Advances in understanding avian nesting ecology are hindered by a prevalent lack of agreement between nest‐site characteristics and fitness metrics such as nest success. We posit this is a result of inconsistent and improper timing of nest‐site vegetation measurements. Therefore, we evaluated how the timing of nest vegetation measurement influences the estimated effects of vegetation structure on nest survival. We simulated phenological changes in nest‐site vegetation growth over a typical nesting season and modeled how the timing of measuring that vegetation, relative to nest fate, creates bias in conclusions regarding its influence on nest survival. We modeled the bias associated with four methods of measuring nest‐site vegetation: Method 1—measuring at nest initiation, Method 2—measuring at nest termination regardless of fate, Method 3—measuring at nest termination for successful nests and at estimated completion for unsuccessful nests, and Method 4—measuring at nest termination regardless of fate while also accounting for initiation date. We quantified and compared bias for each method for varying simulated effects, ranked models for each method using AIC, and calculated the proportion of simulations in which each model (measurement method) was selected as the best model. Our results indicate that the risk of drawing an erroneous or spurious conclusion was present in all methods but greater with Method 2 which is the most common method reported in the literature. Methods 1 and 3 were similarly less biased. Method 4 provided no additional value as bias was similar to Method 2 for all scenarios. While Method 1 is seldom practical to collect in the field, Method 3 is logistically practical and minimizes inherent bias. Implementation of Method 3 will facilitate estimating the effect of nest‐site vegetation on survival, in the least biased way, and allow reliable conclusions to be drawn.

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Abstract:The USDA Farm Bill conservation programs provide landowner incentives to remove less productive and environmentally sensitive lands from agricultural production and reestablish them in natural vegetation (e.g., native grasses, trees, etc.) to achieve conservation objectives. However, removal of arable land from production imposes an opportunity cost associated with loss in revenue from commodities that otherwise would have been produced. Recent Farm Bills have increasingly emphasized targeted practices to achieve specific environmental outcomes that maximize environmental benefits relative to cost. The Habitat Buffers for Upland Birds practice (CP-33) under the continuous Conservation Reserve Program is an example of a targeted conservation practice that has produced measureable outcomes (increased bobwhite and grassland bird populations) with relatively minor changes in primary land use. However, establishing conservation buffers on profitable farmland may be incompatible with the economic objectives of landowners/producers. Precision agriculture technologies provide a powerful conservation planning tool for identifying environmental and economic opportunities in agricultural systems. Precision implementation of conservation practices, such as CP-33, is the foundation of strategic conservation planning and is essential for optimization of environmental and economic benefits. Toward this end, we developed a geospatial decision support tool (Arc GIS tool) to inform this decision-making process. We illustrate the geoprocessing workflow of the tool and demonstrate the conditions under which precision implementation of conservation practices can concomitantly increase whole-field profitability and environmental services for an example farm in Mississippi.

Agriculture is the world's largest industry, continues to dominate human land use, and will become more intensive to meet global food demands associated with population growth. Sustainability of global agricultural systems will require strategic integration of conservation practices to protect ecosystems services, health, and productivity. Natural communities as a component of agricultural landscapes support wildlife populations that provide essential ecosystem services with broad societal value. However, allocation of land to noncrop uses entails economic opportunity costs to producers. Effective conservation delivery is dependent on being able to quantify and visualize both the expected costs and benefits. We argue that by identifying economic opportunities for conservation enrollment, increased adoption by landowners is achievable. Our primary goal was to illustrate the necessity, technology, and application of precision conservation in a wildlife management framework. The tools, technologies, and processes associated with precision agriculture can be adapted to inform conservation practice adoption when wildlife objectives are explicitly incorporated into farm-and landscape-level decision framework. We illustrate strategic, objective-driven conservation planning and delivery with case studies from an intensive agricultural landscape in the Lower Mississippi Alluvial Valley. A griculture is the world's largest industry and continues to dominate human land use (Robertson and Swinton, 2005). With the human population expected to reach 9.4 billion and per capita arable land expected to be reduced by nearly 40% by 2050 (Lal, 2000), intensification of agricultural production is expected. The mechanism of increase will involve either allocation of additional land to production or maximization of the potential (i.e., increase yield) of land already in use. Considering most of the world's arable land is already in agricultural production (Baligar et al., 2001), future production demands will likely come from land currently in use. Precision agriculture provides a method for implementing the latter

