Assessing Multiregion Avian Benefits from Strategically ... · Strategically Targeted Agricultural Buffers ... (10 ecoregiones) ... Assessing Multiregion Avian Benefits from Strategically

Conservation Practice and Policy

Assessing Multiregion Avian Benefits fromStrategically Targeted Agricultural Buffers

KRISTINE O. EVANS, * L. WES BURGER JR., SAM RIFFELL, AND MARK D. SMITH†

Department of Wildlife, Fisheries, and Aquaculture, Mississippi State University, Box 9690, Mississippi State, MS 39762, U.S.A.,email [email protected]

Abstract: Mounting evidence of wildlife population gains from targeted conservation practices has promptedthe need to develop and evaluate practices that are integrated into production agriculture systems andtargeted toward specific habitat objectives. However, effectiveness of targeted conservation actions acrossbroader landscapes is poorly understood. We evaluated multiregion, multispecies avian densities on row-crop fields with native grass field margins (i.e., buffers) as part of the first U.S. agricultural conservationpractice designed to support habitat and population recovery objectives of a national wildlife conservationinitiative. We coordinated breeding season point transect surveys for 6 grassland bird species on 1151 row-crop fields with and without native grass buffers (9–37 m) in 14 U.S. states (10 ecoregions) from 2006 to2011. In most regions, breeding season densities of 5 of 6 targeted bird species were greater in the 500-msurrounding survey points centered on fields with native grass buffers than in landscapes without buffers.Relative effect sizes were greatest for Northern Bobwhite (Colinus virginianus), Dickcissel (Spiza americana),and Field Sparrow (Spizella pusilla) in the Mississippi Alluvial Valley and Eastern Tallgrass Prairie regions.Other species (e.g., Eastern Meadowlark [Sturnella magna], Grasshopper Sparrow [Ammodramus savannarum])exhibited inconsistent relative effect sizes. Bird densities on fields with and without buffers were greatestin the Central Mixed-grass Prairie region. Our results suggest that strategic use of conservation buffers inregions with the greatest potential for relative density increases in target species will elicit greater range-wide population response than diffuse, uninformed, and broadly distributed implementation of buffers.We recommend integrating multiple conservation practices in broader agricultural landscapes to maximizeconservation effectiveness for a larger suite of species.

Keywords: agricultural conservation, conservation buffers, grassland birds, monitoring, Northern Bobwhite,targeted conservation

Evaluacion de los Beneficios de la Mutliregionalidad de Aves a Partir de Amortiguadores Agriculturales Es-trategicamente Senalados

Resumen: La creciente evidencia de aumentos en la poblacion de vida silvestre, obtenida de practicas deconservacion objetivo, ha provocado la necesidad de desarrollar y evaluar a las practicas que se integran ala produccion de los sistemas agrıcolas y se han enfocado en objetivos especıficos de habitat. Sin embargo, laefectividad de las acciones de la conservacion a traves de terrenos mas amplios es poco entendida. Evaluamosla densidad multiregion y multiespecie de aves en campos de cultivos en hilera con margenes de pastizalnativo (es decir, amortiguadores) como parte de la primera practica de conservacion agrıcola en los EUA,disenada para apoyar a los objetivos de recuperacion de habitat y de poblacion de una iniciativa nacional deconservacion de vida silvestre. Coordinamos censos de transecto de punto en temporada de reproduccion para6 especies de aves de pastizal en 1151 campos de cultivos en hilera con y sin amortiguadores de pastizal nativo(9-37 m), en 14 estados de los EUA (10 ecoregiones) desde 2006 hasta 2011. En la mayorıa de las regiones,las densidades de temporada de reproduccion de 5 de las 6 especies objetivo fueron mayores en los 500 malrededor de los puntos de muestreo centrados en los campos con amortiguadores de pastizal nativo que en

*Current address: Box 9627 Mississippi State MS 39762 U.S.A.†Current address: School of Forestry and Wildlife Sciences, 3301 Forestry and Wildlife Building, Auburn University, AL 36849-5418 U.S.A.Paper submitted March 13, 2013; revised manuscript accepted January 30, 2014.

1Conservation Biology, Volume 00, No. 0, 1–10C© 2014 Society for Conservation BiologyDOI: 10.1111/cobi.12311

2 Targeted Agricultural Buffers for Birds

los terrenos sin amortiguadores. Los tamanos de efecto relativo fueron mayores para Colinus virginianus,Spiza americana y Spizella pusilla en las regiones del Valle Aluvial del Mississippi y la Pradera Orientalde Hierbas Altas. Otras especies (p. ej.: Sturnella magna y Ammodramus savannarum) exhibieron tamanosde efecto relativo irregulares. Las densidades de aves en campos con y sin amortiguadores fueron mayoresen la region de la Pradera Central de Hierbas Mixtas. Nuestros resultados sugieren que el uso estrategico deamortiguadores de conservacion en regiones con el mayor potencial para incrementos en la densidad relativaen especies objetivo provocara una mayor respuesta de poblacion de rango extenso que la implementacion deamortiguadores difusa, mal informada y distribuida en general. Recomendamos integrar multiples practicasde conservacion en terrenos agrıcolas mas amplios para maximizar la efectividad de la conservacion paraun conjunto mayor de especies.

