Landowner and Practitioner Perspectives on Private Land Conservation Programs

<p>Efforts to reverse declines in native grasslands benefit from agricultural policies that encourage private land conservation. The U.S. Department of Agriculture’s Conservation Reserve Program (CRP) improved conservation across landscapes but enrollment has declined. We used sequential exploratory mixed methods to compare landowner and conservation practitioners’ perceptions, evaluate perceived benefits, and identify potential improvements to CRP. Focus groups of practitioners informed a quantitative survey of landowners who had properties >160 total acres in Nebraska. Results suggest potential misalignment in perceptions between practitioners and landowners. Practitioners were concerned that conservation, especially of wildlife, was secondary to profit. But the majority of landowners valued CRP-related ecosystem services, including native pollinators. Practitioners posited that younger landowners were primarily profit motivated, but CRP enrollment did not differ by demographics. Practitioners and landowners identified rule complexity as a major challenge and practitioner–landowner relationships as critical to success. Findings suggest that practitioners may underestimate non-economic motivations and illuminate opportunities to encourage private land conservation.</p

The evaluation of the predictive performance of the Ring-necked Pheasant fitted and the corrected species distribution models.

<p>Standardized predicted values of Ring-necked Pheasant abundance compared to observed abundance values from an independent dataset collected in 2012 indicated that both the original spatial model (A) and the corrected spatial model (B) perform well. Data points are identified in blue, where the intensity of points is reflected by the color shade (dark blue = high intensity, and light blue = low intensity). The solid black line represents the fitted least-squares regression line and the two dashed lines represent the 95% confidence intervals. The dotted line identifies where a perfect fit would occur between predicted pheasant abundance and observed abundance.</p

The change in Ring-necked Pheasant response to CRP enrollment as the saturation of trees or small grains varies in the surrounding landscape (5 km radius).

<p>CRP enrollment increases pheasant abundance; however the benefits of CRP are inhibited by trees (a) in the surrounding landscape while aided by small grains (b). Solid line represents null relationship of CRP and pheasant counts. Dotted lines represent additive effects of the second cover type in the landscape.</p

The final 30×30-m resolution predicted Ring-necked Pheasant species distribution model for Nebraska based on the corrected fitted land cover and topographic variables.

<p>The range of predicted values was divided into ten categories based on an equal area approach, whereas each color class represents 10% of the area within the entire species distribution model. Classifying the relative predicted abundance values using this approach allows users to pinpoint the top 10% of the areas within the Nebraska that contain the highest predicted abundance (bright red), which is useful in management planning and implementation.</p

Assessing Landscape Constraints on Species Abundance: Does the Neighborhood Limit Species Response to Local Habitat Conservation Programs?

<div><p>Landscapes in agricultural systems continue to undergo significant change, and the loss of biodiversity is an ever-increasing threat. Although habitat restoration is beneficial, management actions do not always result in the desired outcome. Managers must understand why management actions fail; yet, past studies have focused on assessing habitat attributes at a single spatial scale, and often fail to consider the importance of ecological mechanisms that act across spatial scales. We located survey sites across southern Nebraska, USA and conducted point counts to estimate Ring-necked Pheasant abundance, an economically important species to the region, while simultaneously quantifying landscape effects using a geographic information system. To identify suitable areas for allocating limited management resources, we assessed land cover relationships to our counts using a Bayesian binomial-Poisson hierarchical model to construct predictive Species Distribution Models of relative abundance. Our results indicated that landscape scale land cover variables severely constrained or, alternatively, facilitated the positive effects of local land management for Ring-necked Pheasants.</p></div

Pairwise Spearman’s ranked correlation Rho statistics for land cover variables.

<p>Pairwise Spearman’s ranked correlation Rho statistics for land cover variables.</p

The relationships between Ring-necked Pheasant abundance and the proportion of land cover types within a 5 km radius.

<p>Ring-necked Pheasant populations respond positively to the proportion of row crop agriculture and small grains within the landscape (5 km radius), but negatively to the proportion of trees in the landscape. Solid line represents land cover relationships and the dashed lines represent the 95% credible intervals predicted out to the maximum range we observed during the study.</p

Parameter estimates of habitat and topographic variables measured at the management (1 km radius) and landscape scales (5 km radius), and the mixed-scale model with habitat variables measured at both the management and landscape spatial scales.

<p>Parameter estimates of habitat and topographic variables measured at the management (1 km radius) and landscape scales (5 km radius), and the mixed-scale model with habitat variables measured at both the management and landscape spatial scales.</p

Parameter estimates of habitat and topographic variables measured at the management (1 km radius) and landscape scales (5 km radius), and the mixed-scale model with habitat variables measured at both the management and landscape spatial scales.

<p>Parameter estimates of habitat and topographic variables measured at the management (1 km radius) and landscape scales (5 km radius), and the mixed-scale model with habitat variables measured at both the management and landscape spatial scales.</p

A directed acyclic graph describing the hierarchical Bayesian binomial-Poisson model used to assess the relationships between various land cover variables and Ring-necked Pheasant abundance.

<p>Black nodes represent the non-covariate structure and the gray nodes represent the covariate structure. Notation: <i>y_ij</i> is the number of pheasants detected at survey site <i>i</i> during the <i>jth</i> survey and represents the product of a binomial distribution given the probability of detecting an individual (<i>p_ij</i>) and the number of individuals truly present was <i>N_i</i>. The detection probability, <i>p_ij</i>, at site <i>i</i> during the <i>jth</i> survey is a logit-linear function of covariates and parameter estimates . It is assumed that <i>N_i</i> is Poisson distributed with a mean of <i>λ</i>. Mean abundance at site i is a function of site-specific covariates with a random intercept and a slope of .</p