Agricultural production, including croplands, pasture, and timber, dominates private-land use and land cover across much of the contiguous lower 48 states. These private lands are essential to achieving the goals of national conservation initiatives such as the Northern Bobwhite Conservation Initiative (bobwhite [Colinus virginianus]), Sage Grouse Initiative, and North American Waterfowl Management Plan. Effective conservation delivery in managed landscapes requires 1) an understanding of landowner priorities and ownership objectives, 2) knowledge of the economic and environmental costs and benefits of conservation, and 3) natural resource professionals who understand the business of agriculture and forestry as well as principles of habitat management and wildlife conservation. We make the case for a new vision of multifunctional working landscapes that include designed components of natural and seminatural noncrop perennial plant communities (wetlands, grasslands, riparian areas, field margins, pine [Pinus spp.] grasslands, savannas, etc.) embedded in a matrix of row-crop, pasture, rangeland, and forested working lands that produce sustainable food, fiber, and fuel. Producing sustainable, multifunctional landscapes will require effective conservation delivery that is intentional, objective-driven, targeted, science-based, and landscape scale. We contend that it will also require a new kind of natural resource professional. We consider the specific and novel skill sets that will be required among natural resource professionals to deliver conservation to private owners-producers of working lands.

Agricultural landscapes are important for natural resource conservation, but present numerous obstacles associated with intensive agricultural production. Chief among these challenges is the competing economics outcomes of conservation and crop production. Understanding these outcomes requires quantifying economics of crop production and conservation enrollment. Precision agriculture technology provides a mechanism to address these needs by using advanced technology to quantify spatially explicit profitability in agricultural fields. Precision agriculture's application to conservation planning represents a growing field of research. I present a brief overview of precision agriculture technology and its application in natural resource conservation. I discuss the role precision agriculture can play in United States conservation policy, highlight hindrances to adopting this technology, and provide recommendations for future application. I outline a new approach of targeted conservation delivery that focuses on return on investment to agricultural producers and discuss the role of precision agriculture in this approach. Increased adoption and application of this technology in natural resource conservation will require substantial investment from state wildlife agencies, nongovernmental organizations, farm managers, rural banks, and agricultural companies. Precision agriculture represents the next paradigm shift in natural resource conservation where spatially explicit conservation decisions are made that optimize conservation and profitability to produce environmentally resilient, multifunctional agricultural landscapes.

Our study explored the utility of using Importance‐Satisfaction Analysis (ISA) to identify critical attributes to deer management cooperative (DMC) member satisfaction. With white‐tailed deer (Odocoileus virginanus) management by landowners becoming an increasingly popular conservation tool, DMCs represent an approach by private landowners and hunters to collaboratively improve deer herds and hunting quality. Deer management cooperatives are a group of landowners and hunters voluntarily working together to improve the quality of wildlife, habitat, and hunting experiences on their collective acreage. Deer management cooperatives show promise in providing dual benefits to hunter satisfaction and large‐scale conservation efforts such as increasing habitat connectivity. Heterogeneity of satisfaction for deer hunting is well‐documented and DMC member satisfaction is an important factor in member retention and recruitment. We surveyed 2,817 members of 45 DMCs across five states (Georgia, Michigan, Missouri, New York, and Texas) using ISA methodology to better understand their satisfaction with their experience. Hunters’ responses (n = 459) to the 22 attributes measured were segmented by their divergent motivations for DMC membership, resulting in four unique clusters for comparison (Solitude Members, Social Members, Representative Members, and Quality Harvest Members). Our results indicated that motivations for membership influenced importance and satisfaction ratings, further elucidating that multiple types of hunters and members exist within DMC networks. Areas of agreement among the four DMC clusters were the need for Neighbors to follow Quality Deer Management practices, that DMCs are performing well on members Seeing deer and Co‐op members sharing similar harvest goals, and that Preventing crop damage and the Lease value of the DMC property are low priorities. However, there was little agreement in quadrant placement among the four membership clusters for the remaining 17 attributes indicating the importance of DMCs understanding their individual members’ motivations for joining. By retaining satisfied members, DMCs can continue to provide the hunting quality expected as well as the tangential conservation benefits. © 2021 The Wildlife Society.

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