Identification of functional corridors with movement characteristics of brown bears on the Kenai Peninsula,Alaska

We identified primary habitat and functional corridors across a landscape using Global Positioning System (GPS) collar locations of brown bears (Ursus arctos). After deriving density, speed, and angular deviation of movement, we classified landscape function for a group of animals with a cluster analysis. We described areas with high amounts of sinuous movement as primary habitat patches and areas with high amounts of very directional, fast movement as highly functional bear corridors. The time between bear locations and scale of analysis influenced the number and size of corridors identified. Bear locations should be collected at intervals ≤6 h to correctly identify travel corridors. Our corridor identification technique will help managers move beyond the theoretical discussion of corridors and linkage zones to active management of landscape features that will preserve connectivity.     

RothCUK – a dynamic modelling system for estimating changes in soil C from mineral soils at 1-km resolution in the UK

We describe the development and application of an integrated data and modelling system for estimating soil carbon (C) fluxes from mineral soils caused by changes in climate, land use and land management at 1‐km resolution in the UK (RothCUK). The system was developed with the aim of improving methods for United Nations Framework Convention on Climate Change (UNFCCC) and Kyoto Protocol accounting and integrates national scale data sets of soil properties, land use and climate with the Rothamsted carbon model (RothC). A preliminary estimate of soil C fluxes because of land use change (LUC) over the period 1990–2000 is presented as an example application of the system. RothCUK shows LUC to be a net source of CO₂ from 1990 to 2000 although the RothC estimate was smaller (6488 kt C) than the estimate from the single exponential model (SEM) method currently used to calculate C fluxes due to LUC for the UK National Greenhouse Gas Inventory (mean: 9412 kt C). Based on previous studies, an uncertainty range in our estimates of ±50–100% seems plausible. In agreement with the SEM, RothCUK suggests that the largest single contributor to soil C fluxes from LUC was conversion of grassland to arable land. Differences between the results may be attributed to differences in the two models and the assumptions and underlying data used in making the calculations. The RothCUK system provides a powerful method for estimating changes in soil C stocks, enabling areas and management systems with particularly large changes in soil C stocks to be located at fine resolution.     

Estimating landscape resistance to dispersal

Dispersal is an inherently spatial process that can be affected by habitat conditions in sites encountered by dispersers. Understanding landscape resistance to dispersal is important in connectivity studies and reserve design, but most existing methods use resistance functions with cost parameters that are subjectively chosen by the investigator. We develop an analytic approach allowing for direct estimation of resistance parameters that folds least cost path methods typically used in simulation approaches into a formal statistical model of dispersal distributions. The core of our model is a frequency distribution of dispersal distances expressed as least cost distance rather than Euclidean distance, and which includes terms for feature-specific costs to dispersal and sex (or other traits) of the disperser. The model requires only origin and settlement locations for multiple individuals, such as might be obtained from mark–recapture studies or parentage analyses, and maps of the relevant habitat features. To evaluate whether the model can estimate parameters correctly, we fit our model to data from simulated dispersers in three kinds of landscapes (in which resistance of environmental variables was categorical, continuous with a patchy configuration, or continuous in a trend pattern). We found maximum likelihood estimators of resistance and individual trait parameters to be approximately unbiased with moderate sample sizes. We applied the model to a small grizzly bear dataset to demonstrate how this approach could be used when the primary interest is in the prediction of costs and found that estimates were consistent with expectations based on bear ecology. Our method has important practical applications for testing hypotheses about dispersal ecology and can be used to inform connectivity planning efforts, via the resistance estimates and confidence intervals, which can be used to create a data-driven resistance surface.     

Enhanced Phosphorus Fertilizer (Carbond P®) Supplied to Maize in Moderate and High Organic Matter Soils

Carbond P (CBP) fertilizer often increases P uptake and crop yields in low P and organic matter soils. A glasshouse study was conducted with maize (Zea mays L.) grown in moderate or high organic matter soil with 0, 5, 15, 45, or 135 kg phosphorus pentoxide (P₂O₅) ha^?1 applied as either ammonium polyphosphate (APP) or CBP. In the high organic matter soil, both CBP and APP fertilization resulted in similar increases in biomass yield and P concentration and uptake. This was also observed in the moderate organic matter soil for maize P concentration, but biomass yield and total P uptake were significantly greater for CBP than APP at the two lowest P rates of fertilization and significantly higher for APP than CBP at the highest P application rate. The presence of high organic matter in the soil seemed to negate the effects of the organic acid bonded P found in CBP.     

The influence of landscape characteristics and home-range size on the quantification of landscape-genetics relationships

A common approach used to estimate landscape resistance involves comparing correlations of ecological and genetic distances calculated among individuals of a species. However, the location of sampled individuals may contain some degree of spatial uncertainty due to the natural variation of animals moving through their home range or measurement error in plant or animal locations. In this study, we evaluate the ways that spatial uncertainty, landscape characteristics, and genetic stochasticity interact to influence the strength and variability of conclusions about landscape-genetics relationships. We used a neutral landscape model to generate 45 landscapes composed of habitat and non-habitat, varying in percent habitat, aggregation, and structural connectivity (patch cohesion). We created true and alternate locations for 500 individuals, calculated ecological distances (least-cost paths), and simulated genetic distances among individuals. We compared correlations between ecological distances for true and alternate locations. We then simulated genotypes at 15 neutral loci and investigated whether the same influences could be detected in simple Mantel tests and while controlling for the effects of isolation-by-distance using the partial Mantel test. Spatial uncertainty interacted with the percentage of habitat in the landscape, but led to only small reductions in correlations. Furthermore, the strongest correlations occurred with low percent habitat, high aggregation, and low to intermediate levels of cohesion. Overall genetic stochasticity was relatively low and was influenced by landscape characteristics.