scholarly journals Reduced Reproductive Success of Western Baltic Herring (Clupea harengus) as a Response to Warming Winters

2021 ◽  
Vol 8 ◽  
Author(s):  
Patrick Polte ◽  
Tomas Gröhsler ◽  
Paul Kotterba ◽  
Lena von Nordheim ◽  
Dorothee Moll ◽  
...  
Keyword(s):  
Time Series ◽  
Reproductive Success ◽  
Adult Population ◽  
Regional Climate ◽  
Clupea Harengus ◽  
Reproductive Capacity ◽  
Distribution Area ◽  
Central Component ◽  
Temperature Threshold ◽  
Larval Hatching

Shallow estuaries, bays, and lagoons are generally considered hot spots of ocean productivity that often adjust rapidly to seasonal variations in atmospheric temperatures. During spring when biological reproductive processes begin in the temperate zones, regional climate variability can be immense and uncovering a non-linear biological response, such as fish recruitment to changing temperature regimes might be challenging. Using herring as a paradigm for a response of coastal spring productivity to regional climate drivers, we demonstrated how the annual timing of spawning periods can significantly affect the reproductive success of spring-spawning herring (Clupea harengus) in the western Baltic Sea. An investigation of spawning phenology in consecutive years indicated a temperature threshold range of 3.5–4.5°C triggering initial spawning in the coastal zone. Based on this finding, we analyzed the timing of larval hatching peaks, larval survival and recruitment to the adult population relative to multi-decadal time-series of seasonal sea-surface temperatures. The results revealed that the late seasonal onset of cold periods the corresponding elongation of the period where larvae hatch from the eggs and early larval hatching peaks significantly reduced larval production in a coastal nursery area and finally lead to a reduced abundance of juveniles in the entire distribution area. Using a combination of field research and time series analysis, we presented precedence for shifting regional winter regimes providing a present-day stressor to reproductive capacity of a central component of the coastal food web.

The location of spawning of Irish Sea herring (Clupea harengus)

2001 ◽  
Vol 81 (4) ◽  
pp. 713-714 ◽  
Author(s):  
Mark Dickey-Collas ◽  
Richard D.M. Nash ◽  
Juan Brown
Keyword(s):  
Time Series ◽  
Clupea Harengus ◽  
Irish Sea ◽  
Spawning Grounds ◽  
Isle Of Man ◽  
The North

Time series of ichthyoplankton surveys targeted at herring larvae describe the distribution of spawning in the north Irish Sea by mapping the occurrence of very young larvae. The surveys suggest, that like other herring stocks, the spawning grounds of Irish Sea herring vary over the years. Currently, spawning at the Mourne location is greatly reduced whereas spawning has occurred at a newly described site to the north of the Isle of Man (off the Point of Ayre). Whilst spawning is dominated by autumn spawners in late September, some spawning occurs through to January.

scholarly journals Stationary and Non-Stationary Frameworks for Extreme Rainfall Time Series in Southern Italy

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1477 ◽  
Author(s):  
Davide De Luca ◽  
Luciano Galasso
Keyword(s):  
Time Series ◽  
Climate Models ◽  
Southern Italy ◽  
Regional Climate ◽  
Data Series ◽  
Rainfall Time Series ◽  
Annual Maximum ◽  
Data Set ◽  
Maximum Rainfall ◽  
Rainfall Events

This study tests stationary and non-stationary approaches for modelling data series of hydro-meteorological variables. Specifically, the authors considered annual maximum rainfall accumulations observed in the Calabria region (southern Italy), and attention was focused on time series characterized by heavy rainfall events which occurred from 1 January 2000 in the study area. This choice is justified by the need to check if the recent rainfall events in the new century can be considered as very different or not from the events occurred in the past. In detail, the whole data set of each considered time series (characterized by a sample size N > 40 data) was analyzed, in order to compare recent and past rainfall accumulations, which occurred in a specific site. All the proposed models were based on the Two-Component Extreme Value (TCEV) probability distribution, which is frequently applied for annual maximum time series in Calabria. The authors discussed the possible sources of uncertainty related to each framework and remarked on the crucial role played by ergodicity. In fact, if the process is assumed to be non-stationary, then ergodicity cannot hold, and thus possible trends should be derived from external sources, different from the time series of interest: in this work, Regional Climate Models’ (RCMs) outputs were considered in order to assess possible trends of TCEV parameters. From the obtained results, it does not seem essential to adopt non-stationary models, as significant trends do not appear from the observed data, due to a relevant number of heavy events which also occurred in the central part of the last century.

scholarly journals Improving runoff estimates from regional climate models: a performance analysis in Spain

