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Disease surveillance in wildlife populations involves detecting the presence of a disease, characterizing its prevalence and spread, and subsequent monitoring. A probability sample of animals selected from the population and corresponding estimators of disease prevalence and detection provide estimates with quantifiable statistical properties, but this approach is rarely used. Although wildlife scientists often assume probability sampling and random disease distributions to calculate sample sizes, convenience samples (i.e., samples of readily available animals) are typically used, and disease distributions are rarely random. We demonstrate how landscape-based simulation can be used to explore properties of estimators from convenience samples in relation to probability samples. We used simulation methods to model what is known about the habitat preferences of the wildlife population, the disease distribution, and the potential biases of the convenience-sample approach. Using chronic wasting disease in free-ranging deer (Odocoileus virginianus) as a simple illustration, we show that using probability sample designs with appropriate estimators provides unbiased surveillance parameter estimates but that the selection bias and coverage errors associated with convenience samples can lead to biased and misleading results. We also suggest practical alternatives to convenience samples that mix probability and convenience sampling. For example, a sample of land areas can be selected using a probability design that oversamples areas with larger animal populations, followed by harvesting of individual animals within sampled areas using a convenience sampling method.

Prairies and other North American grasslands, although highly fragmented, provide breeding habitat for a diverse array of species, including species of tremendous economic and ecological importance. Conservation and management of these species requires some understanding of how reproductive success is affected by edge effects, patch size, and characteristics of the landscape. We examined how differences in the percentage of grassland in the landscape influenced the relationships between the success of nests of upland-nesting ducks and (1) field size and (2) distance to nearest field and wetland edges. We collected data on study areas composed of 15-20% grassland and areas composed of 45-55% grassland in central North Dakota, USA during the 1996 and 1997 nesting seasons. Daily survival rates (DSRs) of duck nests were greater in study areas with 45-55% grassland than with 15-20% grassland. Within study areas, we detected a curvilinear relationship between DSR and field size: DSRs were highest in small and large fields and lowest in moderately sized fields. In study areas with 15-20% grassland, there was no relationship between probability of hatching and distance to nearest field edge, whereas in study areas with 45-55% grassland, there was a positive relationship between these two variables. Results of this study support the conclusion that both landscape composition and configuration affect reproductive success of ground-nesting birds. We are prompted to question conservation strategies that favor clustering moderately sized patches of nesting habitat within agricultural landscapes because our results show that such patches would have low nest success, most likely caused by predation. Understanding the pattern of nest success, and the predator-prey mechanisms that produce the pattern, will enable design of patch configurations that are most conducive to meeting conservation goals.

Management of ring-necked pheasants (Phasianus colchicus) in agricultural landscapes would be enhanced by knowledge of the relation between survival and habitat composition and configuration. We related survival and habitat use of hen pheasants during spring in Iowa with landscape characteristics in an area of high habitat diversity with 25.0% grassland and an area of low habitat diversity with 9.3% grassland. Survival of 215 radiomarked hens from 1 April to 3 June 1992-94 averaged 0.81 and did not differ between areas (P = 0.756). Predation was the cause of death in 87.5% of the cases, with 66.7% of all deaths attributed to mammals, especially red fox (Vulpes vulpes). Home ranges of 57 hens averaged 36.6 ha in the high diversity area and 47.7 ha in the low diversity area and did not differ between areas (P = 0.603). Density of edge between grassland and other habitats was predictive of the hazard rate, and the odds of mortality increased 2% for every 10 m/ha of additional edge in the home range. Hens with home ranges characterized by small patches of grassland within the cropland matrix survived as well as those with large blocks of grassland in their home range. Understanding how changes in composition and configuration of landscapes affects wildlife demographics at multiple scales can improve managers' ability to take advantage of agricultural conservation programs.

