of successful identification. Participants misidentified female Lesser Scaup and Redhead more than other species and sex. Given that our survey included avid waterfowl hunters and high-definition photographs of waterfowl in breeding plumage, our results likely underestimate false identifications and suggest there may be a bias in self-reported waterfowl harvest data. We propose that self-reporting mediums for waterfowl harvest (both online and on paper forms) also include colour photographs of species that could potentially be harvested within the area of reporting.
View
... Accidentally killing protected species mistaken for legitimate quarry species presents a problem to threatened wildlife (Agreement on the Conservation of African-Eurasian Migratory Waterbirds [AEWA], 2015). For populations subject to legal hunting, accurate identification is important to ensure sustainable exploitation and avoid impacts on nontarget species (Christensen, Madsen, Asferg, Peder Hounisen, & Haugaard, 2017;European Commission, 2008). The ability of hunters to shoot selectively may vary with species, environmental conditions, and hunter experience (European Commission, 2008). ...
... Though scarce, evaluations of hunters' speciesidentification skills have mixed outcomes. One study assessing hunters' ability to identify five quarry goose species in Denmark found that 14.5% of 2,160 identifications were incorrect (Christensen et al., 2017). While most hunters on the Mississippi Flyway were able to recognize common waterfowl, females of taxa rarely encountered were frequently misidentified (Wilson & Rohwer, 1995). ...
... Grey shading denotes the Nenets autonomous Okrug (NAO) and white shading, Arkhangelsk oblast (AO). In AO, only hunters on the mainland (and not the island of Novaya Zemlya) were surveyed as a "hunter"), and knowledge about Bewick's swan ecology and the laws protecting them (Table S1; European Commission, 2008; Robinson et al., 2016;Christensen et al., 2017). ...
Conservation implications of misidentification and killing of protected species
Article
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Killing protected species mistaken for morphologically similar quarry species, or species with weaker protection, can hinder their conservation. Despite policy aims to reduce threats from illegal killing, information is lacking on susceptible species, conservation impacts and the identification accuracy of hunters. We examined the ability of hunters (n = 232) in Arctic Russia to identify the endangered Northwest European Bewick's swan Cygnus columbianus bewickii using photographs. Only 14% (n = 33) identified this species correctly and distinguished it from sympatric and congeneric whooper swans C. cygnus and mute swans C. olor, with 15% of individuals admitting to accidentally hunting a Bewick's swan in the previous 3 years. We conclude that there is a risk of Bewick's swans being shot accidentally when mistaken for similar species with less legal protection. Improving hunters' skills in discerning protected from legitimate quarry species is likely to be an effective tool for conservation of morphologically similar species.
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... Despite the acknowledged need for better data on human offtake, only few actions have been taken to better estimate the quality (age, sex and population) and quantity of harvested waterfowl. Correct identi cation of harvested geese is often non-trivial, and hunters are known to make mistakes in identifying hunted waterfowl species (Christensen et al. 2017). Particularly challenging is identi cation of goose subspecies, such as within the bean goose clade. ...
Genetic assessment of subspecies composition in bean goose (Anser fabalis) harvest in Sweden, Finland and Estonia
Preprint
Full-text available
  • Oct 2024
Bean goose (Anser fabalis) harvest in Europe consists of two subspecies, whose conservation statuses are different. However, the proportions of each subspecies in hunting bags are unknown. We studied the subspecies composition among harvested bean geese in Sweden, Finland and Estonia as a case study by sequencing a short mitochondrial DNA (mtDNA) region (210 bp) for subspecies identi cation. The proportion of taiga bean geese (A. f. fabalis) over two hunting seasons was 94% in Sweden, but only 5.8% and 11% in Estonia and southeastern Finland, respectively. Majority of harvested bean geese in Estonia and southeastern Finland were tundra bean geese (A. f. rossicus), and hence the results show that the Finnish spatio-temporal harvest regulations have successfully managed to focus the harvest mostly to the abundant tundra bean goose. We also detected mitochondrial heteroplasmy, i.e. multiple mtDNA variants within some of the individuals. In addition, we discovered a few exceptional individuals with an mtDNA haplotype belonging to eastern taiga bean goose (A. f. middendor i) or greater white-fronted goose (A. albifrons), which could be hybrids between bean goose subspecies or interspeci c hybrids due to untypical morphology. Our method is more cost-e cient than previously used molecular methods, and could be used to monitor bean goose hunting bag in the future.
