Surplus production, variability, and climate change in the great sardine and anchovy fisheries

2001 ◽  
Vol 58 (9) ◽  
pp. 1891-1903 ◽  
Author(s):  
Larry D Jacobson ◽  
Jose A.A De Oliveira ◽  
Manuel Barange ◽  
Miguel A Cisneros-Mata ◽  
Roberto Félix-Uraga ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Survey Data ◽  
Environmental Changes ◽  
Production Rates ◽  
Surplus Production ◽  
Production Variability ◽  
Stock Biomass ◽  
Show Evidence ◽  
Long Time

We used fishery and survey data to calculate annual surplus production (ASP) and instantaneous surplus production rates (ISPR) for eight anchovy and nine sardine stocks. In addition, we calculated ASP per unit spawning area for six anchovy and six sardine stocks. Median ASP was highest for stocks with highest median biomass (mostly anchovies), and ASP was typically about 16% of stock biomass. ASP was often negative, more frequently for anchovies (36% of years) than for sardines (17% of years). ISPR was less variable for sardines and autocorrelated for longer-lived stocks (mostly sardines). Strong biomass increases tended to be preceded by short, abrupt increases in ISPR, and declines were pronounced when catches exceeded ASP for 5 years or more. The longest "runs" of positive and negative production were 21 and 4 years for sardine off Japan, 10 and 3 years for sardine off California, 8 and 2 years for anchovy off Peru, and 4 and 3 years for anchovy off California. ISPR is more sensitive to environmental changes than catch, biomass, or ASP and appear to be better for identifying environmentally induced regime shifts. Long time series show evidence of density-dependent effects on ASP in anchovies and sardines, but environmentally induced variation appears to dominate.

scholarly journals Photosynthesis, carbon acquisition and primary productivity of phytoplankton: a review dedicated to Colin Reynolds

Hydrobiologia ◽  
2020 ◽  
Vol 848 (1) ◽  
pp. 77-94 ◽  
Author(s):  
Martin T. Dokulil ◽  
Kuimei Qian
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Time Series ◽  
Primary Productivity ◽  
Light Harvesting ◽  
Algal Growth ◽  
Long Time Series ◽  
Methods And Techniques ◽  
Long Time ◽  
The Subject

AbstractThe review intends to give an overview on developments, success, results of photosynthetic research and on primary productivity of algae both freshwater and marine with emphasis on more recent discoveries. Methods and techniques are briefly outlined focusing on latest improvements. Light harvesting and carbon acquisition are evaluated as a basis of regional and global primary productivity and algal growth. Thereafter, long-time series, remote sensing and river production are exemplified and linked to the potential effects of climate change. Lastly, the synthesis seeks to put the life achievements of Colin S. Reynolds into context of the subject review.

A performance evaluation of surplus production models with time-varying intrinsic growth in dynamic ecosystems

2019 ◽  
Vol 76 (12) ◽  
pp. 2245-2255 ◽  
Author(s):  
Geneviève M. Nesslage ◽  
Michael J. Wilberg
Keyword(s):  
Growth Rate ◽  
Time Series ◽  
Survey Data ◽  
Atlantic Menhaden ◽  
Data Sets ◽  
Time Varying ◽  
Intrinsic Growth Rate ◽  
Surplus Production ◽  
Production Models ◽  
Exploitation Rate

We conducted a simulation study to evaluate performance of surplus production models (SPMs) with a time-varying intrinsic growth rate (SPMTVr) for stocks with predation-driven changes in productivity. Data sets were simulated using an age-structured, linked, predator–prey model of Atlantic menhaden (Brevoortia tyrannus), a forage fish native to the Northwest Atlantic, and Atlantic striped bass (Morone saxatilis), its primary predator, with differing time series of fishing mortality on both predator and prey. Simulations generated test data sets for Atlantic menhaden SPMs that included either a static or time-varying intrinsic growth rate parameter. The SPMTVr largely produced more accurate, less variable estimates of exploitation rate and biomass than models with static intrinsic growth. We also applied SPMTVr to empirical Atlantic menhaden catch and survey data for 1964–2016. The SPMTVr fit the survey data well, estimated an intrinsic growth rate time series that mirrored long-term juvenile survey trends, and produced biomass and exploitation rate trends that mirrored a statistical catch-at-age model. The SPMTVr estimated dynamic, maximum sustainable yield (MSY)-based reference points that reflected changing stock productivity.

