Responsive in-season nitrogen management for cereals

Current nitrogen (N) management strategies for worldwide cereal production systems are characterized by low N use efficiency (NUE), environmental contamination, and considerable ongoing debate regarding what can be done to improve N fertilizer management. Development of innovative strategies that improve NUE and minimize off-field losses is crucial to sustaining cereal-based farming. In this paper, we review the major managerial causes for low NUE, including (1) poor synchrony between fertilizer N and crop demand, (2) uniform field applications to spatially variable landscapes that commonly vary in crop N need, and (3) failure to account for temporally variable influences on crop N needs. Poor synchronization is mainly due to large pre-plant applications of fertilizer N, resulting in high levels of inorganic soil N long before rapid crop uptake occurs. Uniform applications within fields discount the fact that N supplies from the soil, crop N uptake, and crop response are spatially variable. Current N management decisions also overlook year-to-year weather variations and sometimes fail to account for soil N mineralized in warm, wet years, ignoring indigenous N supply. The key to optimizing tradeoffs amongst yield, profit, and environmental protection is to achieve synchrony between N supply and crop demand, while accounting for spatial and temporal variability in soil N. While some have advocated a soil-based management zones (MZ) approach as a means to direct variable N applications and improve NUE, this method disregards yearly variation in weather. Thus, it seems unlikely that the soil-based MZ concept alone will be adequate for variable application of crop N inputs. Alternatively, we propose utilizing emerging computer and electronic technologies that focus on the plant to assess N status and direct in-season spatially variable N applications. Several of these technologies are reviewed and discussed. One technology showing promise is ground-based active-light reflectance measurements converted to NDVI or other similar indices. Preliminary research shows this approach addresses the issue of spatial variability and is accomplished at a time within the growing season so that N inputs are synchronized to match crop N uptake. We suggest this approach may be improved by first delineating a field into MZ using soil or other field properties to modify the decision associated with ground-based reflectance sensing. While additional adaptive research is needed to refine these newer technologies and subsequent N management decisions, preliminary results are encouraging.We expect N use efficiency can be greatly enhanced using this plant-based responsive strategy for N management in cereals

Modelling the impact of toxic and disturbance stress on white-tailed eagle (Haliaeetus albicilla) populations

Several studies have related breeding success and survival of sea eagles to toxic or non-toxic stress separately. In the present investigation, we analysed single and combined impacts of both toxic and disturbance stress on populations of white-tailed eagle (Haliaeetus albicilla), using an analytical single-species model. Chemical and eco(toxico)logical data reported from laboratory and field studies were used to parameterise and validate the model. The model was applied to assess the impact of ∑PCB, DDE and disturbance stress on the white-tailed eagle population in The Netherlands. Disturbance stress was incorporated through a 1.6% reduction in survival and a 10–50% reduction in reproduction. ∑PCB contamination from 1950 up to 1987 was found to be too high to allow the return of white-tailed eagle as a breeding species in that period. ∑PCB and population trends simulated for 2006–2050 suggest that future population growth is still reduced. Disturbance stress resulted in a reduced population development. The combination of both toxic and disturbance stress varied from a slower population development to a catastrophical reduction in population size, where the main cause was attributed to the reduction in reproduction of 50%. Application of the model was restricted by the current lack of quantitative dose–response relationships between non-toxic stress and survival and reproduction. Nevertheless, the model provides a first step towards integrating and quantifying the impacts of multiple stressors on white-tailed eagle populations