Cumulative effects of forestry on habitat use by gray wolf (<Emphasis Type="Italic">Canis lupus</Emphasis>) in the boreal forest

Forest harvesting involves the creation of roads and cutblocks, both of which can influence animal habitat use. We evaluated the cumulative effects of forestry on habitat selection by six packs of gray wolf (Canis lupus) widely distributed in Quebec’s boreal forest. Resource selection functions were used to evaluate cumulative effects at two levels. First, we studied how the response of wolves to roads and cutblocks varied within their home range (HR level) as a function of the local abundance of these habitat features. Second, we assessed whether differences in the response to roads and cutblocks observed among packs (inter-HR level) could be explained by variations in their average abundance among individual home ranges. At the HR level, we found that cumulative effects shaped habitat selection of wolves, and the nature of the effects varied during the year. For example, we detected a decrease in the selection of roads following an increase in local road density during the rendez-vous and the nomadic periods, but not during the denning period. At the inter-HR level, we found a functional response to logging activity only during the denning period. Packs with home ranges characterized by a larger proportion of recent cutblocks selected these cutblocks more strongly. We conclude that cumulative effects of logging activities occur at multiple levels, and these effects can have profound effects on habitat use by wolves, thereby influencing spatial predator–prey dynamics. Wildlife conservation and management in boreal ecosystems should thus account for cumulative impacts of anthropogenic features on animal distribution.     

Chemical control of the European tarnished plant bug, Lygus rugulipennis, on strawberry in the UK

European tarnished plant bug, Lygus rugulipennis, is a serious pest on late season strawberries in the UK. Feeding by the pest on the developing fruits causes severe malformation, and over 50% of fruit may be downgraded as a result of capsid feeding in unsprayed crops. A range of compounds was tested against the pest over two years at East Malling Research. In 2008 experiments were conducted on weed plots with high L. rugulipennis populations, and in 2009 were conducted on an everbearer strawberry planting. The 2008 experiments showed that etoxazole had no effect on L. rugulipennis and that although flonicamid and indoxacarb significantly reduced populations they were not as effective as thiacloprid, either with or without a surfactant, or acetamiprid. In the 2009 experiment on strawberry thiacloprid + surfactant, applied twice, was more effective than this treatment applied once, which in turn was more effective than thiacloprid alone. In both years the most effective treatment was the pyrethroid bifenthrin. There was no suggestion that different developmental stages of the pest were more susceptible to the tested insecticides. Thus there was no evidence to suggest that timing applications against specific life stages would significantly improve pest control.     

Site-specific early season potato yield forecast by neural network in Eastern Canada

Deterministic potato (Solanum tuberosum L.) growth models hardly rely on driving seasonal field variables that directly characterize spatial variation of plant growth. For example, the SUBSTOR model computes the leaf area index (LAI) as an auxiliary variable from meteorological conditions and soil properties. Empirical models may account for seasonal LAI functions and accurately predict potato yield. The objective was to evaluate multiple linear regression (MLR) and neural networks (NN) as predictive models of potato yield. Using data from several replicated on-farm experiments conducted over 3 years, model performance was evaluated for their capacity to forecast tuber yields 9, 10 and 11 weeks before harvest compared to SUBSTOR. A 3-input NN using LAI functions and cumulative rainfall yielded the most accurate estimations and forecasts of tuber yields. This NN showed that tuber yield of contrasting zones was mostly a function of meteorological conditions prevailing during the first 5–8 weeks after planting. Subsequent development of tubers was essentially controlled by biomass allocation to tubers. The NN models were more coherent than MLR and SUBSTOR for two reasons: (1) the use of seasonal LAI directly as input rather than computed as an auxiliary variable and (2) the non-linearity of the modeling process resulting in more accurate estimation of the temporal discontinuities of potato tuber growth. This model showed potential for application in precision agriculture by accounting for temporal and spatial real-time climatic and crop data.     

Issues related to the detection of boundaries

Ecotones are inherent features of landscapes, transitional zones, and play more than one functional role in ecosystem dynamics. The delineation of ecotones and environmental boundaries is therefore an important step in land-use management planning. The delineation of ecotones depends on the phenomenon of interest and the statistical methods used as well as the associated spatial and temporal resolution of the data available. In the context of delineating wetland and riparian ecosystems, various data types (field data, remotely sensed data) can be used to delineate ecotones. Methodological issues related to their detection need to be addressed, however, so that their management and monitoring can yield useful information about their dynamics and functional roles in ecosystems. The aim of this paper is to review boundary detection methods. Because the most appropriate methods to detect and characterize boundaries depend of the spatial resolution and the measurement type of the data, a wide range of approaches are presented: GIS, remote sensing and statistical ones.     