Palabras Clave: amortiguadores de conservacion, aves de pastizal, Colinus virginianus, conservacion agrıcola,conservacion objetivo, monitoreo

Introduction

Limited evidence of large-scale ecological successes fromconservation actions (Hoffmann et al. 2010) suggests dif-fuse application of conservation practices with genericanticipated ecological benefits is no longer acceptablein the conservation community. Deliberate and itera-tive conservation management decisions, applied strate-gically and efficiently within the landscape to allowmaximum environmental benefits, are the prevailing con-servation paradigm (Hoffmann et al. 2010). In the UnitedStates and Europe, government-subsidized agriculturalconservation programs provide financial incentives forproducers to voluntarily alter crop production to fos-ter multiple environmental services (Sullivan et al. 2004;Lovell & Sullivan 2006). Since 2004, U.S. policy makersestablished new practices that incentivize agriculturalconservation with approaches that target objectives ofnational conservation initiatives. These practices weredesigned to achieve specific environmental outcomes atlandscape scales that are linked to regional and nationalconservation priorities (e.g., Burger et al. 2006a). How-ever, major conservation programs applied at large spa-tial extents must be designed to evaluate programmaticoutcomes effectively (Sutherland et al. 2004; Whitfield2006). Conservation programs should be evaluated atmultiple spatial scales (e.g., field, farm, landscape, and re-gion) to appropriately capture differences in environmen-tal outcomes due to regionally variable land forms, landuses, and conservation practice and to refine targetedconservation actions at appropriate scales (Whittinghamet al. 2007).

We evaluated multiregion programmatic outcomes(i.e., population density) from a spatially extensiveconservation practice (habitat buffers for upland birds[CP33]) established in the United States under theConservation Reserve Program (U.S. Department ofAgriculture 2004). The practice provides landownerincentives to establish linear patches (i.e., buffers) ofnative warm-season grasses around field margins target-ing population recovery goals of a conservation partner-

ship titled the National Bobwhite Conservation Initiative(NBCI) (Dimmick et al. 2002; National Bobwhite Techni-cal Committee 2011). In the United States, populationsof Northern Bobwhite (Colinus virginianus), an iconicgame bird and flagship species for grassland bird con-servation, have declined 75% in the past 40 years (Saueret al. 2011). The CP33 practice was designed deliberatelyunder the ecological premise that incremental changesin land cover from row-crop agriculture to natural nativegrasses will elicit disproportionate population responsesby Northern Bobwhite and other priority grassland birdspecies. Buffers were typically planted to a mix contain-ing native warm season grasses (including big bluestem[Andropogon gerardii], little bluestem [Schizachyriumscoparium], Indiangrass [Sorghastrum nutans], switch-grass [Panicum virgatum], and regionally appropriateseed producing forbs such as partridge pea [Chamae-crista fasciculata], blackeyed susan [Rudbeckia hirta],coneflower [Echinacea spp.], bundleflower [Desman-thus spp.], and prairie clover [Dalea spp.]) or naturallyregenerated to native grasses and forbs from existing seedbanks.

We worked with a coalition of 24 state and federalagencies, nongovernmental organizations, and universi-ties in 14 states to develop and implement a 6-yearregional monitoring program to compare densities oftargeted bird species (Northern Bobwhite and selectgrassland songbirds) in 500-m radial landscapes aroundbird survey points on a random sample of row-crop fieldswhere CP33 native grass buffers were established ver-sus fields without these buffers. We hypothesized thatdensities of several grassland bird species are greater inlandscapes where native grass buffers are establishedalong row-crop field margins than in landscapes withnonbuffered fields and that the observed relative effectsize is sustained over time. Furthermore, we presumedobserved relative effect sizes for target species vary withdifferent landscape processes and life-history require-ments in different regions. Evidence of regional variationin programmatic outcomes should suggest conservationprojects targeted under national conservation initiatives

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may be more successful if management were tailored toaccount for regional differences in land form, land use,and habitat selection (Whittingham et al. 2007; Daveyet al. 2010a).

Methods

The U.S. Department of Agriculture Farm Service Agency(FSA) mandated the CP33 practice be evaluated to mea-sure effects of habitat buffer establishment on NorthernBobwhite and priority grassland bird densities acrossthe Northern Bobwhite range (U.S. Department ofAgriculture 2004). The coordinated national CP33 moni-toring program was established in 14 states; these statescontained 80% of established CP33 acreage in 2006(Fig. 1) (Burger et al. 2006b). Prior to implementing mon-itoring, FSA personnel selected randomly 40 landownercontracts for CP33 enrollment from all enrolled CP33contracts available in each state as of 31 December2005. We then selected randomly 1–3 buffered fields perlandowner contract and established survey points alongthe exterior edge and linear midpoint of each selectedbuffered field. We established survey points on more thanone field in a contract if the distribution of fields allowedfor no overlap of a 500-m radius around survey points(Burger et al. 2006b). We located corresponding refer-ence points on nonbuffered row-crop fields (1–3 km fromeach buffered field) sharing similar landscape featuresand cropping regimes to control for potential variationin agricultural landscapes that may obscure comparativemodels (Burger et al. 2006b).