View
... On the other hand, the observation error can be split into (1.1) an overcoverage error, when the sampling frame includes replicated hunters (i.e. the same hunter can report his/her hunting bag several times) or hunters no longer active (leading to structural null hunting bags; see the section "Variable of interest"), and (1.2) a response error, caused by discrepancies between the hunting bags reported by the hunters and the actual ones (in particular, when hunters do not report their individual hunting bags, for instance after a group driven hunt). Some causes specific to hunting bag surveys can lead to response errors, such as (1.2.1) a recall (or memory) error corresponding to the inability to recall the exact value of the bag, leading to omission or digit preference (Atwood 1956;Sen 1972;Wright 1978;Filion 1980;Chu et al. 1992;Miller and Anderson 2002;Beaman 2002;Beaman et al. 2005a, b;Vaske and Beaman 2006); (1.2.2) a misclassification error, that is, attributing the bag to the wrong species, either because of misidentification or misnaming (Atwood 1956;Sen 1971;Christensen et al. 2017b); (1.2.3) a reporting error (or mechanical error in the sense of MacDonald and Dillman 1968), arising through mistakes when completing the questionnaire; and (1.2.4) a prestige error, that is a deliberate distortion by intentionally inflating the reported harvest (Atwood 1956;MacDonald and Dillman 1968;Sen 1973). Of course, other error types exist and could be added to this taxonomy (i.e. ...
Moving from intentions to actions for collecting hunting bag statistics at the European scale: some methodological insights
Article
Full-text available
  • Aug 2020
  • EUR J WILDLIFE RES
For migratory birds, sustainable harvest management based on quantitative modelling needs cross-border hunting bag statistics. At the European scale, proper modelling requires both reliable and mutually compatible hunting bag data between regions and countries. Owing to the absence of harmonisation among the different hunting bag collecting schemes in Europe and the lack of methodological metadata, adaptive management at the flyway scale is currently extremely challenging for a number of species. For improving the current state of affairs, we expose statistical concepts, terminology and issues inherent to hunting bag data collection schemes; identify the multiplicity of error sources for being able to judge the quality of hunting bag statistics; call for a harmonisation process; discuss the origin of the hurdles in the production of standardised hunting bag statistics at the European scale; and suggest some potential avenues for future actions for overcoming them.
View
... However, the data depend upon survey information from hunters, which relies on the accuracy of their bird identification. Christensen et al. (2017) found that hunters in Denmark asked to identify between five goose species averaged 76% accuracy. Some species were more easily identified than others (e.g. ...
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The global offtake of wild animals is valued at US$400 billion annually and supports the livelihoods of 15% of the global population. Wetlands are amongst the most important ecosystems globally, but offtake may represent a substantial pressure. This study assessed the availability of information and evaluated the offtake of wild animals from wetlands by focussing on fish and waterbirds. A literature search identified 2726 studies on wetland offtake. Scoping of these resulted in 82 studies that contained quantitative information on fish or waterbird offtake. Fishing offtake statistics for inland waters are collated nationally by some governments, but other sources of information are few. Reporting of fish offtake for species or across scales was constrained by insufficient detail, even in relatively well-documented countries such as Bangladesh. Although government hunting statistics from Europe and North America were available, there was little waterbird data from less economically developed countries. The case of Canada indicated that the species richness and composition of waterbirds taken varied between indigenous subsistence and recreational hunting communities. Hidden (unquantified) offtake, of both fish and waterbirds, hinders obtaining precise data for offtake, which may threaten the conservation of species and the sustainability of wetland ecosystems.
