Detecting dominant landscape objects through multiple scales: An integration of object-specific methods and watershed segmentation

Complex systems, such as landscapes, are composed of different critical levels of organization where interactions are stronger within levels than among levels, and where each level operates at relatively distinct time and spatial scales. To detect significant features occurring at specific levels of organization in a landscape, two steps are required. First, a multiscale dataset must be generated from which these features can emerge. Second, a procedure must be developed to delineate individual image-objects and identify them as they change through scale. In this paper, we introduce a framework for the automatic definition of multiscale landscape features using object-specific techniques and marker-controlled watershed segmentation. By applying this framework to a high-resolution satellite scene, image-objects of varying size and shape can be delineated and studied individually at their characteristic scale of expression. This framework involves three main steps: 1) multiscale dataset generation using an object-specific analysis and upscaling technique, 2) marker-controlled watershed transformation to automatically delineate individual image-objects as they evolve through scale, and 3) landscape feature identification to assess the significance of these image-objects in terms of meaningful landscape features. This study was conducted on an agro-forested region in southwest Quebec, Canada, using IKONOS satellite data. Results show that image-objects tend to persist within one or two scale domains, and then suddenly disappear at the next, while new image-objects emerge at coarser scale domains. We suggest that these patterns are associated to sudden shifts in the entire image structure at certain scale domains, which may correspond to critical landscape thresholds.This revised version was published online in May 2005 with corrections to the Cover Date.     

Assessment of groundwater quality and its variations in the capture zone of a pumping well in an agricultural area

Agricultural activities are frequently associated with water contamination. The spreading and storage of fertilizers, for instance, may result in groundwater contamination due to pollutants leaching into an aquifer. Nitrates and fecal bacteria are two important contaminants associated with agriculture. Thus, the development of efficient strategies for groundwater protection in agricultural areas requires an assessment of these two contaminants. Given this perspective, groundwater quality monitoring was carried out over the whole capture zone of a municipal well located in an agricultural area in the St.-Lawrence Lowlands in Québec. Thirty-eight piezometers were installed within the roughly 2 km² capture area of the well to measure physico-chemical parameters such as major ions, field measured parameters (pH, electrical conductivity, dissolved oxygen, water level, temperature), and isotopic ratios, bacteriological parameters (Heterotrophic Plate Count—HPC, enterococci, total coliforms, Escherichia coli) and their variations in space and time. Groundwater was sampled from the pumping well and the piezometers during 25 field campaigns in 2005, 2006 and 2007. The results demonstrate the impact of agricultural activities on nitrate contamination. They indicate high spatial and temporal variations in nitrate concentrations, from 6 to 125 mgNO₃⁻/L within the capture area, with 40% of the samples exceeding the Québec drinking water limit of 45 mgNO₃⁻/L. Nitrate pollution in the municipal well exceeded 45 mgNO₃⁻/L during 2005, but no bacteriological contamination was observed. The results also show a high variability of nitrate concentration with depth within the capture zone. Electrical conductivity appears as a good indicator of the presence of nitrate and calcium ions in this capture zone. Correlations between nitrate, calcium and chloride suggest that these ions come from the same source of fertilizer. Nitrate isotopic composition suggests that nitrate in groundwater originates from both chemical and organic fertilizers. The bacteriological results show that the extracted volume of water during sampling of a piezometer has a significant impact on the bacteria count. The variability of bacteriological pollution is important in space and time, showing a higher contamination during summer. Only 2% of the raw water samples exhibit contamination exceeding the drinking water standard for treated water. Total coliforms seem to be a good precursor of E. coli or enterococci contamination. Globally, the physico-chemical and bacteriological groundwater quality within the studied capture area and the pumping well shows contamination by nitrates, but low contamination levels by fecal bacteria.     

Vegetation Composition and Succession of Abandoned Farmland: Effects of Ecological,Historical and Spatial Factors

In North America, as well as in Europe, the mechanization and the modernization of the agricultural activities had strongly modified the agricultural landscapes. Originating from these transformations of the agricultural environment, abandoned farmlands remain poorly known environments. A holistic approach, including the analysis of ecological, historical and spatial factors, is used in order to understand the dynamics of these environments created by agricultural abandonment in southwestern Québec (Canada). The analysis of 36 abandoned farmlands in the study area reveals the existence of two ecological groups. The first ecological group is composed by abandoned farmlands originating from pasture and at the moment dominated by a spiny shrub vegetation. The second ecological group includes past cultivated field at the moment dominated by either hydric herbaceous and shrub vegetation. Abiotic ecological variables such as slope, surface stoniness, canopy opening and soil pH, as well as land-use history, and age of the abandoned farmlands, are major factors explaining the current state of abandoned farmlands. Succession vector analysis reveals a strong differentiation among abandoned farmlands as to their tree species regeneration. Possible management alternatives, such as reforestation, are proposed in order to integrate those new environments to the modern agricultural landscape.     

Positive regulation of T cell activation and integrin adhesion by the adapter Fyb/Slap

The molecular adapter Fyb/Slap regulates signaling downstream of the T cell receptor (TCR), but whether it plays a positive or negative role is controversial. We demonstrate that Fyb/Slap-deficient T cells exhibit defective proliferation and cytokine production in response to TCR stimulation. Fyb/Slap is also required in vivo for T cell-dependent immune responses. Functionally, Fyb/Slap has no apparent role in the activation of known TCR signaling pathways, F-actin polymerization, or TCR clustering. Rather, Fyb/Slap regulates TCR-induced integrin clustering and adhesion. Thus, Fyb/Slap is the first molecular adapter to be identified that couples TCR stimulation to the avidity modulation of integrins governing T cell adhesion.     