Because evaluation and conservation of bird communi-ties beyond local scales is a key goal of bird conservationinitiatives (e.g., North American Bird Conservation Initia-tive Monitoring Subcommittee 2007; National BobwhiteTechnical Committee 2011), our objective included un-derstanding regional variation in density and relative ef-fect size for targeted species. Bird conservation regions(BCRs) are ecologically defined regions in North and Cen-tral America with similar vegetation structure and landuse that support similar bird communities (North Ameri-can Bird Conservation Initiative 2000). Though 10 BCRswere included in the study area, a preliminary analysisfor each species revealed imprecise (>40% coefficient ofvariation [CV]) density estimates in 5 regions. Survey sitesin only 5 BCRs (Central Mixed-grass Prairie [BCR 19], East-ern Tallgrass Prairie [BCR 22], Central Hardwoods [BCR24], Mississippi Alluvial Valley [BCR 26], and Southeast-ern Coastal Plain [BCR 27]) produced adequate samplesizes to be evaluated independently for each targetedspecies (Fig. 1). However, points from all 10 BCRs wereincluded in overall evaluation for each species.

We conducted breeding season point transect bird sur-veys 1–4 times annually at each survey point from 2006 to

2011 (May–July). We surveyed points on paired bufferedand nonbuffered fields simultaneously to ensure similarweather conditions. We conducted surveys on 904 fields(458 buffered, 446 nonbuffered) in 11 states in 2006 and1151 fields (581 buffered, 570 nonbuffered), 1124 fields(564 buffered, 560 nonbuffered), and 1146 fields (572buffered, 574 nonbuffered) in 14 states in 2007, 2008,and 2009, respectively. Variation in sample size acrossyears and the unbalanced design (i.e., among-year dif-ferences in number of buffered and nonbuffered fields)resulted from field accessibility issues at some sites, lackof availability of nonbuffered fields in some landscapes,or enrollment of nonbuffered fields into CP33 during thestudy period.

We recorded singing and whistling and observed maleNorthern Bobwhite and selected priority grassland birdspecies from sunrise to 3 h following sunrise during 10-min counts at 1 of 6 predetermined radial distance in-tervals (0–25, 26–50, 51–100, 101–250, 251–500, >500m) centered on survey points. We recorded date, time,observer, and weather conditions following each survey(Marques et al. 2007). Priority grassland birds were se-lected to be surveyed for each BCR by identifying speciesmost likely affected by agricultural conservation pro-grams, particularly native grass field buffers; species thatwere declining in abundance (as per the North AmericanBreeding Bird Survey [Sauer et al. 2011]); species withdistributions that overlapped CP33 states; and speciesabundant enough to analyze statistically (or of regionalinterest) (Burger et al. 2006b). In addition to NorthernBobwhite, priority species that met these criteria in-cluded Eastern Kingbird (Tyrranus tyrannus), EasternMeadowlark (Sturnella magna), Dickcissel (Spiza amer-icana), Field Sparrow (Spizella pusilla), and Grasshop-per Sparrow (Ammodramus savannarum).

We analyzed regional and overall bird data with con-ventional and multiple covariate distance sampling (con-ventional [CDS]; multiple covariate [MCDS]) for eachspecies in program Distance (version 6.0, release 2)(Thomas et al. 2010). We right-truncated data where thedetection probability g(w) <0.1. With the CDS analyses,we evaluated the fit of 3 key function models (uniform,half-normal, and hazard rate) and followed that with 3series expansion adjustments (cosine, simple polynomial,and hermite polynomial) (Buckland 1992). With MCDS,we evaluated half-normal and hazard rate key functionswith cosine and hermite polynomial adjustments.

We evaluated differences in detection probabilitiesin radial landscapes centered on buffered versus non-buffered fields to the truncation distance by com-paring stratified detection functions (by habitat typeover all years, and by habitat type-within year) with apooled detection function (assuming equal detectabil-ity across buffered and nonbuffered strata for all years)with Akaike’s information criterion (AIC) (Akaike 1973),



Figure 1. Location of survey points and bird conservation regions (BCRs) for 2006–2011 breeding seasonmonitoring of paired row-crop fields containing native grass buffers and fields without buffers in 14 U.S. states(BCRs: 11, Prairie Potholes; 19, Central Mixed Grass Prairie; 21, Oaks and Prairies; 22, Eastern Tallgrass Prairie;23, Prairie-Hardwood Transition; 24, Central Hardwoods; 25, Western Gulf Coast Plain; 26, Mississippi AlluvialValley; 27, Southeastern Coastal Plain; 29, Piedmont).

goodness-of-fit tests, and probability density functionplots generated for each model (Table 1) (Bucklandet al. 2001; Marques & Buckland 2003; Pacifici et al.2008). We assessed yearly variation in detection prob-ability to account for successional changes in vegeta-tive structure of buffers and annual changes in croppingregimes and land use in landscapes surrounding surveypoints. We calculated stratum-specific density (males perhectare) by incorporating species-specific estimates ofdetection probability at regional and overall scales (Buck-land et al. 2001). We calculated density estimates foreach species in landscapes centered on fields with andwithout buffers by year to account for potential variationin density due to natural population fluctuation and re-sponse to changes in habitat condition due to successionin buffers, cropping regimes, and land use. We calculatedsimple effect sizes by subtracting the nonbuffered frombuffered density estimates and relative effect sizes by di-viding simple effect sizes by the nonbuffered densities.We calculated 95% confidence intervals for effect size;those that included zero were not significant (Gardner &Altman 1989; Sim & Reid 1999).