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... Third, the indicators used to track changes in management effort may not be fully representative of the actual actions undertaken on the ground. For instance, they do not consider spatial variation in scaring and compensation levels, nor the fact that hunting bags may be liable to misreporting (Christensen, Madsen, Asferg, Hounisen, & Haugaard, 2017). However, such information is rarely recorded consistently and in a manner that would enable more widespread analysis of management time series (Tombre et al., 2013). ...
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The management of conflicts between wildlife conservation and agricultural practices often involves the implementation of strategies aimed at reducing the cost of wildlife impacts on crops. Vital to the success of these strategies is the perception that changes in management efforts are synchronised relative to changes in impact levels, yet this expectation is never evaluated. We assess the level of synchrony between time series of population counts and management effort in the context of conflicts between agriculture and five populations of large grazing birds in northern Europe. We reveal inconsistent patterns of synchrony and asynchrony between changes in population counts and impact management effort relating to population harvesting, monetary payments or scaring practices. This variation is likely due to differing management aims, the existence of lags between management decisions and population monitoring, and the inconsistent use of predictive models across case studies. Overall, our findings highlight the need for more adaptive and timely responses of management to changes in target species numbers so as not to unexpectedly increase social conflicts and jeopardise the status of wildlife populations.
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Migration tracking assists harvest management of overabundant Canada geese in Manitoba, Canada
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Similar to other jurisdictions across North America, populations of temperate‐nesting giant Canada geese ( Branta canadensis maxima ) have increased to unprecedented levels in Manitoba, Canada, causing extensive damage to crops and property, posing risks to human safety, and mostly avoiding mortality risk from fall hunting seasons. As a result, this population in southern Manitoba was declared overabundant in 2019, through an amendment to the Canada Migratory Birds Regulations. Management authorities sought to increase harvest rates by introducing an additional hunting period in spring, or conservation season, wherein harvest could be concentrated on this population. An important consideration was the need to avoid additional harvest on non‐target populations that do not meet the criteria to be classified as overabundant, specifically, sub‐arctic nesting Canada geese ( Branta canadensis interior ) and mid‐continent cackling geese ( Branta hutchinsii hutchinsii ). To investigate differences in migration timing of populations, and ultimately determine start and closure dates for the spring conservation season, we deployed light‐level geolocators on adult females of each population between 2016 and 2018. We used Bayesian approaches to derive locations from light‐level data and generalized linear mixed models to investigate potential differences in timing of international border crossing among goose populations. Migration data confirmed that movement of these populations overlapped extensively in fall, but in spring, a narrow period existed where mainly the target population was present. Our findings provide the basis for decisions about timing of spring conservation seasons for overabundant temperate‐nesting Canada geese in Manitoba, the first season of its kind for this population in North America. Additionally, our work represents the first large‐scale use of light‐level geolocator technology for assisting with waterfowl harvest management decisions.
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Table of Contents Abstract ................................................................................................1 Introduction ..................................................................1 Design and Methods.....................................................................2 Survey Results...............................................................................3 Acknowledgements .......................................................................5 References ......................................................................5 Waterfowl harvest estimates Species, state, flyway...................................7 Special seasons...............................................................................28 Canada harvest ...........................................................................................31 Long-term trend graphs................................................................................33 Waterfowl age and sex ratios ...................................................................35 Long-term trend graphs.............................................................................47 Dove and pigeon estimates...................................................................51 Woodcock estimates................................................................................53 Snipe, coot, gallinule, and rail estimates ....................................................54 Species-specific rail estimates.............................................................60
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Hunting is important to many people because it provides food, recreation, and cultural identity, so proper management of wildlife is necessary. Wildlife agencies and researchers often rely on harvest data supplied by hunters, but interpretation of these data can be misleading when biases are not acknowledged, assessed, and corrected. We use harvest information collected by the Alaska Department of Fish and Game (ADF&G) from moose (Alces alces gigas) hunters to examine and correct 3 common biases in harvest data: heaping in responses of estimated effort (i.e., rounding), changes in report design, and nonreporting. We found that bias due to heaping was limited (2.8%). A large increase in special permits in 2004 (6.1% in 2003 and 40.1% in 2004) corresponded with increases in individuals with multiple permits (8.6% and 17.3%), which biased estimates of hunt participation calculated from permit data. Failure to correct for multiple reports per hunter also resulted in an artificial decline in success over time. Road access influenced reporting rates; rural Alaska residents without a road had the lowest reporting rate (67%) and rural with a road the greatest (82%). A statewide trend of 663 additional hunters per year calculated from raw permit data was eliminated once data were corrected for both multiple permits and nonreporting. Late reporters were also less likely to hunt (11.8%) than all reporters. Our research shows that survey data bias can significantly influence data interpretation, and wildlife managers must balance information needs, time constraints, and financial resources when determining which biases to correct. © 2015 The Wildlife Society.