An increasing number of state and national databases are available to assess agricultural and environmental trends in natural resource populations. We use a case study approach to consider methodologies for combining state and national data to assess the impact of agricultural policy on state wildlife populations. The scientific question is to assess the impact of the Conservation Reserve Program on pheasant populations in Iowa, using land cover/use data from the National Resources Inventory and count data from an annual state pheasant population survey. Our approach involves identifying a common spatial polygon for linking summaries from each of two datasets, and then estimating parameters that describe temporal trends in land cover and in pheasant populations over a common time period within each polygon. Estimated pheasant population parameters are regressed on land cover summaries to investigate the impact of the Conservation Reserve Program on pheasant populations in regions of the state. Results reveal that the population response to the Conservation Reserve Program varies by region in relation to the physiography and agricultural use of the region, in ways that were not anticipated by policy developers. Statistical considerations for developing appropriate models for combining data are discussed.

Muskrat (Ondatra zibethicus) populations were studied in backwater and open-water habitats of Pool Nine of the Upper Mississippi River to determine density, natality, survival, and harvest rate. Density in backwater habitats ranged from 0.3 to 3.7 ± 0.7 adults/ha, which was lower than open-water densities, which ranged from 1.0 ± 0.1 to 9.3 ± 1.3 adults/ha. Litter sizes (7.1 ± 0.2 young/litter) and numbers of litters (1.5-2.0 litters/female/year) were similar in each habitat. Monthly adult breeding-season survival in open-water habitats was 0.86 ± 0.06 in 1981 and 0.82 in 1982. Monthly summer survival for juveniles throughout Pool Nine was 0.80 in 1981 and 0.87 in 1982. The monthly overwinter survival rate in both habitats was 0.82 ± 0.04. Harvest rate averaged 0.79 during the 1981 trapping season; 0.92 in open-water habitats compared with 0.47 in backwaters. Harvest mortality was largely compensatory, suggesting that lower backwater population densities were the result of past overharvest decline and directly related to longterm habitat degradation.

Small mammal populations were compared on unmined rangeland and reclaimed coal surface-mined land reseeded 2 years and 3-5 years previously. Eight species of small mammals were present on the 3-5-year-old reclaimed areas compared with six on 2-year-old areas and five on unmined rangeland. The masked shrew (Sorex cinereus) and northern grasshopper mouse (ONychomys leucogaster) were captured almost exclusively on 3-5-year-old reclamied land and unmined rangeland. Deer mice (Peromyscus maniculatus) dominated the community on all reclaimed areas in terms of density (13.8 ± 1.2/ha) and biomass (240.1 ± 109.1 g/ha). They composed 93.6 ± 1.9% of all small mammals caputed on 2-year-old areas and 83.2 ± 1.1% of those captured on 3-5-year-old areas. Variation in their density paralleled variations in proportions of juveniles on the recolonized areas. Deer mice also were most abundant on unmined rangeland in terms of density, but thirteen-lined groudn squirrels (Spermophilus tridecemlineatus) dominated in terms of biomass. Density of recolonizing deer mice stabilized within 2 years after reclamation. After 2 years, total small mammal density remained relatively constant, and diversity of the community increased.

We describe a simulation model that estimates the energy and protein demand, body weight fluctuations, and population density changes of black-tailed jack rabbits (Lepus californicus), and tests the hypothesis that dense populations are limited by forage resources. Using field and literature values for energy and nitrogen requirements for maintenance, growth, and reproduction, we estimated the demand for forage resources by fluctuating jack rabbit populations in Curlew Valley, Utah. The model produced body weight dynamics within error estimates of measured body weights of both sexes for 90% of an annual cycle. Simulated daily energy requirements (161.2 kcal/kg/day) and daily nitrogen requirements (353.6 mg/kg/day) were within 10% of reported empirical values. Sensitivity analysis of model parameters and variables suggests that output is most sensitive to variations in such inputs as digestive efficiency and maximum consumption rate. Simulated populations, at peak densities, consumed <1% of available forage resources and there was no significant difference at different population levels in simulated energy or protein difference state. We conclude that the observed declines from population peaks, characteristic of this oscillatory population, must be caused by ecological mechanisms other than food resource depletion.