Results

Detection functions (including levels of stratification andinfluential covariates) for each species varied region-ally (Supporting Information). Breeding season North-ern Bobwhite densities were 85–109% (0.066–0.117males/ha) greater in radial landscapes centered onbuffered row-crop fields versus landscapes centered onnonbuffered fields across the 14 states 1–6 years follow-ing establishment of buffers (2006–2009) (Fig. 2, Sup-porting Information). Dickcissel densities were 85–120%(0.211–0.600 males/ha) and Field Sparrow densities were58–106% (0.147–0.189 males/ha) greater in landscapescentered on buffered fields across years. Eastern Mead-owlark response varied annually; densities were 4–22%(0.003–0.022 males/ha) greater in landscapes centeredon nonbuffered fields than in landscapes centered onbuffered fields in 4 of 6 years. Grasshopper Sparrowdensities were 6–95% (0.006–0.056 males/ha) greaterin landscapes centered on buffered fields than on land-scapes centered on nonbuffered fields from 2007 to 2011.Eastern Kingbird densities were 11–18% (0.014–0.029


Evans et al. 5

Table 1. Percent composition of land cover types at 500 m (upper value for each bird conservation region [BCR]) and 1500 m (lower value for eachBCR) landscapes in each BCR centered on bird survey points located in row-crop fields containing native grass buffers versus nonbuffered row-cropfields.

Type BCR∗ CP33 Row crop Pasture Woody Developed Rangeland

Buffered CH 5.66 50.78 8.74 26.20 3.77 0.001.67 46.27 14.81 27.76 4.33 0.00

CMP 6.71 62.62 3.74 4.75 3.79 14.262.04 61.42 5.06 5.19 3.13 18.99

ETP 4.45 58.01 8.72 18.89 5.35 0.000.99 59.49 10.88 17.09 6.42 0.00

MAV 5.97 68.05 2.49 14.31 3.22 0.001.43 66.86 4.08 17.47 3.11 0.00

SCP 5.73 34.47 6.38 40.97 5.15 0.001.61 30.03 8.68 46.99 5.54 0.00

Nonbuffered CH 0.45 61.36 10.04 19.06 4.21 0.000.77 49.12 12.80 27.62 4.43 0.00

CMP 0.52 66.82 4.48 3.18 5.08 15.600.72 61.85 7.06 4.67 3.71 17.50

ETP 0.29 71.62 6.70 10.95 6.08 0.000.34 65.73 9.17 13.83 6.03 0.00

MAV 0.78 70.85 5.30 15.33 3.44 0.000.88 68.67 4.57 16.89 3.44 0.00

SCP 0.11 49.16 6.41 32.63 5.35 0.000.44 35.40 8.81 42.98 5.16 0.00

∗Abbreviations: CH, Central Hardwoods (BCR 24); CMP, Central Mixed-grass Prairie (BCR 19); ETP, Eastern Tallgrass Prairie (BCR 22); MAV,Mississippi Alluvial Valley (BCR 26); SCP, Southeastern Coastal Plain (BCR 27).

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Figure 2. Breeding seasonrelative effect size([densitybuffered −densitynonbuffered]/densitynonbuffered), and 95%CI, of targeted upland birddensities on pairedrow-crop fields containingnative grass buffers andfields without buffers(2006–2011) across 14 U.S.states.

males/ha) greater on landscapes centered on nonbufferedfields than on landscapes centered on buffered fieldsacross years.

Region-specific Northern Bobwhite densities weregreatest (up to 0.663 males/ha across years) in the Cen-tral Mixed Grass Prairie (BCR 19), an area that con-tained the westernmost survey points and most abundantU.S. Northern Bobwhite populations (Fig. 3a; Support-ing Information). However, observed relative effect size

suggested that native grasses may not limit populationsor that ample alternative habitat is available in this re-gion (Table 1). Densities were lowest (as low as 0.011males/ha) in the Mississippi Alluvial Valley region (BCR26; Supporting Information). Survey points in this areawere along the Mississippi River alluvial floodplain. How-ever, observed relative effect sizes were greater here thanfor all other regions (281–873% greater density in land-scapes centered on buffered fields than on landscapes



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Figure 3. Regional breeding season (a) Northern Bobwhite, (b) Dickcissel, (c) Field Sparrow, (d) EasternMeadowlark, (e) Grasshopper Sparrow, and (f) Eastern Kingbird relative effect size ([densitybuffered −densitynonbuffered]/densitynonbuffered), and 95% CI, on surveyed fields with native grass buffers and fields withoutbuffers from 2006 to 2011.


