Erratum

Naturwissenschaften Aktuell     

In situ measurements of nitrate leaching implicate poor nitrogen and irrigation management on sandy soils

Minimizing the risk of nitrate contamination along the waterways of the U.S. Great Plains is essential to continued irrigated corn production and quality water supplies. The objectives of this study were to quantify nitrate (NO(3)) leaching for irrigated sandy soils (Pratt loamy fine sand [sandy, mixed, mesic Lamellic Haplustalfs]) and to evaluate the effects of N fertilizer and irrigation management strategies on NO(3) leaching in irrigated corn. Two irrigation schedules (1.0x and 1.25x optimum) were combined with six N fertilizer treatments broadcast as NH(4)NO(3) (kg N ha(-1)): 300 and 250 applied pre-plant; 250 applied pre-plant and sidedress; 185 applied pre-plant and sidedress; 125 applied pre-plant and sidedress; and 0. Porous-cup tensiometers and solution samplers were installed in each of the four highest N treatments. Soil solution samples were collected during the 2001 and 2002 growing seasons. Maximum corn grain yield was achieved with 125 or 185 kg N ha(-1), regardless of the irrigation schedule (IS). The 1.25x IS exacerbated the amount of NO(3) leached below the 152-cm depth in the preplant N treatments, with a mean of 146 kg N ha(-1) for the 250 and 300 kg N preplant applications compared with 12 kg N ha(-1) for the same N treatments and 1.0x IS. With 185 kg N ha(-1), the 1.25x IS treatment resulted in 74 kg N ha(-1) leached compared with 10 kg N ha(-1) for the 1.0x IS. Appropriate irrigation scheduling and N fertilizer rates are essential to improving N management practices on these sandy soils.     

Quantifying population declines based on presence‐only records for red‐list assessments

Accurate trend estimates are necessary for understanding which species are declining and which are most in need of conservation action. Imperfect species detection may result in unreliable trend estimates because this may lead to the overestimation of declines. Because many management decisions are based on population trend estimates, such biases could have severe consequences for conservation policy. We used an occupancy‐modeling framework to estimate detectability and calculate nationwide population trends for 14 Swiss amphibian species both accounting for and ignoring imperfect detection. Through the application of International Union for Conservation of Nature Red List criteria to the different trend estimates, we assessed whether ignoring imperfect detection could affect conservation policy. Imperfect detection occurred for all species and detection varied substantially among species, which led to the overestimation of population declines when detectability was ignored. Consequently, accounting for imperfect detection lowered the red‐list risk category for 5 of the 14 species assessed. We demonstrate that failing to consider species detectability can have serious consequences for species management and that occupancy modeling provides a flexible framework to account for observation bias and improve assessments of conservation status. A problem inherent to most historical records is that they contain presence‐only data from which only relative declines can be estimated. A move toward the routine recording of nonobservation and absence data is essential if conservation practitioners are to move beyond this toward accurate population trend estimation.