scholarly journals Potential and Challenges of Harmonizing 40 Years of AVHRR Data: The TIMELINE Experience

2021 ◽  
Vol 13 (18) ◽  
pp. 3618
Author(s):  
Stefan Dech ◽  
Stefanie Holzwarth ◽  
Sarah Asam ◽  
Thorsten Andresen ◽  
Martin Bachmann ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Observation Time ◽  
Sensor Data ◽  
High Temporal Resolution ◽  
Statistical Parameters ◽  
Medium Resolution ◽  
Long Time ◽  
Earth Observation Satellite

Earth Observation satellite data allows for the monitoring of the surface of our planet at predefined intervals covering large areas. However, there is only one medium resolution sensor family in orbit that enables an observation time span of 40 and more years at a daily repeat interval. This is the AVHRR sensor family. If we want to investigate the long-term impacts of climate change on our environment, we can only do so based on data that remains available for several decades. If we then want to investigate processes with respect to climate change, we need very high temporal resolution enabling the generation of long-term time series and the derivation of related statistical parameters such as mean, variability, anomalies, and trends. The challenges to generating a well calibrated and harmonized 40-year-long time series based on AVHRR sensor data flown on 14 different platforms are enormous. However, only extremely thorough pre-processing and harmonization ensures that trends found in the data are real trends and not sensor-related (or other) artefacts. The generation of European-wide time series as a basis for the derivation of a multitude of parameters is therefore an extremely challenging task, the details of which are presented in this paper.

Measuring the effect of land degradation and environmental changes on agricultural production in Somalia with two structural breaks

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abdinur Ali Mohamed ◽  
Ahmed Ibrahim Nageye
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Land Degradation ◽  
Unit Root ◽  
Agricultural Production ◽  
Crop Production ◽  
Structural Breaks ◽  
Environmental Changes ◽  
Content Type ◽  
Long Run

PurposeThe purpose of this study is to measure the effect of land degradation and the environmental changes on agricultural productivity in Somalia, as well as the other factors that affect crop production in Somalia.Design/methodology/approachCobb-Douglas production function assumes crop production as a dependent variable and land degradation, labor, capital, fertilizer and climate change as the explanatory variables. In this study time-series data (1962–2017) collected from the Food and Agriculture Organization and World Development Indicators were used. The unit root of the data was examined using Ng-Perron and the Lee-Strazicich methods to explore the unit root property of the breaks. Structural breaks are observed using the Chow test, and the long-run relationship between the variables is examined using Gregory and Hanssen's approach.FindingsThis study found that land degradation and climate change have a negative relationship with agriculture production in Somalia. Land degradation leads to the decline in agricultural production as the loss of one hectare of land due the depletion causes agriculture production of Somalia to fall by about five percent. Climate changes and warming of the environment lead to the reduction of agriculture production. One degree Celsius rise in the temperature leads to a three percent decline in agricultural production. Capital contributes immensely to agricultural production as one unit of additional capital raises production by seven percent. The contribution of labor to agricultural production is limited because of land contractionPractical implicationsLand degradation is a significant contributor to the decline of agricultural production. As land degradation continues to worsen, rural poverty increases, which in turn causes the rural migration and the social conflict. The government should develop land improvement programs such as increasing market orientation of the farmers, encourage private sector engagement in agribusiness and establish a regulatory framework of the land uses.Originality/valueThis study examines the structure of the time-series and specifies the break periods to determine when and where significant and sudden changes occurred within land degradation and agricultural production. The study employs advanced econometric methods, namely, Ng-Perron method and the Lee-Strazicich method to test the unit root property of the breaks. It also examines the long-run relationship between the variables using Gregory and Hanssen's approach.

scholarly journals Time series and beyond: multifaceted plankton research at a marine Mediterranean LTER site