Evans et al. 7

centered nonbuffered fields across years) (Fig. 3a). Rela-tive effect sizes were also large (133–320% greater in land-scapes centered on buffered fields than in those centeredon nonbuffered fields) in the Eastern Tallgrass Prairieregion (BCR 22) across years (Supporting Information).Northern Bobwhites in the Central Hardwoods (BCR 24)and Southeastern Coastal Plain (BCR 27) also exhibitedgreater densities in landscapes centered on fields withbuffers than on fields without them, although densitieswere less than those observed in other regions (Fig. 3a;Supporting Information).

Regional Dickcissel densities and relative effect sizeswere greatest in landscapes centered on buffered fieldsin the Mississippi Alluvial Valley and least in bufferedfields in the Southeastern Coastal Plain (Fig. 3b, Support-ing Information). Field Sparrow densities in landscapescentered on buffered fields were consistent across re-gions, but relative effect sizes were greatest in the EasternTallgrass Prairie region across years (Fig. 3c, Support-ing Information). Similar to Northern Bobwhite, EasternMeadowlark densities were greatest in the Central Mixed-grass Prairie, but they exhibited negative or minimal rel-ative effect sizes in this region relative to other regions(Fig. 3d; Supporting Information). Relative effect sizesvaried across years in all regions. Grasshopper Sparrowdensities were <0.1 male/ha in most regions, except inCentral Mixed-grass Prairie. Relative effect sizes werenegligible in most regions, but they were positive (8–180% greater densities in landscapes centered on fieldswith buffers than on nonbuffered fields) in the CentralHardwoods (Fig. 3e, Supporting Information). EasternKingbird also exhibited substantial annual and regionalvariability; its greatest densities and largest relative effectsizes were observed in the Central Mixed-grass Prairie(Fig. 3f, Supporting Information).

Discussion

Native grass field buffers in our study comprised <7% ofthe 500 m and <2% of the 1500 m radial landscape aroundsurvey points (Table 1; Evans 2012). Three species(Northern Bobwhite, Dickcissel, and Field Sparrow) con-sistently exhibited greater breeding season densities inradial landscapes centered on row-crop fields containingnative grass buffers than in landscapes with nonbufferedfields over the 14-state study area. Five species respondedpositively to buffers in some regions and in some years,suggesting regional and annual variability must be ad-dressed in large-scale studies to avoid biased conclusionsand ill-informed management recommendations (Bakkeret al. 2002; Davey et al. 2010a). Relative effect sizes insome regions were disproportionate to the amount ofnative grasses added to the immediate landscape, sug-gesting buffers may increase total usable space (Guthery

1997) by altering functional use of adjacent areas (Smith& Burger 2009).

Regional differences in observed relative effect sizemay also result from varying metapopulation processesdriven by surrounding landscape factors (Tscharntkeet al. 2005; Kleijn et al. 2011). Addition of native grasses inregions with limited amounts of native grass, high perme-ability, and minimal landscape complexity may maximizethe relative effectiveness of conservation buffer practicesfor some bird species (Tscharntke et al. 2005; Kleijnet al. 2011). Though we did not directly test influences oflandscape composition and complexity, it may take verysmall habitat amounts to elicit and sustain positive relativeeffect sizes in some species in regions with low popula-tion abundances and very limited habitat. Such resultswere observed for Corn Buntings (Emberiza calandra)in Scotland (Perkins et al. 2011), bumble bees (Bombusspp.) in the United Kingdom (Carvell et al. 2011), andin a comprehensive multitaxa meta-analysis (Batary et al.2011), where targeted agrienvironmental conservationpractices in all the studies were more effective in inten-sive agricultural landscapes than in structurally complexlandscapes.

Alternatively, in regions with abundant target speciespopulations, such as the Central Mixed-grass Prairie, in-cremental additions of native grass buffers may not pro-vide the necessary habitat to elicit positive relative ef-fect sizes in some species. Northern Bobwhite and otherspecies may be subject to different limiting factors (e.g.,climate, habitat selection preferences [Whittinghamet al. 2007]) in this region than in other regions or requiremore native grass to elicit a positive relative effect sizethan CP33 buffers provided.

Further study is necessary to determine ecologicalmechanisms and limiting factors driving observed dif-ferences in relative effect size among species, regions,and years (Davey et al. 2010a) and to determine if ob-served relative effect sizes represent net population in-creases or simple redistribution of individuals within thelandscape. Previous farm-scale studies suggest greaterbreeding and overwintering bird densities on field mar-gins bordered by native herbaceous vegetation in Mis-sissippi (e.g., Smith et al. 2005a, 2005b; Conover et al.2009) and North Carolina (e.g., Marcus et al. 2000; Riddleet al. 2008). Smith (2004) found field buffers influencedsecond-order habitat use (i.e., home range selection) butnot survival in radio-marked Northern Bobwhite. In theUnited Kingdom, Gray Partridge (Perdix perdix) abun-dance is greater where conservation headlands (i.e., se-lective pesticide spray on outer 6–12 m of cereal crop)and wild bird cover practices (i.e., 6 m of noncroppedfield margins cultivated with wild bird seed mixture) arein place (Ewald et al. 2010), and Yellowhammer (Em-beriza citrinella) density is greater where entry levelstewardship margins (i.e., whole-farm per-hectare con-servation incentives, including buffer strips and boundary



management) have been established (Davey et al. 2010b).Conservation practices (including field buffers) targetingrestoration of threatened Cirl Bunting (Emberiza cirlus)populations increased their abundance 83% relative tounmanaged areas (Peach et al. 2001). Furthermore, con-servation practices targeting restoration of Corn Buntingsincreased abundances 5.6% annually, whereas abundancedecreased 14.5% annually on conventional farms (Perkinset al. 2011).

