A Case for Standardized Ungulate Surveys and Data Management in the Western United States

Mason, R. M.; Carpenter, Len H.; Cox, Michael; Devos, James C.; Fairchild, John A.; Freddy, David J.; Heffelfinger, Jim; Kahn, Richard H.; McCorquodale, Scott M.; Pac, David F.; Summers, D.A.; White, Gary C.; Williams, Byron K.

doi:10.2193/0091-7648(2006)34[1238:acfsus]2.0.co;2

Cited by 13 publications

(13 citation statements)

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“…When there is a high density of low‐use roads on winter range, this can be a rational reason for using road surveys, but there was another less defensible reason for the use of road surveys—“we've always done it that way.” As pointed out by American inventor, Charles F. Kettering (Boyd 1957:page 206) “If you've always done it that way, it is probably wrong.” Our results from the mild winters strongly support conclusions of Koenen et al (2002) that it is critical to incorporate knowledge of mule deer range under different winter conditions and their behavior into survey design. Studies concerned with estimating abundance or density of deer and elk stress good survey design is crucial for obtaining reliable results (Bowden et al 2000, Mason et al 2010, Thomas et al 2010) and that convenience sampling from roads or the like can result in biases that are not correctable (Samuel et al 1992, Anderson 2001, Roberts et al 2006, Collier et al 2007, Weaver and Weckerly 2011). This conclusion applies to composition surveys as well, as shown by our results (Berger and Gompper 1999, White et al 2001).…”

Section: Discussionmentioning

confidence: 99%

“…Our results from the mild winters strongly support conclusions of Koenen et al (2002) that it is critical to incorporate knowledge of mule deer range under different winter conditions and their behavior into survey design. Studies concerned with estimating abundance or density of deer and elk stress good survey design is crucial for obtaining reliable results (Bowden et al 2000, Mason et al 2010, Thomas et al 2010) and that convenience sampling from roads or the like can result in biases that are not correctable (Samuel et al 1992, Anderson 2001, Roberts et al 2006, Collier et al 2007, Weaver and Weckerly 2011. This conclusion applies to composition surveys as well, as shown by our results (Berger andGompper 1999, White et al 2001).…”

Section: Discussionmentioning

confidence: 99%

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Are Composition Surveys for Mule Deer Along Roads or From Helicopters Biased? Lessons from the Field

Conner

McKeever

2020

Wildl. Soc. Bull.

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Monitoring sex and age ratios (i.e., population composition) is common practice in deer (Odocoileus spp.) management because these estimates are used to determine population vital rates, as well as assess effects of hunting regulations and other management actions. However, there is longstanding recognition of potential biases in sex and age ratios that can arise from differences in deer behavior and sightability, or from methodological issues, such as using roads for sampling. Biologists often use roads for composition surveys because of convenience and roads are often considered to provide coverage of the sampling area and, consequently, unbiased estimates of sex and age ratios. We tested the long‐standing belief that low‐use roads through mule deer (O. hemionus) winter range provided an unbiased sampling scheme by designing and conducting a random‐route survey in conjunction with the road survey through the same winter range in Round Valley, California, USA, during 2015 and 2016. In addition, we conducted a helicopter survey of the same area in 2016. We found adult male:adult female (buck:doe) ratios were 31–45% greater from the random‐route survey compared with the road survey. There was no difference in buck:doe ratios between road and helicopter surveys, but the random‐route survey had 55% greater buck:doe ratios than the helicopter survey. The helicopter survey also had 2.2–4.7 times greater proportions of unclassified bucks than the road or random‐route surveys. There were no differences in fawn:doe ratios among the 3 survey methods. We conducted additional spatial analyses to determine if the buck:doe ratio was greater along random‐routes because bucks were avoiding roads or because the random‐route survey covered different areas. We found that bucks were not avoiding roads; rather, the roads did not adequately cover the winter range area. There were differences between all 3 methods, but our main message is that the assumption that roads provide adequate coverage of winter range and unbiased estimates of population composition should be evaluated. To evaluate that assumption, we recommend conducting ≥1 survey using random routes and comparing composition estimates with road surveys. Further, if information on buck antler‐class is required for management decisions, a ground survey is preferable to a helicopter survey. © 2020 The Wildlife Society.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Are Composition Surveys for Mule Deer Along Roads or From Helicopters Biased? Lessons from the Field

Conner

McKeever

2020

Wildl. Soc. Bull.

