Timothy J. Fox

A cautionary tale regarding use of the National Land Cover Dataset 1992

Abstract Digital land-cover data are among the most popular data sources used in ecological research and natural resource management. However, processes for accurate land-cover classification over large regions are still evolving. We identified inconsistencies in the National Land Cover Dataset 1992, the most current and available representation of land cover for the conterminous United States. We also report means to address these inconsistencies in a bird-habitat model. We used a Geographic Information System (GIS) to position a regular grid (or lattice) over the upper midwestern United States and summarized the proportion of individual land covers in each cell within the lattice. These proportions were then mapped back onto the lattice, and the resultant lattice was compared to satellite paths, state borders, and regional map classification units. We observed mapping inconsistencies at the borders between mapping regions, states, and Thematic Mapper (TM) mapping paths in the upper midwestern United States, particularly related to grassland-herbaceous, emergent-herbaceous wetland, and small-grain land covers. We attributed these discrepancies to differences in image dates between mapping regions, suboptimal image dates for distinguishing certain land-cover types, lack of suitable ancillary data for improving discrimination for rare land covers, and possibly differences among image interpreters. To overcome these inconsistencies for the purpose of modeling regional populations of birds, we combined grassland-herbaceous and pasture-hay land-cover classes and excluded the use of emergent-herbaceous and small-grain land covers. We recommend that users of digital land-cover data conduct similar assessments for other regions before using these data for habitat evaluation. Further, caution is advised in using these data in the analysis of regional land-cover change because it is not likely that future digital land-cover maps will repeat the same problems, thus resulting in biased estimates of change.

Breeding bird territory placement in riparian wet meadows in relation to invasive reed canary grass, Phalaris arundinacea.

Invasive plants are a growing concern worldwide for conservation of native habitats. In endangered wet meadow habitat in the Upper Midwestern United States, reed canary grass (Phalaris arundinacea) is a recognized problem and its prevalence is more widespread than the better-known invasive wetland plant purple loosestrife (Lythrum salicaria). Although resource managers are concerned about the effect of reed canary grass on birds, this is the first study to report how common wet meadow birds use habitat in relation to reed canary grass cover and dominance. We examined three response variables: territory placement, size of territories, and numbers of territories per plot in relation to cover of reed canary grass. Territory locations for Sedge Wren (Cistothorus platensis) and Song Sparrow (Melospiza melodid) were positively associated with reed canary grass cover, while those for Common Yellowthroat (Geothlypis trichas) were not. Only Swamp Sparrow (M. georgiana) territory locations were negatively associated with reed canary grass cover and dominance (which indicated a tendency to place territories where there was no reed canary grass or where many plant species occurred with reed canary grass). Swamp Sparrow territories were positively associated with vegetation height density and litter depth. Common Yellowthroat territories were positively associated with vegetation height density and shrub cover. Song Sparrow territories were negatively associated with litter depth. Reed canary grass cover within territories was not associated with territory size for any of these four bird species. Territory density per plot was not associated with average reed canary grass cover of plots for all four species. Sedge Wrens and Song Sparrows may not respond negatively to reed canary grass because this grass is native to wet meadows of North America, and in the study area it merely replaces other tall lush plants. Avoidance of reed canary grass by Swamp Sparrows may be mediated through their preference for wet areas where reed canary grass typically does not dominate.

Curve Fit: a pixel‐level raster regression tool for mapping spatial patterns

Summary 1. Despite the fact that pixels (i.e. picture elements) are the basic sampling units of maps, we are aware of no software package or tool that allows users to model changes that may occur at such fine spatial resolutions over broad geographic extents. 2. Curve Fit is an extension to the application ArcMap that allows users to conduct linear or nonlinear regression analysis on the range of values found within input ras ter data sets (geo-referenced images), independently for each pixel. 3. Outputs consist of raster surfaces of regression model parameter estimates, standard errors, goodness-of-fit estimates and multimodel inference measures. 4. Curve fit outputs characterize continuous spatial or temporal change across a series of raster data sets.

A generalizable energetics‐based model of avian migration to facilitate continental‐scale waterbird conservation

Conserving migratory birds is made especially difficult because of movement among spatially disparate locations across the annual cycle. In light of challenges presented by the scale and ecology of migratory birds, successful conservation requires integrating objectives, management, and monitoring across scales, from local management units to ecoregional and flyway administrative boundaries. We present an integrated approach using a spatially explicit energetic-based mechanistic bird migration model useful to conservation decision-making across disparate scales and locations. This model moves a Mallard-like bird (Anas platyrhynchos), through spring and fall migration as a function of caloric gains and losses across a continental-scale energy landscape. We predicted with this model that fall migration, where birds moved from breeding to wintering habitat, took a mean of 27.5 d of flight with a mean seasonal survivorship of 90.5% (95% Cl = 89.2%, 91.9%), whereas spring migration took a mean of 23.5 d of flight with mean seasonal survivorship of 93.6% (95% CI = 92.5%, 94.7%). Sensitivity analyses suggested that survival during migration was sensitive to flight speed, flight cost, the amount of energy the animal could carry, and the spatial pattern of energy availability, but generally insensitive to total energy availability per se. Nevertheless, continental patterns in the bird-use days occurred principally in relation to wetland cover and agricultural habitat in the fall. Bird-use days were highest in both spring and fall in the Mississippi Alluvial Valley and along the coast and near-shore environments of South Carolina. Spatial sensitivity analyses suggested that locations nearer to migratory endpoints were less important to survivorship; for instance, removing energy from a 1036 km2 stopover site at a time from the Atlantic Flyway suggested coastal areas between New Jersey and North Carolina, including the Chesapeake Bay and the North Carolina piedmont, are essential locations for efficient migration and increasing survivorship during spring migration but not locations in Ontario and Massachusetts. This sort of spatially explicit information may allow decision-makers to prioritize their conservation actions toward locations most influential to migratory success. Thus, this mechanistic model of avian migration provides a decision-analytic medium integrating the potential consequences of local actions to flyway-scale phenomena.