Assessing Spatial Uncertainty Associated with Forest Fire Boundary Delineation

Uncertainty in managing forested landscapes arises from many sources, including complexities inherent in forest ecosystems and their disturbance processes. However, gaining knowledge about forested ecosystems at the landscape level is often impeded by limitations in collecting comprehensive, representative, as well as accurate data sets. Historical reference data sets about past disturbances are also mostly lacking. In the case of ground fires, however, records of past fires can be obtained by analyzing fire scars using dendrochronology. While the temporal series of disturbance can be determined, there is still uncertainty about the spatial limits of individual forest surface fires. Here, we investigate how a patch-based method (fuzzy set membership) and a boundary-based uncertainty method (boundary membership) can help determine the spatial uncertainty related to forest fire events and their boundary locations. We compare these methods using fire scar data from ponderosa pine (Pinus ponderosa) and Douglas-fir (Pseudotsuga menziesii) sampled at 33 1-ha plots in a 1500-ha study area within the Stein River watershed (British Columbia). Patch-based fire maps, using multiple constraints, were derived for years 1785–1937. We compared the resulting total fire event maps with the boundary-based method, finding that depending on values chosen for the patch-based method, negative correlation was present (though very modest: r = − 0.1, p ≤ 0.05) between some maps. However, significant positive correlation between maps (though again modest: r = 0.22, p ≤ 0.05) was found under the least constrained patch-based methods, suggesting that fire patches are counted more than once in riparian zones. Our results suggest that these two methods provide complementary information about historical fire size and spatial limits. Quantifying spatial uncertainty about fire size and fire boundary location using a boundary membership method can contribute to not only understanding past fire regimes but also to providing better estimates of area burned.     

Relative expression of matrix metalloproteinase-2 and -9 in synovial fluid from healthy calves and calves with experimentally induced septic arthritis

OBJECTIVE: To identify changes over time in relative expression of matrix metalloproteinase-2 (MMP-2) and -9 (MMP-9) in synovial fluid from healthy calves and calves with experimentally induced septic arthritis. ANIMALS: 12 Holstein calves. PROCEDURES: In 7 calves, Escherichia coli was injected in the right tarsal joint on day 1. Joint lavage was performed on day 2, and calves were treated with ceftiofur from days 2 through 21. Synovial fluid samples were collected on days 1 (before inoculation), 2 (before joint lavage), 3, 4, 8, 12, 16, 20, and 24. In the remaining 5 calves, joint lavage was performed on day 2 and synovial fluid samples were collected from the left tarsal joint. Relative expression of MMP-2 and MMP-9 was determined by means of gel zymography. RESULTS: On day 1, MMP-2 was detected in all synovial fluid samples but MMP-9 was not detected. In calves with septic arthritis, values for relative expression of MMP-9 monomer and dimer were significantly increased on days 2 through 20 and days 2 through 24, respectively, and relative expression of MMP-2 was significantly increased on days 3 through 20. There were significant linear associations between relative expression of the monomer and dimer forms of MMP-9 and between neutrophil count and relative expression of the MMP-9 monomer and dimer forms. CONCLUSIONS AND CLINICAL RELEVANCE: Results indicated that relative expression of MMP-9 and MMP-2 increased in synovial fluid from calves with experimentally induced septic arthritis, with relative expression remaining high for several days after infection.     

Host functional connectivity and the spread potential of Lyme disease

Context

In the ecology of Lyme disease emergence, it remains unclear to what extent spread of the tick vector (Ixodes scapularis) and the pathogen (Borrelia burgdorferi) are dependent upon the dispersal of vertebrate hosts in spatially heterogeneous landscapes. Yet, empirical measure of these complex ecologically driven spread processes present conceptual and methodological challenges despite important public health implications.

Objectives

To examine the relationship between landscape characteristics and tick-borne disease spread, we modeled the influence of landscape connectivity for a simplified vertebrate host community (white-footed mouse—Peromyscus leucopus, American robin—Turdus migratorius, white-tailed deer—Odocoileus virginianus) on the potential spread of the tick population compared to the pathogen in a spatially-structured landscape.