2019 ◽  
Vol 34 ◽  
pp. 273-310 ◽  
Author(s):  
Adriana Zingone ◽  
Domenico D'Alelio ◽  
Maria Grazia Mazzocchi ◽  
Marina Montresor ◽  
Diana Sarno ◽  
...  
Keyword(s):  
Time Series ◽  
Environmental Changes ◽  
Multiple Scales ◽  
Algal Species ◽  
Taxonomic Diversity ◽  
Life Cycles ◽  
Trophic Relationships ◽  
Primary Role ◽  
Long Time Series ◽  
Long Time

Plankton are a pivotal component of the diversity and functioning of coastal marine ecosystems. A long time-series of observations is the best tool to trace their patterns and variability over multiple scales, ultimately providing a sound foundation for assessing, modelling and predicting the effects of anthropogenic and natural environmental changes on pelagic communities. At the same time, a long time-series constitutes a formidable asset for different kinds of research on specific questions that emerge from the observations, whereby the results of these complementary studies provide precious interpretative tools that augment the informative value of the data collected. In this paper, we review more than 140 studies that have been developed around a Mediterranean plankton time series gathered in the Gulf of Naples at the station LTER-MC since 1984. These studies have addressed different topics concerning marine plankton, which have included: i) seasonal patterns and trends; ii) taxonomic diversity, with a focus on key or harmful algal species and the discovery of many new taxa; iii) molecular diversity of selected species, groups of species or the whole planktonic community; iv) life cycles of several phyto- and zooplankton species; and v) interactions among species through trophic relationships, parasites and viruses. Overall, the products of this research demonstrate the great value of time series besides the record of fluctuations and trends, and highlight their primary role in the development of the scientific knowledge of plankton much beyond the local scale.

scholarly journals Dynamic Changes of NDVI in the Growing Season of the Tibetan Plateau During the Past 17 Years and Its Response to Climate Change

2019 ◽  
Vol 16 (18) ◽  
pp. 3452 ◽  
Author(s):  
Xianglin Huang ◽  
Tingbin Zhang ◽  
Guihua Yi ◽  
Dong He ◽  
Xiaobing Zhou ◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Tibetan Plateau ◽  
Time Series Analysis ◽  
Environmental Changes ◽  
Climatic Factors ◽  
Growing Season ◽  
Lag Time ◽  
The Tibetan Plateau ◽  
Series Analysis

The fragile alpine vegetation in the Tibetan Plateau (TP) is very sensitive to environmental changes, making TP one of the hotspots for studying the response of vegetation to climate change. Existing studies lack detailed description of the response of vegetation to different climatic factors using the method of multiple nested time series analysis and the method of grey correlation analysis. In this paper, based on the Normalized Difference Vegetation Index (NDVI) of TP in the growing season calculated from the MOD09A1 data product of Moderate-resolution Imaging Spectroradiometer (MODIS), the method of multiple nested time series analysis is adopted to study the variation trends of NDVI in recent 17 years, and the lag time of NDVI to climate change is analyzed using the method of Grey Relational Analysis (GRA). Finally, the characteristics of temporal and spatial differences of NDVI to different climate factors are summarized. The results indicate that: (1) the spatial distribution of NDVI values in the growing season shows a trend of decreasing from east to west, and from north to south, with a change rate of −0.13/10° E and −0.30/10° N, respectively. (2) From 2001 to 2017, the NDVI in the TP shows a slight trend of increase, with a growth rate of 0.01/10a. (3) The lag time of NDVI to air temperature is not obvious, while the NDVI response lags behind cumulative precipitation by zero to one month, relative humidity by two months, and sunshine duration by three months. (4) The effects of different climatic factors on NDVI are significantly different with the increase of the study period.

scholarly journals Flood history of the Bavarian Alpine Foreland since the late Middle Ages in the context of internal and external climate forcing factors

2014 ◽  
Vol 11 (7) ◽  
pp. 7409-7440 ◽  
Author(s):  
O. Böhm ◽  
J. Jacobeit ◽  
R. Glaser ◽  
K.-F. Wetzel
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Climate Variability ◽  
Little Ice Age ◽  
Ice Age ◽  
Natural Climate Variability ◽  
Long Time ◽  
History Of ◽  
Alpine Foreland ◽  
Natural Climate

