TY - JOUR A1 - Bürger, Gerd T1 - A conundrum of trends BT - comment on a paper by Lischeid et al. (2021) JF - Journal of hydrology N2 - This comment is meant to reiterate two warnings: One applies to the uncritical use of ready-made (openly available) program packages, and one to the estimation of trends in serially correlated time series. Both warnings apply to the recent publication of Lischeid et al. about lake-level trends in Germany. KW - Linear trends KW - Autocorrelation KW - Pre-whitening Y1 - 2022 U6 - https://doi.org/10.1016/j.jhydrol.2022.127745 SN - 0022-1694 SN - 1879-2707 VL - 609 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Baayen, Harald R. A1 - Vasishth, Shravan A1 - Kliegl, Reinhold A1 - Bates, Douglas T1 - The cave of shadows: Addressing the human factor with generalized additive mixed models JF - Journal of memory and language KW - Generalized additive mixed models KW - Within-experiment adaptation KW - Autocorrelation KW - Experimental time series KW - Confirmatory versus exploratory data analysis KW - Model selection Y1 - 2017 U6 - https://doi.org/10.1016/j.jml.2016.11.006 SN - 0749-596X SN - 1096-0821 VL - 94 SP - 206 EP - 234 PB - Elsevier CY - San Diego ER - TY - JOUR A1 - van Schaik, Loes A1 - Palm, Juliane A1 - Klaus, Julian A1 - Zehe, Erwin A1 - Schroeder, Boris T1 - Potential effects of tillage and field borders on within-field spatial distribution patterns of earthworms JF - Biological chemistry N2 - Earthworms play a key role in regulating soil ecosystem functions and services. The small scale variability in earthworm abundance is often found to be very high, which is a problem for representative sampling of earthworm abundance at larger scales. In agricultural fields, soil tillage may influence both the average earthworm abundance as well as the spatial distribution of earthworms. Therefore we studied the abundance and spatial pattern of the different ecological earthworm types, i.e. endogeic, epigeic and anecic earthworms, in four agricultural fields differing in soil tillage (two fields with regular tillage and two fields with conservation tillage) and surrounding land use (other cropped fields or apple orchard and forest). To this aim we sampled earthworms on a total number of 430 plots (50 x 50 cm(2)) using a combination of extraction with mustard solution and hand sorting. The results exhibit large differences in average earthworm abundance between the four fields. Only one of the two fields with conservation tillage had a comparatively very high overall abundance of earthworms. Furthermore, we found a high spatial variability of earthworms within the field scale often exhibiting a patchy distribution. We detected a trend of decreasing earthworm abundances from the field border into the field for different earthworm groups on each of the fields. In three fields with low total earthworm abundance (and only very few epigeic earthworms) there was a short scale autocorrelation with ranges varying strongly for the endogeic earthworms (37.9 m, 62.6 m, and 85.2 m) compared to anecic earthworms (19.8 m, 22.8 m, and 27.4 m). In the field with high abundance, after trend removal, the variogram models for anecic and endogeic earthworms were rejected based on their negative explained variances. On this field, we found only a short scale autocorrelation for the epigeic earthworms with a range of 143 m. Based on these results it seems that ploughing alone cannot explain the differences in abundance and range of autocorrelation found on the four fields. The trend of strongly decreasing earthworm abundance from the field border into the field in the one field with high abundance does indicate that the field border or surrounding land use may also influence the recolonization of fields, but more research is required to provide further evidence for this hypothesis. Due to the very different patterns of earthworm distributions in the fields it remains difficult to recommend an optimal number and distance of samples to obtain a representative earthworm abundance for the field scale. (C) 2016 Elsevier B.V. All rights reserved. KW - Earthworms KW - Spatial distribution KW - Autocorrelation KW - Agricultural fields KW - Soil tillage Y1 - 2016 U6 - https://doi.org/10.1016/j.agee.2016.05.015 SN - 0167-8809 SN - 1873-2305 VL - 228 SP - 82 EP - 90 PB - De Gruyter CY - Berlin ER - TY - JOUR A1 - Klemm, Juliane A1 - Herzschuh, Ulrike A1 - Pisaric, Michael F. J. A1 - Telford, Richard J. A1 - Heim, Birgit A1 - Pestryakova, Luidmila Agafyevna T1 - A pollen-climate transfer function from the tundra and taiga vegetation in Arctic Siberia and its applicability to a Holocene record JF - Palaeogeography, palaeoclimatology, palaeoecology : an international journal for the geo-sciences N2 - This study aims to establish, evaluate, and apply a modern pollen-climate transfer function from the transition zone between arctic tundra and light-needled taiga in Arctic Siberia. Lacustrine samples (n = 96) from the northern Siberian lowlands of Yakutia were collected along four north-to-south transects crossing the arctic forest line. Samples span a broad temperature and precipitation gradient (mean July temperature, T-July: 7.5-18.7 degrees C; mean annual precipitation, P-ann: 114-315 mm/yr). Redundancy analyses are used to examine the relationship between the modern pollen signal and corresponding vegetation types and climate. Performance of transfer functions for T-July and P-ann were cross-validated and tested for spatial autocorrelation effects. The root mean square errors of prediction are 1.67 degrees C for T-July and 40 mm/yr for P-ann. A climate reconstruction based on fossil pollen spectra from a Siberian Arctic lake sediment core spanning the Holocene yielded cold conditions for the Late Glacial (1-2 degrees C below present T-July). Warm and moist conditions were reconstructed for the early to mid Holocene (2 degrees C higher T-July than present), and climate conditions similar to modern ones were reconstructed for the last 4000 years. In conclusion, our modern pollen data set fills the gap of existing regional calibration sets with regard to the underrepresented Siberian tundra-taiga transition zone. The Holocene climate reconstruction indicates that the temperature deviation from modern values was only moderate despite the assumed Arctic sensitivity to present climate change. KW - Mean July temperature KW - Reconstruction KW - Weighted-average partial least squares KW - Autocorrelation KW - Yakutia Y1 - 2013 U6 - https://doi.org/10.1016/j.palaeo.2013.06.033 SN - 0031-0182 SN - 1872-616X VL - 386 SP - 702 EP - 713 PB - Elsevier CY - Amsterdam ER - TY - BOOK A1 - Strohe, Hans Gerhard T1 - Time series analysis BT - textbook for students of economics and business administration ; [part 2] KW - Zeitreihenanalyse KW - Stationärer Prozess KW - Spektraldichte KW - Autokorrelation KW - Time Series Analysis KW - Stationary Stochastic Processes KW - ARMA Processes KW - Autocorrelation KW - Spectral Density KW - ARIMA Models KW - ARCH KW - GARCH Y1 - 2004 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-6601 ER -