2012 ◽  
Vol 16 (6) ◽  
pp. 1709-1723 ◽  
Author(s):  
D. González-Zeas ◽  
L. Garrote ◽  
A. Iglesias ◽  
A. Sordo-Ward
Keyword(s):  
Time Series ◽  
Large Scale ◽  
Climate Models ◽  
Regional Climate ◽  
Aridity Index ◽  
Regional Climate Models ◽  
Hydrologic Model ◽  
Direct Runoff ◽  
Interpolation Methods ◽  
Basin Scale

Abstract. An important step to assess water availability is to have monthly time series representative of the current situation. In this context, a simple methodology is presented for application in large-scale studies in regions where a properly calibrated hydrologic model is not available, using the output variables simulated by regional climate models (RCMs) of the European project PRUDENCE under current climate conditions (period 1961–1990). The methodology compares different interpolation methods and alternatives to generate annual times series that minimise the bias with respect to observed values. The objective is to identify the best alternative to obtain bias-corrected, monthly runoff time series from the output of RCM simulations. This study uses information from 338 basins in Spain that cover the entire mainland territory and whose observed values of natural runoff have been estimated by the distributed hydrological model SIMPA. Four interpolation methods for downscaling runoff to the basin scale from 10 RCMs are compared with emphasis on the ability of each method to reproduce the observed behaviour of this variable. The alternatives consider the use of the direct runoff of the RCMs and the mean annual runoff calculated using five functional forms of the aridity index, defined as the ratio between potential evapotranspiration and precipitation. In addition, the comparison with respect to the global runoff reference of the UNH/GRDC dataset is evaluated, as a contrast of the "best estimator" of current runoff on a large scale. Results show that the bias is minimised using the direct original interpolation method and the best alternative for bias correction of the monthly direct runoff time series of RCMs is the UNH/GRDC dataset, although the formula proposed by Schreiber (1904) also gives good results.

scholarly journals Downscaling future precipitation extremes to urban hydrology scales using a spatio-temporal Neyman–Scott weather generator

2016 ◽  
Vol 20 (4) ◽  
pp. 1387-1403 ◽  
Author(s):  
Hjalte Jomo Danielsen Sørup ◽  
Ole Bøssing Christensen ◽  
Karsten Arnbjerg-Nielsen ◽  
Peter Steen Mikkelsen
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Regional Climate ◽  
Weather Generator ◽  
Spatial Extent ◽  
Urban Hydrology ◽  
Precipitation Time Series ◽  
Spatio Temporal

Abstract. Spatio-temporal precipitation is modelled for urban application at 1 h temporal resolution on a 2 km grid using a spatio-temporal Neyman–Scott rectangular pulses weather generator (WG). Precipitation time series used as input to the WG are obtained from a network of 60 tipping-bucket rain gauges irregularly placed in a 40 km  ×  60 km model domain. The WG simulates precipitation time series that are comparable to the observations with respect to extreme precipitation statistics. The WG is used for downscaling climate change signals from regional climate models (RCMs) with spatial resolutions of 25 and 8 km, respectively. Six different RCM simulation pairs are used to perturb the WG with climate change signals resulting in six very different perturbation schemes. All perturbed WGs result in more extreme precipitation at the sub-daily to multi-daily level and these extremes exhibit a much more realistic spatial pattern than what is observed in RCM precipitation output. The WG seems to correlate increased extreme intensities with an increased spatial extent of the extremes meaning that the climate-change-perturbed extremes have a larger spatial extent than those of the present climate. Overall, the WG produces robust results and is seen as a reliable procedure for downscaling RCM precipitation output for use in urban hydrology.

scholarly journals Sporophytes of the rare liverwort Cephalozia macounii

2013 ◽  
Vol 58 (2) ◽  
pp. 491-494 ◽  
Author(s):  
Sanna Laaka-Lindberg ◽  
Kimmo Syrjänen
Keyword(s):  
Northern Hemisphere ◽  
Critically Endangered ◽  
Reproductive Capacity ◽  
Distribution Area ◽  
Habitats Directive ◽  
Eu Habitats Directive ◽  
The Eu ◽  
Entire Distribution

Abstract The dioicous epixylic liverwort Cephalozia macounii (Aust.) Aust. is rare over its entire distribution area in the Northern Hemisphere. It is protected under the EU Habitats Directive and classified as critically endangered in Finland and Sweden. One reason cited for its rareness and the declining trend in its distribution its poor reproductive capacity. It does not produce asexual gemmae, which in general is common among liverworts. Although female plants with perianths are quite common, the male plants of the species have rarely been seen and sporophytes have not been described until now. In this paper we describe and illustrate the sporophytes of C. macounii on the basis of an old specimen collected in Southern Finland in the 1800s.