A compilation of global soil carbon data from field experiments provides empirical evidence that warming-induced net losses of soil carbon could accelerate climate change. Planetary warming and soil carbon loss Warming can enhance the exchange of carbon between the soil and the atmosphere, but there is no consensus on the direction or magnitude of warming-induced changes in soil carbon. This paper presents a comprehensive analysis of warming-induced changes in soil carbon stocks based on data from field experiments across North America, Europe and Asia. The authors find that the effects of warming are contingent upon the size of the initial soil carbon stock, with considerable carbon losses occurring in high-latitude areas. Extrapolation of their findings to the global scale provides support for the idea that rising temperatures will stimulate the net loss of soil carbon to the atmosphere, driving a positive land carbon–climate feedback that could accelerate climate change. The majority of the Earth’s terrestrial carbon is stored in the soil. If anthropogenic warming stimulates the loss of this carbon to the atmosphere, it could drive further planetary warming 1 , 2 , 3 , 4 . Despite evidence that warming enhances carbon fluxes to and from the soil 5 , 6 , the net global balance between these responses remains uncertain. Here we present a comprehensive analysis of warming-induced changes in soil carbon stocks by assembling data from 49 field experiments located across North America, Europe and Asia. We find that the effects of warming are contingent on the size of the initial soil carbon stock, with considerable losses occurring in high-latitude areas. By extrapolating this empirical relationship to the global scale, we provide estimates of soil carbon sensitivity to warming that may help to constrain Earth system model projections. Our empirical relationship suggests that global soil carbon stocks in the upper soil horizons will fall by 30 ± 30 petagrams of carbon to 203 ± 161 petagrams of carbon under one degree of warming, depending on the rate at which the effects of warming are realized. Under the conservative assumption that the response of soil carbon to warming occurs within a year, a business-as-usual climate scenario would drive the loss of 55 ± 50 petagrams of carbon from the upper soil horizons by 2050. This value is around 12–17 per cent of the expected anthropogenic emissions over this period 7 , 8 . Despite the considerable uncertainty in our estimates, the direction of the global soil carbon response is consistent across all scenarios. This provides strong empirical support for the idea that rising temperatures will stimulate the net loss of soil carbon to the atmosphere, driving a positive land carbon–climate feedback that could accelerate climate change.

The mechanical and physiological bases for root growth against high mechanical impedance are reviewed. The best estimates of maximum axial root growth pressure (σmax) in completely impeded pea roots appear to be from 0.5 to 0.6 MPa, which results from a turgor pressure of about 0.8 MPa. When roots are incompletely impeded, a range of responses has been reported. Roots do not change elongation rate in a simple mechanical way in response to changes in mechanical impedance. Instead, ethylene might play a key role in mediating an increase in root diameter and a decrease in elongation rate. These changes persist for some hours or days after impedance is removed. Differences between species in their ability to penetrate strong soil layers are not related to differences in σmax, but appear to be due to differences in root diameter. In rice, differences between cultivars in the ability of their roots to penetrate strong wax layers are not related to their elongation rates through uniformly strong media. Differences between species or cultivars in their ability to penetrate strong layers may be due to differences in the tendency of roots to deflect or buckle when they grow from a weak to a strong environment.

Shoot growth in wheat is sensitive to high soil strength, but as high strength and drying tend to occur together it has proved difficult to separate the effects of water stress and mechanical impedance. The results of two field experiments in 2003 and 2004, where soil strength was manipulated by compaction and irrigation, demonstrated that the yield of wheat (Triticum aestivum L.) was sensitive to physical stress in the root zone. We obtained linear relationships between yield and soil strength and between yield and accumulated soil moisture data (accumulation analogous to thermal time), with similar slopes for both seasons. We were unable to detect root-sourced signals of xylem-sap ABA concentration, despite changes in stomatal conductance. When mechanical impedance and matric potential were varied independently in controlled environments, the growth of wheat was sensitive to mechanical impedance, but not to small changes in matric potential. While the response of stomatal conductance to soil drying in the field could be interpreted as evidence of hydraulic signalling, we suggest that the role of high soil strength, in limiting growth rates on moderately dry soil, requires further research.