scholarly journals The effect of sea surface temperature on the structure and connectivity of species landings interaction networks in a multispecies recreational fishery.

2022 ◽  
Author(s):  
Kayla Mackenzie Blincow ◽  
Brice X Semmens
Keyword(s):  
Time Series ◽  
Dynamic Modelling ◽  
Single Species ◽  
Unintended Consequences ◽  
Interaction Networks ◽  
Multispecies Fisheries ◽  
Recreational Fishery ◽  
Species Management ◽  
Management Approaches ◽  
Modelling Methods

Multispecies fisheries, particularly those that routinely adapt the timing, location, and methods of fishing to prioritize fishery targets, present a challenge to traditional single-species management approaches. Efforts to develop robust management for multispecies fisheries require an understanding of how priorities drive the network of interactions between catch of different species, especially given the added challenges presented by climate change. Using 35 years of landings data from a southern California recreational fishery, we leveraged empirical dynamic modelling methods to construct causal interaction networks among the main species targeted by the fishery. We found strong evidence for dependencies among species landings time series driven by apparent hierarchical catch preference within the fishery. In addition, by parsing the landings time series into anomalously cool, normal, and anomalously warm regimes (the last reflecting ocean temperatures anticipated by 2040), we found that network complexity was highest during warm periods. Our findings suggest that as ocean temperatures continue to rise, so too will the risk of unintended consequences from single species management in this multispecies fishery.

scholarly journals An equation-free method reveals the ecological interaction networks within complex microbial ecosystems

2016 ◽  
Author(s):  
Kenta Suzuki ◽  
Katsuhiko Yoshida ◽  
Yumiko Nakanishi ◽  
Shinji Fukuda
Keyword(s):  
Time Series ◽  
Microbial Communities ◽  
Microbial Processes ◽  
Interaction Networks ◽  
List Type ◽  
Metagenomic Sequencing ◽  
Ecological Interactions ◽  
Microbial Interaction ◽  
Ecological Interaction ◽  
Dataset Size

AbstractMapping the network of ecological interactions is key to understanding the composition, stability, function and dynamics of microbial communities. In recent years various approaches have been used to reveal microbial interaction networks from metagenomic sequencing data, such as time-series analysis, machine learning and statistical techniques. Despite these efforts it is still not possible to capture details of the ecological interactions behind complex microbial dynamics.We developed the sparse S-map method (SSM), which generates a sparse interaction network from a multivariate ecological time-series without presuming any mathematical formulation for the underlying microbial processes. The advantage of the SSM over alternative methodologies is that it fully utilizes the observed data using a framework of empirical dynamic modelling. This makes the SSM robust to non-equilibrium dynamics and underlying complexity (nonlinearity) in microbial processes.We showed that an increase in dataset size or a decrease in observational error improved the accuracy of SSM whereas, the accuracy of a comparative equation-based method was almost unchanged for both cases and equivalent to the SSM at best. Hence, the SSM outperformed a comparative equation-based method when datasets were large and the magnitude of observational errors were small. The results were robust to the magnitude of process noise and the functional forms of inter-specific interactions that we tested. We applied the method to a microbiome data of six mice and found that there were different microbial interaction regimes between young to middle age (4-40 week-old) and middle to old age (36-72 week-old) mice.The complexity of microbial relationships impedes detailed equation-based modeling. Our method provides a powerful alternative framework to infer ecological interaction networks of microbial communities in various environments and will be improved by further developments in metagenomics sequencing technologies leading to increased dataset size and improved accuracy and precision.

scholarly journals Smokefree policy and medication dispensing for people in prison: interrupted time series analysis

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
A Leyland ◽  
E Tweed ◽  
T Byrne ◽  
P Conaglen ◽  
P Craig ◽  
...  
Keyword(s):  
Time Series ◽  
Prison Population ◽  
Moving Average ◽  
Unintended Consequences ◽  
Eye Drops ◽  
Natural Experiments ◽  
Interrupted Time Series Analysis ◽  
Objective Health ◽  
Smokefree Policy ◽  
Medication Dispensing