Evaluating Forecasting Procedures for Predicting Pacific Herring (Clupea harengus pallasi) Recruitment in British Columbia

1988 ◽  
Vol 45 (6) ◽  
pp. 928-935 ◽  
Author(s):  
M. Stocker ◽  
D. J. Noakes
Keyword(s):  
Time Series ◽  
Clupea Harengus ◽  
Environmental Data ◽  
Forecast Errors ◽  
Pacific Herring ◽  
Time Step ◽  
Absolute Deviation ◽  
Percent Error ◽  
One Step ◽  
Absolute Percent Error

The ability of four forecasting methods to generate one-step-ahead forecasts of Pacific herring (Clupea harengus pillasi) recruitment is considered in this paper. Recruitment time series for five coastal stocks and various environmental time series are employed in the analyses. Information up to and including time t is employed to estimate the parameters of each model used to forecast recruitment in year t + 1. Parameter estimates are then updated after each time step with a total of seven one-step-ahead forecasts being generated by each model for each stock. The forecast errors are compared using the five criteria: (1) root mean squared error, (2) mean absolute deviation, (3) mean absolute percent error, (4) median absolute deviation, and (5) median absolute percent error. The results of the study indicate that time series models may provide better forecasts of recruitment for the Strait of Georgia/Johnstone Strait stocks than the other competing procedures. A Ricker stock–recruitment model that takes into account environmental data appears to produce marginally better forecasts for the Central Coast and Queen Charlotte Island stocks, while all models produced equally good/bad forecasts for the Prince Rupert district stocks.

scholarly journals Imprint of Climate Change on Pan-Arctic Marine Vegetation

2020 ◽  
Vol 7 ◽  
Author(s):  
Dorte Krause-Jensen ◽  
Philippe Archambault ◽  
Jorge Assis ◽  
Inka Bartsch ◽  
Kai Bischof ◽  
...  
Keyword(s):  
Time Series ◽  
Management Strategies ◽  
Open Water ◽  
The Arctic ◽  
Distribution Area ◽  
Arctic Ecosystems ◽  
Migration Rates ◽  
Lack Of Information ◽  
Distribution Limits ◽  
And Storage

The Arctic climate is changing rapidly. The warming and resultant longer open water periods suggest a potential for expansion of marine vegetation along the vast Arctic coastline. We compiled and reviewed the scattered time series on Arctic marine vegetation and explored trends for macroalgae and eelgrass (Zostera marina). We identified a total of 38 sites, distributed between Arctic coastal regions in Alaska, Canada, Greenland, Iceland, Norway/Svalbard, and Russia, having time series extending into the 21st Century. The majority of these exhibited increase in abundance, productivity or species richness, and/or expansion of geographical distribution limits, several time series showed no significant trend. Only four time series displayed a negative trend, largely due to urchin grazing or increased turbidity. Overall, the observations support with medium confidence (i.e., 5–8 in 10 chance of being correct, adopting the IPCC confidence scale) the prediction that macrophytes are expanding in the Arctic. Species distribution modeling was challenged by limited observations and lack of information on substrate, but suggested a current (2000–2017) potential pan-Arctic macroalgal distribution area of 820.000 km2 (145.000 km2 intertidal, 675.000 km2 subtidal), representing an increase of about 30% for subtidal- and 6% for intertidal macroalgae since 1940–1950, and associated polar migration rates averaging 18–23 km decade–1. Adjusting the potential macroalgal distribution area by the fraction of shores represented by cliffs halves the estimate (412,634 km2). Warming and reduced sea ice cover along the Arctic coastlines are expected to stimulate further expansion of marine vegetation from boreal latitudes. The changes likely affect the functioning of coastal Arctic ecosystems because of the vegetation’s roles as habitat, and for carbon and nutrient cycling and storage. We encourage a pan-Arctic science- and management agenda to incorporate marine vegetation into a coherent understanding of Arctic changes by quantifying distribution and status beyond the scattered studies now available to develop sustainable management strategies for these important ecosystems.

scholarly journals A new estimator of heat periods for decadal climate predictions – a complex network approach

2016 ◽  
Vol 23 (4) ◽  
pp. 307-317 ◽  
Author(s):  
Michael Weimer ◽  
Sebastian Mieruch ◽  
Gerd Schädler ◽  
Christoph Kottmeier
Keyword(s):  
Climate Model ◽  
Extreme Values ◽  
Regional Climate ◽  
Low Frequency ◽  
Research Field ◽  
Temperature Threshold ◽  
Fixed Temperature ◽  
Correlation Threshold ◽  
Decadal Climate ◽  
Decadal Predictions

Abstract. Regional decadal predictions have emerged in the past few years as a research field with high application potential, especially for extremes like heat and drought periods. However, up to now the prediction skill of decadal hindcasts, as evaluated with standard methods, is moderate and for extreme values even rarely investigated. In this study, we use hindcast data from a regional climate model (CCLM) for eight regions in Europe and quantify the skill of the model alternatively by constructing time-evolving climate networks and use the network correlation threshold (link strength) as a predictor for heat periods. We show that the skill of the network measure to estimate the low-frequency dynamics of heat periods is superior for decadal predictions with respect to the typical approach of using a fixed temperature threshold for estimating the number of heat periods in Europe.

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