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“…The aim of this collaboration is to improve ecological and conservation outcomes of management decisions (Knutson et al , Moore et al ). Such “distributed decision‐making,” in which coordinated monitoring and decision‐making responsibilities are shared among many cooperators, often involves collecting, analyzing, and storing monitoring data from the study system (Mason et al , Moore et al ). Cooperators participating in such programs need practical solutions for maintaining long‐term data sets (Ballard et al ) and obtaining timely decision support (Marzluff et al ).…”

Section: Data Management Challengesmentioning

confidence: 99%

A data management system for long‐term natural resource monitoring and management projects with multiple cooperators

Hunt

Jacobi²,

Knutson

et al. 2015

Wildl. Soc. Bull.

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Collection, processing, and long-term storage of data for broad-scale, collaborative natural resource monitoring and management projects poses technical and administrative challenges that, if not properly addressed, result in suboptimal management and learning. Data from many cooperators, often spanning multiple organizations, must be efficiently centralized and processed, and must be consistent in content and quality over the lifespan of such projects. We present a data management system for natural resource monitoring and management consisting of 2 components: a centralized, web-based platform for data entry and a connected relational database for data processing, modeling, and analysis. After the data management system has been customized to meet the needs of a specific project, operation and system maintenance require minimal external technical support, making it suitable for long-term projects that face potential staffing and budgeting constraints. We discuss the scope of projects for which this approach is applicable and document 2 U.S. Fish and Wildlife Service adaptive management case studies demonstrating this data management system: 1) Native Prairie Adaptive Management, and 2) Wetland Restoration and Sediment Removal. The standardized approach presented within is broadly applicable in collaborative natural resource monitoring and management settings and has the potential to improve management outcomes and facilitate deeper ecological understanding of systems being managed.

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“…These DAUs were established with the objective of estimating population parameters of interest for distinct Figure 1. Historical (1987-2006 estimates of Colorado's mule deer population based on pooled model estimates from all data analysis units (DAUs). A region wide decline in mule deer populations was observed from the late 1980s through the early 1990s.…”

Section: Study Areamentioning

confidence: 99%

“…This sequence of events is a fundamental tenet of adaptively managed systems (Williams et al 2002). However, few wildlife management plans have been formally designed, or structured, as adaptive management programs (Montana Fish, Wildlife and Parks 2001, Mason et al 2006, Nichols et al 2007. Despite this, managers are often challenged to retroactively assess the effects of decisions on a managed system.…”

mentioning

confidence: 99%

Biological and socio‐economic effects of statewide limitation of deer licenses in Colorado

et al. 2011

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We evaluated the biological and socio‐economic effects of statewide limitation of mule deer (Odocoileus hemionus) hunting licenses, which began in Colorado in 1999. We implemented a before‐after‐control‐impact (BACI) analysis of annual helicopter sex and age class surveys, collected as part of the Colorado Division of Wildlife's routine monitoring, to assess changes in adult male/adult female ratios and fawn/adult female ratios in response to this change in harvest management. Following statewide limitation and reduction of license sales (1999–2006), we observed increases in adult male/adult female ratios of 7.39 (SE = 2.36) to 15.23 (SE = 1.22) adult males per 100 adult females in moderately limited areas and of 17.55 (SE = 3.27) to 21.86 (SE = 2.31) adult males per 100 adult females in highly limited areas. We simultaneously observed reductions in fawn/adult female ratios in newly limited areas by as much as 6.96 (SE = 2.19) fawns per 100 females, whereas in areas that had previously been limited we observed stabilization of fawn/adult female ratios at levels lower than levels observed under the unlimited harvest management structure. An immediate decline of $7.86 million in annual revenue stemmed from the change in harvest management, but revenue subsequently rebounded. This study provides preliminary evidence of potential effects that other state and provincial wildlife management agencies may face as they consider shifting mule deer harvest management towards limited license scenarios. © 2011 The Wildlife Society.

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A Case for Standardized Ungulate Surveys and Data Management in the Western United States

Cited by 13 publications

References 13 publications

Are Composition Surveys for Mule Deer Along Roads or From Helicopters Biased? Lessons from the Field

Are Composition Surveys for Mule Deer Along Roads or From Helicopters Biased? Lessons from the Field

A data management system for long‐term natural resource monitoring and management projects with multiple cooperators

Biological and socio‐economic effects of statewide limitation of deer licenses in Colorado

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