Abstract Background Previous evaluations of smokefree prison policies have suggested improvements in self-rated health and some smoking-related symptoms. No studies to date have investigated impacts on medication use as proxy measures of objective ill-health or as indicators of potential negative unintended consequences. These is limited evidence to date on these important outcomes. Methods We obtained from NHS National Services Scotland aggregate data on medication items dispensed in prisons, based on individual named patient medication records, and from the Scottish Prison Service data on the prison population, for the period Jan 2013-Nov 2019. Items of interest comprised those for smoking cessation (varenicline and buproprion); nicotine replacement; specific smoking-related health conditions (glyceryl trinitrate; inhaled bronchodilators and steroids; antibiotics; chloramphenicol eye drops; and proton pump inhibitors and H2 receptor antagonists), and potential unintended mental health consequences (anti-depressants). We also included a set of negative controls for which dispensing was not expected to be affected by the new smokefree policy (anticonvulsants, excluding pregabalin and gabapentin). Analyses were undertaken using AutoRegressive Integrated Moving Average (ARIMA) time series methods, with the dates of the policy's announcement and of implementation included as pre-specified breakpoints. Results The results of ARIMA modelling of medication dispensing are confidential until May 2020 due to their sensitivity and will be available to present at WCPH 2020. Conclusions The use of routinely available dispensing data as an indicator of objective health impacts and potential negative unintended consequences provides novel insights into the effectiveness of smokefree prison policies. Results will be of interest to international jurisdictions considering such policies and to those seeking to harness the potential of administrative data for natural experiments.

scholarly journals Economic effort management in multispecies fisheries: the FcubEcon model

2010 ◽  
Vol 67 (8) ◽  
pp. 1802-1810 ◽  
Author(s):  
Ayoe Hoff ◽  
Hans Frost ◽  
Clara Ulrich ◽  
Dimitrios Damalas ◽  
Christos D. Maravelias ◽  
...  
Keyword(s):  
Single Species ◽  
Fish Stock ◽  
Economic Optimization ◽  
Management Tools ◽  
Management Framework ◽  
Fish Stocks ◽  
Effort Allocation ◽  
Multispecies Fisheries ◽  
The Past ◽  
Quota Management

Abstract Hoff, A., Frost, H., Ulrich, C., Damalas, D., Maravelias, C. D., Goti, L., and Santurtún, M. 2010. Economic effort management in multispecies fisheries: the FcubEcon model. – ICES Journal of Marine Science, 67: 1802–1810. Applying single-species assessment and quotas in multispecies fisheries can lead to overfishing or quota underutilization, because advice can be conflicting when different stocks are caught within the same fishery. During the past decade, increased focus on this issue has resulted in the development of management tools based on fleets, fisheries, and areas, rather than on unit fish stocks. A natural consequence of this has been to consider effort rather than quota management, a final effort decision being based on fleet-harvest potential and fish-stock-preservation considerations. Effort allocation between fleets should not be based on biological considerations alone, but also on the economic behaviour of fishers, because fisheries management has a significant impact on human behaviour as well as on ecosystem development. The FcubEcon management framework for effort allocation between fleets and fisheries is presented, based on the economic optimization of a fishery's earnings while complying with stock-preservation criteria. Through case studies of two European fisheries, it is shown how fishery earnings can be increased significantly by reallocating effort between fisheries in an economically optimal manner, in both effort-management and single-quota management settings.