Methods

We parameterized a hybrid demographic-dispersal connectivity model by combining a series of reported host dispersal and tick burden estimates with empirically-measured tick abundance and pathogen prevalence sampled from a Lyme-endemic island landscape in Thousand Islands National Park (Ontario, Canada) and simulated several tick- and pathogen-spread scenarios.

Results

The extent of tick spread by mice [amount of reachable habitat (ARH)?=?18.0%] is considerably similar to that of robins (ARH?=?18.7%), while deer support the greatest tick spread extent (ARH?=?82.0%). Infected mice carrying ticks support the highest pathogen spread (ARH?=?19.8%). Short-distance pathogen spread and long-distance tick spread were facilitated by intermediate stepping stone habitat fragments.

Conclusions

We provide evidence that host functional connectivity mediates tick spread differently than pathogen spread, and depends strongly on landscape configuration. Our study therefore emphasizes the importance of landscape spatial heterogeneity on the ecological processes that influence regional tick-borne disease spread.

     

Proliferation of peripheral blood mononuclear cells from healthy piglets after mitogen stimulation as indicators of disease resilience

Disease resilience refers to the productivity of an animal under disease. Given the high biosecurity of pig nucleus herds, traits that can be measured on healthy pigs and that are genetically correlated with disease resilience, that is, genetic indicator traits, offer a strategy to select for disease resilience. Our objective was to evaluate mitogen stimulation assays (MSAs) on peripheral blood mononuclear cells (PBMCs) from young healthy pigs as genetic indicators for disease resilience. Data were from a natural disease challenge in which batches of 60 or 75 naïve Yorkshire × Landrace piglets were introduced every 3 wk into a continuous flow barn that was seeded with multiple diseases. In this environment, disease resilience traits, including growth, treatment, and mortality rates, were recorded on 3,136 pigs that were genotyped with a high-density marker panel. PBMCs from 882 of these pigs from 19 batches were isolated from whole blood collected prior to the disease challenge and stimulated with five mitogens: concanavalin A (ConA), phytohemagglutinin (PHA), pokeweed mitogen (PWM), lipopolysaccharide (LPS), and phorbol myristate acetate (PMA). The proliferation of cells was evaluated at 48, 72, and 96 h and compared with unstimulated samples (rest count). Heritabilities of cell proliferation were estimated using a model with batch as a fixed effect and covariates of entry age; rest count; complete blood count proportions of lymphocytes, monocytes, eosinophils, and basophils; and pen, litter, and animal genetics as random effects. Heritability estimates were highest for response to ConA (0.30 ± 0.09, 0.28 ± 0.10, 0.17 ± 0.10, and 0.25 ±0.10 at 48, 72, and 96 h after stimulation and for area under the curve across the three time points, respectively). Estimates were in a similar range for response to PHA and PMA but low for PWM and LPS. Responses to ConA, PHA, and PMA were moderately genetically correlated with several disease resilience traits and in the expected direction, but individual estimates were not significantly different from zero due to large SEs. In conclusion, although validation is needed, MSAss, in particular based on ConA, show promise as genetic indicator traits for disease resilience.     

Genetic variation among cultivars of red clover (Trifolium pratense L.) detected by RAPD markers amplified from bulk genomic DNA

Summary The use of random amplified polymorphic DNA (RAPD) markers obtained from bulked samples was investigated for cultivar identification in red clover. Pooled samples were examined in order to minimize variation within cultivars. To determine the appropriate number of individuals to include in the bulked samples representing each cultivar, DNA samples from two, three, four, five, ten and twenty individuals were pooled. Twenty was found to be an appropriate number of red clover individuals per bulk in order to amplify only the DNA sequences shared among most individuals in each cultivar. Fourteen 10-mer primers were used to amplify genomic DNA from combined leaf samples of 15 red clover cultivars from European, Japanese and North American origins. A total of 79 amplified products, of which 55 were polymorphic, was obtained. Cultivar-specific bands were observed with 13 primers. The amplification patterns obtained from two primers could distinguish all 15 red clover cultivars. Rogers' genetic distances for all 105 pairwise comparisons were calculated to evaluate relationships among these cultivars. Cluster analysis based on these genetic distances separated these 15 cultivars into three groups, with two of the groups consisting of a single Japanese cultivar each, while the third group included cultivars from European, North American, and Japanese origins.