Regional variation in our study suggests native herba-ceous buffers such as those established via the CP33practice will increase population densities of some grass-land bird species in most regions, but density gainswill be higher during the breeding season for prioritybird species such as Northern Bobwhite when buffersare established in agricultural landscapes in the EasternTallgrass Prairie and Mississippi Alluvial Valley. Futureconservation practices developed to promote sustain-able wildlife populations should therefore be tailored tomeet regional habitat requirements. However, managersshould use caution when ascribing broad-scale conserva-tion success from targeted practices to a suite of species(e.g., grassland birds) because targeted practices cannotaddress the multiple resource requirements of all grass-land bird species (Brennan & Kuvlesky 2005). Buffers mayprovide adequate vegetation structure for some speciesbut fail to meet structure requirements of other species(e.g., Eastern Meadowlark and Grasshopper Sparrow).We recommend managers combine multiple conserva-tion practices and deliver them strategically to increaselandscape complexity via provision of an array of nestingand foraging habitats to meet multispecies recovery ob-jectives and enhance biodiversity and ecosystem services(Grice et al. 2004; Batary et al. 2011). Targeted conserva-tion practices strategically applied at the landscape levelcould provide necessary habitat to meet life-history needswith minimal effect on agricultural production (Barbouret al. 2007; Schonhart et al. 2011; McConnell & Burger2012).

In the United States and Europe, government-fundedconservation programs are under perennial threat of re-duction, and proof of conservation benefits from theseprograms has become increasingly important (Burgeret al. 2006a; Whitfield 2006). To be effective, policy-driven agricultural conservation must be informed bysound scientific research. Results of the CP33 moni-toring program demonstrates that multiscale evaluationof wildlife response to a conservation practice is fullyachievable and should be a critical feedback compo-nent to future conservation policy (Whittingham 2007;Perkins et al. 2011). Total federal costs for CP33 moni-toring were approximately 1–2% of total programmaticcosts. We therefore recommend programmatic funds forevaluation of future government-sponsored conservationprovisions will be a cost-effective means to self-correctagricultural policy and should be included from program-matic conception to allow for optimization of future con-

servation policy decisions (Grice et al. 2004; Robertson &Swinton 2005).

Acknowledgments

The national CP33 monitoring program was coordi-nated and delivered by the Department of Wildlife,Fisheries, and Aquaculture and the Forest and WildlifeResearch Center, Mississippi State University. The na-tional CP33 monitoring program was funded by theMultistate Conservation Grant Program (Grants MS M-1-T, MS M-2-R), a program supported with funds fromthe Wildlife and Sport Fish Restoration Program andjointly managed by the Association of Fish and WildlifeAgencies, U.S. Fish and Wildlife Service, USDA-FarmService Agency, and USDA-Natural Resources Conser-vation Service-Conservation Effects Assessment Project.Collaborators included Arkansas Game and Fish Commis-sion, Georgia Department of Natural Resources, IllinoisDepartment of Natural Resources/Ballard Nature Cen-ter, Indiana Department of Natural Resources, Iowa De-partment of Natural Resources, Kentucky Departmentof Fish and Wildlife Resources/Kentucky Chapter ofThe Wildlife Society, Mississippi Department of Wildlife,Fisheries and Parks, Missouri Department of Conser-vation, Nebraska Game and Parks Commission, NorthCarolina State University, North Carolina Wildlife Re-sources Commission, Ohio Department of Natural Re-sources, Ohio Pheasants Forever, South Carolina Depart-ment of Natural Resources, Tennessee Wildlife ResourcesAgency, Texas Audubon, Texas Parks and Wildlife Depart-ment, Union University, University of Tennessee-Martin,Southeast Quail Study Group, and Southeast PartnersIn Flight.

Supporting Information

Level of stratification of the detection function for eachspecies (Appendix S1) and annual regional and over-all density estimates and effect sizes (Appendix S2) areavailable on-line. The authors are solely responsible forthe content and functionality of these materials. Queries(other than absence of the material) should be directedto the corresponding author.

Literature Cited

Akaike, H. 1973. Information theory and an extension of the maximumlikelihood principle. Pages 267–281 in B. N. Petrov and F. Csaki,editors. Proceedings of a second international symposium on infor-mation theory. Akademiai Kiado, Budapest.

Bakker, K. K., D. E. Naugle, and K. F. Higgins. 2002. Incorporatinglandscape attributes into models for migratory grassland bird con-servation. Conservation Biology 16:1638–1646.

Barbour, P. J., S. W. Martin, and W. Burger. 2007. Estimating economicimpact of conservation field borders on farm revenue. Crop Man-agement 6. DOI:10.1094/CM-2007-0614-01-RS.