Abstract. This paper describes the flood history of the Bavarian part of the Alpine Foreland of Germany and addresses different questions concerning climate variability and flood frequencies from the 13th century until today. Will recent climatic change modify the flood frequencies within the Bavarian Alpine Foreland or are the flood frequencies varying due to altering climatic conditions since historical times? In the context of recent discussions whether man-made climate change will modify the present state of flood frequencies, a look back into the past is essential to understand the occurrence of floods in general and of recent floods in particular. In order to understand climatic variability and changes in a comprehensive way, it is necessary to review long time series. A perceived increase of summer floods in eastern Germany and Bavaria since 1997 requires examination of long time series to estimate changes in flood frequencies in a proper way. In view of the annual distribution of flood events within the Alpine Foreland of Germany, summer floods prove to be most important. Based on written historical sources, the flood history of the Alpine Foreland of Germany can be reconstructed back to the 14th century. One major result is the occurrence of "flood-rich" and "flood-poor" episodes in nearly cyclical sequences. Flood-rich periods were recorded in the periods 1300–1335, 1370–1450, 1470–1525, 1555–1590, 1615–1665, 1730–1780, 1820–1870, and 1910–1955 as well as in a 9th period beginning in 1980. The flood-rich periods are characterized by longer flood durations. Most of the flood-rich and flood-poor periods (in particular the beginning and the end of them) can be connected to changes in natural climate variability. These include changing sunspot numbers (as a measure of solar activity), so-called Little Ice Age Type Events (LIATEs) as well as changes in the North Atlantic Oscillation (NAO). Climate signals from external forcing factors, which could be used to explain the changing flood frequencies in the Bavarian Alpine Foreland, end in 1930. Relationships within the climate system such as the correlation of flood frequencies with the NAO have changed during the transition from the post Little Ice Age period to the Modern Climate Optimum around 1930. Natural climate variability might have been outperformed by anthropogenic climate change.

The Development of Climate Science of the Baltic Sea Region

2017 ◽  
Author(s):  
Anders Omstedt
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Baltic Sea ◽  
Environmental Changes ◽  
Climate Science ◽  
Regime Shifts ◽  
The Baltic Sea ◽  
The Earth ◽  
Baltic Sea Region ◽  
The Baltic

Dramatic climate changes have occurred in the Baltic Sea region caused by changes in orbital movement in the earth–sun system and the melting of the Fennoscandian Ice Sheet. Added to these longer-term changes, changes have occurred at all timescales, caused mainly by variations in large-scale atmospheric pressure systems due to competition between the meandering midlatitude low-pressure systems and high-pressure systems. Here we follow the development of climate science of the Baltic Sea from when observations began in the 18th century to the early 21st century. The question of why the water level is sinking around the Baltic Sea coasts could not be answered until the ideas of postglacial uplift and the thermal history of the earth were better understood in the 19th century and periodic behavior in climate related time series attracted scientific interest. Herring and sardine fishing successes and failures have led to investigations of fishery and climate change and to the realization that fisheries themselves have strongly negative effects on the marine environment, calling for international assessment efforts. Scientists later introduced the concept of regime shifts when interpreting their data, attributing these to various causes. The increasing amount of anoxic deep water in the Baltic Sea and eutrophication have prompted debate about what is natural and what is anthropogenic, and the scientific outcome of these debates now forms the basis of international management efforts to reduce nutrient leakage from land. The observed increase in atmospheric CO2 and its effects on global warming have focused the climate debate on trends and generated a series of international and regional assessments and research programs that have greatly improved our understanding of climate and environmental changes, bolstering the efforts of earth system science, in which both climate and environmental factors are analyzed together.Major achievements of past centuries have included developing and organizing regular observation and monitoring programs. The free availability of data sets has supported the development of more accurate forcing functions for Baltic Sea models and made it possible to better understand and model the Baltic Sea–North Sea system, including the development of coupled land–sea–atmosphere models. Most indirect and direct observations of the climate find great variability and stochastic behavior, so conclusions based on short time series are problematic, leading to qualifications about periodicity, trends, and regime shifts. Starting in the 1980s, systematic research into climate change has considerably improved our understanding of regional warming and multiple threats to the Baltic Sea. Several aspects of regional climate and environmental changes and how they interact are, however, unknown and merit future research.

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