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Nonresponse Bias in New Zealand Waterfowl Harvest Surveys
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Nonrespondents to a postal harvest questionnaire conducted in New Zealand in 1987 and 1988 were surveyed by telephone. I compared reported mallard (Anas platyrhynchos) harvest, hours hunted, and ducks shot per hour between those who did and those who did not respond to the postal questionnaire. Mallard harvest and hours hunted were less for nonrespondents than for respondents, but estimates of ducks shot per hour were not significantly different. Harvest estimates based solely on questionnaire respondents were about 20% higher than estimates that included information from nonrespondents. There was evidence that nonresponse bias changed between years.
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Response Errors in Canadian Waterfowl Surveys
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Survey experiments based on bag check were initiated by the Canadian Wildlife Service during 1968-69 in a few study areas in Eastern Canada to provide information on the extent of response bias in the estimates of the characteristics of the harvest from mail surveys on specific days of the season. The responses were checked in the field and queried on the questionnaire. The experiments were modified during 1969-70 to cover a larger sample and provide estimates of the hunter's kill, that of his party, and of the bias due to memory lag of the hunter. The present paper considers the effect of memory lag, response wave, and size of waterfowl harvest on the response bias and the accuracy with which the species composition of the kill was reported by the waterfowl hunter. We show that the response bias is positive and highly significant and was, on the whole, 60 percent of the mean of field records when data for both successful and unsuccessful hunters were combined; in addition it was consistently higher for the follow-ups than for the first questionnaire. However, when successful hunters alone were considered, the bias was only 16 percent of the field mean and there was no apparent increase in bias for the follow-up questionnaire. Although these studies do not provide a reliable basis for estimating response errors for the entire season in the Canadian Mail Surveys they do suggest that the estimates of kill for all hunters (successful and unsuccessful combined) may be subject to considerable positive bias; but the bias may not be serious when the reports from successful hunters alone are considered. Species composition of the kill was reported with a reasonable degree of accuracy for certain important species.
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Causes and Effects of Biases on Waterfowl Harvest Estimates
Article
  • Apr 1978
Hunters at 2 Iowa Public Hunting Areas were required to bring their waterfowl through check stations and later were mailed a questionnaire asking how many ducks and geese they bagged on these areas. The estimate of the total harvest as extrapolated was about twice the value recorded at the check station. The number of trips was overestimated by about 35 percent. For most estimates, less than 10 percent of the bias could be attributed to the tendency for unsuccessful hunters to be less likely to return the questionnaire. Most of the bias was caused by inaccurate reporting from hunters who returned the questionnaires. One source of response bias was rounding upward of the seasonal bag which increased the harvest estimate by about 5 percent. Another source, caused when some person other than the addressee returned the questionnaire, could have inflated the estimate up to 10 percent. About 75 percent of the detected bias must be attributed to other factors. Probably much is due to hunters including friends' data when reporting their seasonal bag. Some method of estimating its effects on regular surveys is needed.
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