Is it possible to forecast the grain quality and yield of different varieties of winter wheat from Minolta SPAD meter measurements?

To optimize wheat segregation for the various markets, it is necessary to add to genotype segregation, a prediction before harvest of the values of yield and grain protein concentration (GPC) for the different fields of the collecting area. Different tools allowing a prediction of crop production exist. Among them, the evaluation of nitrogen concentration by a chlorophyll meter (Soil–Plant Analysis Development (SPAD) readings), classically used to adapt the nitrogen fertilizer application, has been used in few works to foresee grain yield and grain protein concentration. But the relationships between N crop status and SPAD measurements varies among varieties and this genotypic effect has rarely been incorporated in models of forecasting grain quality.

This paper compares several models to forecast yield, nitrogen uptake in grain (NUG) and grain protein concentration from trials carried out in 2001 and 2002 at the INRA experiment station of Grignon (West of Paris). Trials crossed nine varieties by four (2002) or five (2001) nitrogen rates. Input variables of those models are mainly chlorophyll meter measurements (SPAD) on the penultimate leaf at GS65 and on the flag leaf at GS71 Zadoks growth stages and ear number per square meter (NE).

A square root model of yield based on NE × SPAD gave the best fit (RMSE = 0.6 t ha⁻¹ for both stages) if considering three different groups of genotypes. Based on the same variable, NE × SPAD, a quadratic model for NUG without significant effect of genotypes gave the best fit (RMSE, between 21 and 30 kg ha⁻¹ depending of the growth stage). And, for GPC, considering the same three groups of genotypes, the slope of the linear model with the ratio of predicted grain nitrogen concentration to predicted yield, is the same at both stages and very close to the standard value used to calculate protein concentration from nitrogen concentration (5.7), but the predictive quality of the model is more than 10% higher at GS71 (R² of 0.77) than at flowering (R² of 0.64). Finally, the sensibility of the models to delay in the stage of measurement is discussed.     

Effect of reproductive disorders and parity on repeat breeder status and culling of dairy cows in Quebec

This study quantified the effect of peripartum reproductive disorders and parity on repeat breeder status and involuntary culling of dairy cows. Reproductive data of 418 383 lactations were taken from a computerized databank of health records for dairy cows. A logistic regression model was used with dystocia, retained placenta (RP), metritis complex, and parity as fixed effect risk factors and herd entered as the random effect. Of the peripartum problems studied, dystocia had the greatest effect on future fertility. Dystocia increased the odds of a cow being a repeat breeder by 44% [odds ratio (OR): 1.44; confidence interval (CI): 1.37 to 1.51]. Compared to first-parity cows, cows in second, third, and fourth parities had significantly higher odds of being a repeat breeder: 18% (OR: 1.18; CI: 1.16 to 1.20); 24% (OR: 1.24; CI: 1.21 to 1.26); and 42% (OR: 1.42; CI: 1.39 to 1.45), respectively. The odds for second-, third-, or fourth-parity repeat breeders being culled were 24% (OR: 1.24; CI: 1.20 to 1.28); 39% (OR: 1.39; CI: 1.35 to 1.43); and 67% (OR: 1.67; CI: 1.62 to 1.71) respectively, while peripartum reproductive problems had less of an effect.     

Environmental,historical, and contextual determinants of vegetation cover: a landscape perspective

We formulated and tested models of relationships among determinants of vegetation cover in two agroforested landscapes of eastern North America (Haut Saint-Laurent, Quebec, Canada) that differed by the spatial arrangement of their geomorphic features and intensity of agricultural activities. Our landscape model compared the woody plots of each landscape in terms of the relative influence of environmental attributes, land use history (1958 – 1997), and spatial context (i.e., proximity of similar or contrasting land cover). Our vegetation model evaluated the relative contribution of the same sets of variables to the distributions of herbs, trees, and shrubs. Relationships were assessed using partial Mantel tests and path analyses. Significant environmental and contextual differences were found between the vegetation plots of the two landscapes, but disturbance history was similar. Our vegetation model confirms the dominant effect of historical factors on vegetation patterns. Whereas land-use history overrides environmental and contextual control for trees, herbaceous and shrub species are more sensitive to environmental conditions. Context is determinant only for understory species in older, less-disturbed plots. Results are discussed in relevance to vegetation dynamics in a landscape perspective that integrates interactions between environmental and human influences.     

Age-related susceptibility of strawberry leaves and berries to infection by Podosphaera aphanis

Powdery mildew, caused by Podosphaera aphanis, is a major disease of strawberry worldwide. The importance of the disease varies with production system (June bearing vs day neutral) which could be explained in part by the concurrent presence of susceptible leaves or berries and abundant airborne inoculum. Age-related susceptibility was studied by inoculating strawberry leaves and berries at different growth stages of the June bearing cultivar Jewel and the day neutral cultivar Seascape. On eight occasions in 2007, five plants of each cultivar were inoculated with dry conidia using a settling tower. There was a significant effect of leaf and berry growth stage on the susceptibility, which decreased exponentially as leaves or berries aged to reach almost zero when the leaves were completely expanded or the berries at the pink stage at the time of inoculation. The proportion of maximum mildew severity as a function of leaf or berry growth stage was predicted using non-parametric regression (R² = 0.96–0.97). The predicted values were validated with data collected in fields or tunnels naturally infected by P. aphanis. There was a linear relation between predicted and observed proportion of maximum mildew severity (R² = 0.95–0.99). The results of this study showed that timing fungicide sprays based on periods of high leaf and berry susceptibility should greatly improve management of strawberry powdery mildew.