Evans et al. 9

Batary, P., A. Baldi, D. Kleijn, and T. Tscharntke. 2011. Landscape-moderated biodiversity effects of agri-environmental management:a meta-analysis. Proceedings of the Royal Society of London, SeriesB 278:1894–1902.

Brennan, L. A., and W. P. Kuvlesky Jr. 2005. North American grasslandbirds: An unfolding conservation crisis? Journal of Wildlife Manage-ment 69:1–13.

Buckland, S. T. 1992. Fitting density functions with polynomials. Ap-plied Statistics 41:63–76.

Buckland, S. T., D. R. Anderson, K. P. Burnham, J. L. Laake, D. L.Borchers, and L. Thomas. 2001. Introduction to distance sampling.Oxford University Press, Oxford.

Burger, L. W., Jr., D. McKenzie, R. Thackston, and S. J. DeMaso. 2006a.The role of farm policy in achieving large-scale conservation: bob-white and buffers. Wildlife Society Bulletin 34:986–993.

Burger, W., M. D. Smith, R. Hamrick, B. Palmer, and S. Wellendorf.2006b. CP33—Habitat Buffers for Upland Birds monitoring proto-col. Mississippi State University Miscellaneous Publication, Missis-sippi.

Carvell, C., J. L. Osborne, A. F. G. Bourke, S. N. Freeman, R. F. Pywell,and M. S. Heard. 2011. Bumble bee species’ response to a targetedconservation measure depend on landscape context and habitatquality. Ecological Applications 21:1760–1771.

Conover, R. R., L. W. Burger Jr., and E. T. Linder. 2009. Breedingbird response to field border presence and width. Wilson Journal ofOrnithology 121:548–555.

Davey, C., J. Vickery, N. Boatman, D. Chamberlain, H. Parry, and G.Siriwardena. 2010a. Regional variation in the efficacy of entry levelstewardship in England. Agriculture, Ecosystems and Environment139:121–128.

Davey, C. M., J. A. Vickery, N. D. Boatman, D. E. Chamberlain, and G.M. Siriwardena. 2010b. Entry level stewardship may enhance birdnumbers in boundary habitats. Bird Study 57:415–420.

Dimmick, R. W., M. J. Gudlin, and D. F. McKenzie. 2002. The North-ern Bobwhite conservation initiative. Miscellaneous publication ofthe Southeastern Association of Fish and Wildlife Agencies, SouthCarolina.

Evans, K. O. 2012. Multi-scale response of upland birds to targeted agri-cultural conservation. PhD dissertation. Mississippi State University,Mississippi.

Ewald, J. A., N. J. Aebischer, S. M. Richardson, P. V. Grice, and A.I. Cooke. 2010. The effect of agri-environment schemes on greypartridges at the farm level in England. Agriculture, Ecosystems andEnvironment 138:55–63.

Gardner, M. J., and D. G. Altman. 1989. Estimation rather than hy-pothesis testing: confidence intervals rather than p values. Pages6–19 in M. J. Gardner and D. G. Altman, editors. Statistics withconfidence: confidence intervals and statistical guidelines. BritishMedical Association, London.

Grice, P., A. Evans, J. Osmond, and R. Brand-Hardy. 2004. Science intopolicy: the role of research in the development of a recovery planfor farmland birds in England. Ibis 146:239–249.

Guthery, F. S. 1997. A philosophy of habitat management for northernbobwhites. Journal of Wildlife Management 61:291–301.

Hoffmann, M., et al. 2010. The impact of conservation on the status ofthe world’s vertebrates. Science 330:1503–1509.

Kleijn, D., M. Rundlof, J. Scheper, H. G. Smith, and T. Tscharntke. 2011.Does conservation on farmland contribute to halting the biodiversitydecline? Trends in Ecology & Evolution 26:474–481.

Lovell, S. T., and W. C. Sullivan. 2006. Environmental benefits of con-servation buffers in the United States: evidence, promise, and openquestions. Agriculture, Ecosystems and Environment 112:249–260.

Marcus, J. F., W. E. Palmer, and P. T. Bromley. 2000. The effects of farmfield borders on overwintering sparrow densities. Wilson Bulletin112:517–523.

Marques, F. C., and S. T. Buckland. 2003. Incorporating covariates intostandard line transect analyses. Biometrics 59:924–935.

Marques, T. A., L. Thomas, S. G. Fancy, and S. T. Buckland. 2007. Im-proving estimates of bird density using multiple covariate distancesampling. Auk 124:1229–1243.

McConnell, M., and L. W. Burger. 2012. Precision conservation: ageospatial decision support tool for optimizing conservation andprofitability in agricultural landscapes. Journal of Soil and WaterConservation 66:347–354.

National Bobwhite Technical Committee. 2011. W. E. Palmer, T. M. Ter-hune, and D. F. McKenzie, editors. The National Bobwhite Conserva-tion Initiative: a range-wide plan for recovering bobwhites. NationalBobwhite Technical Committee Technical Publication, version 2.0,Knoxville, Tennessee.

North American Bird Conservation Initiative. 2000. Bird conservationregion descriptions: a supplement to the North American Bird Con-servation Initiative Bird Conservation Region Map. U.S. NABCI Com-mittee.

North American Bird Conservation Initiative Monitoring Subcommittee.2007. Opportunities for improving avian monitoring. U.S. NorthAmerican Bird Conservation Initiative Report. Division of MigratoryBird Management, U.S. Fish and Wildlife Service, Arlington, Virginia.

Pacifici, K., T. R. Simons, and K. H. Pollock. 2008. Effects of vegetationand background noise on the detection process in auditory avianpoint-count surveys. Auk 125:600–607.

Peach, W. J., L. J. Lovett, S. R. Wotton, and C. Jeffs. 2001. Countrysidestewardship delivers cirl buntings (Emberiza circulus) in Devon,UK. Biological Conservation 101:361–373.

Perkins, A. J., H. E. Maggs, A. Watson, and J. D. Wilson. 2011. Adaptivemanagement and targeting of agri-environment schemes does bene-fit biodiversity: a case study of the corn bunting Emberiza calandra.Journal of Applied Ecology 48:514–522.

Riddle, J. D., C. E. Moorman, and K. H. Pollock. 2008. The im-portance of habitat shape and landscape context to NorthernBobwhite populations. Journal of Wildlife Management 72:1376–1382.

Robertson, G. P., and S. M. Swinton. 2005. Reconciling agriculturalproductivity and environmental integrity: a grand challenge for agri-culture. Frontiers in Ecology and Environment 3:38–46.

Sauer, J. R., J. E. Hines, J. E. Fallon, K. L. Pardieck, D. J. ZiolkowskiJr., and W. A. Link. 2011. The North American Breeding BirdSurvey, results and analysis 1966–2009. Version 3.23.2011. USGSPatuxent Wildlife Research Center, Laurel, Maryland. Available fromhttp://www.mbr-pwrc.usgs.gov/bbs/ (accessed Dec 2011).

Schonhart, M., T. Schauppenlehner, E. Schmid, and A. Muhar. 2011.Integration of bio-physical and economic models to analyze manage-ment intensity and landscape structure effects at farm and landscapelevel. Agricultural Systems 104:122–134.

Sim, J., and N. Reid. 1999. Statistical inference by confidence intervals:issues of interpretation and utilization. Physical Therapy 79:186–195.

Smith, M. D. 2004. Wildlife habitat benefits of field border managementpractices in Mississippi. PhD dissertation. Mississippi State Univer-sity, Mississippi.

Smith, M. D., and L. W. Burger Jr. 2009. Population response of northernbobwhite to field border management practices in Mississippi. Pages220–231 in S. B. Cederbaum, B. C. Faircloth, T. M. Terhune, J.J. Thompson, and J. P. Carroll, editors. Gamebird 2006: Quail VIand Perdix XII. Warnerll School of Forestry and Natural Resources,Athens, Georgia.

Smith, M. D., P. J. Barbour, L. W. Burger Jr., and S. J. Dinsmore.2005a. Density and diversity of overwintering birds in managedfield borders in Mississippi. Wilson Journal of Ornithology 117:258–269.

Smith, M. D., P. J. Barbour, L. W. Burger Jr., and S. J. Dinsmore. 2005b.Breeding bird abundance and diversity in agricultural field bordersin the Black Belt Prairie of Mississippi. Proceedings of the AnnualConference of the Southeastern Association of Fish and WildlifeAgencies 59:43–56.



Sullivan, P., et al. 2004. The Conservation Reserve Program: economicimplications for rural America. Agricultural Economic Report 83.U.S. Department of Agriculture Economic Research Service, Wash-ington, D.C.

Sutherland, W. J., A. S. Pullin, P. M. Dolman, and T. M. Knight. 2004.The need for evidence-based conservation. Trends in Ecology &Evolution 19:305–308.

Thomas, L., S. T. Buckland, E. A. Rexstad, J. L. Laake, S. Strindberg, S.L. Hedley, J. R. B. Bishop, T. A. Marques, and K. P. Burnham. 2010.Distance software: design and analysis of distance sampling surveysfor estimating population size. Journal of Applied Ecology 47:5–14.

Tscharntke, T., A. M. Klein, A. Kruess, I. Steffan-Dewenter, and C.Thies. 2005. Landscape perspectives on agricultural intensification

and biodiversity—ecosystem service management. Ecology Letters8:857–874.

U. S. Department of Agriculture. 2004. Practice CP33 habitat buffersfor upland wildlife. Notice CRP-479. USDA Farm Service Agency,Washington, D.C.

Whitfield, J. 2006. How green was my subsidy? Nature 439:908–909.Whittingham, M. J. 2007. Will agri-environment schemes deliver sub-

stantial biodiversity gain, and if not why not? Journal of AppliedEcology 44:1–5.

Whittingham, M. J., J. R. Krebs, R. D. Swetnam, J. A. Vickery, J. D.Wilson, and R. P. Freckleton. 2007. Should conservation strategiesconsider spatial generality? Farmland birds show regional not na-tional patterns of habitat association. Ecology Letters 10:25–35.


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