Reconstructing large interaction networks from empirical time series data

2021 ◽  
Author(s):  
Chun‐Wei Chang ◽  
Takeshi Miki ◽  
Masayuki Ushio ◽  
Po‐Ju Ke ◽  
Hsiao‐Pei Lu ◽  
...  
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Interaction Networks ◽  
Series Data ◽  
Large Interaction

Scoring Modeling in Estimating the Financial Condition of Russian Agro-Industrial Companies

2019 ◽  
pp. 151-175
Author(s):  
Oleg Y. Patlasov ◽  
Olga K. Mzhelskaya
Keyword(s):  
Dynamic Modelling ◽  
Financial Indicators ◽  
Advantages And Disadvantages ◽  
Financial Condition ◽  
Industrial Companies ◽  
Express Analysis ◽  
Regional Specificity ◽  
Methodological Problems ◽  
Discriminant Models ◽  
Modelling Methods

The chapter presents the authors' estimations according to the scoring modeling techniques; also, internationally spread models of bankruptcy forecasting are systematized. Advantages and disadvantages of dynamic modelling methods as applied to financial condition assessment are presented here. Methodological problems of financial modelling are explained here in detail. Regression, logit-regression, and discriminant models are built on the basis of data on the Rosselkhozbank and Sberbank of Russia regulations, taking into account the agrarian specifics of organizations and regional specificity of the Omsk region. An attempt has been made to balance the simplicity of calculations and the accuracy of predictions. Graphs, to be used for express analysis, are constructed on the basis of two core financial indicators.

Harvesting at the Community Level

2020 ◽  
pp. 205-228
Author(s):  
Michael J. Fogarty ◽  
Jeremy S. Collie
Keyword(s):  
Single Species ◽  
Economic Incentives ◽  
Unintended Consequences ◽  
Community Context ◽  
Reference Points ◽  
Individual Species ◽  
Biological Interactions ◽  
Predator Prey ◽  
The Right ◽  
Technical Solutions

Most fisheries are not directed at individual species alone. Rather, in many instances, species within a community are caught together and are also part of competitive networks and food webs. Species that are caught together are subject to technical interactions. Species that compete or are connected through predator–prey interactions (or other types of interactions) are subject to biological interactions. Ignoring either of these forms of interaction in management can lead to unintended consequences. Technical solutions can help to avoid some species while targeting others, but a comprehensive solution requires creating the right economic incentives and some incidental catch is still inevitable. Accounting for trophic interactions means that biological reference points depend on the abundance of other taxa. Single-species approaches are invalid in a multispecies or community context where biological interactions are important. Technical interactions can make it impossible to achieve target exploitation rates even if biological interactions are relatively unimportant.

Disease in fisheries and aquaculture

2020 ◽  
pp. 183-210
Author(s):  
Donald C. Behringer ◽  
Chelsea L. Wood ◽  
Martin Krkošek ◽  
David Bushek
Keyword(s):  
Human Health ◽  
Wild Species ◽  
Disease Transmission ◽  
Economic Losses ◽  
Nutrient Quality ◽  
Species Management ◽  
Negative Impacts ◽  
Management Approaches ◽  
Opening Up

Infectious marine diseases have profound impacts on fisheries and aquaculture through their effects on growth, fecundity, mortality, and marketability. Economic losses have motivated research to minimize the negative impacts of disease on these industries. However, this relationship is reciprocal, as fishing and aquaculture can shape disease transmission. The effects of fisheries and aquaculture on disease are scale dependent, with different outcomes at the population, metapopulation, community, and ecosystem levels. Management approaches are limited in fisheries, and intense in aquaculture, sometimes with undesirable impacts on wild species. Management needs can be particularly intense in hatcheries, where stocks are sensitive and kept at high densities. Increased interest in microbiome–disease interactions are opening up new opportunities to manage marine diseases in aquaculture. Solutions for marine diseases in fisheries and aquaculture may ultimately improve human health by reducing exposure to pathogens and increasing nutrient quality, but could negatively impact human health through exposure to antibiotics and other chemicals used to treat parasites.

scholarly journals A Survey of the Literature on Unintended Consequences Associated with Health Information Technology: 2014–2015

2016 ◽  
Vol 25 (01) ◽  
pp. 13-29 ◽  
Author(s):  
J. Abraham ◽  
L. L. Novak ◽  
T. L. Reynolds ◽  
A. Gettinger ◽  
K. Zheng
Keyword(s):  
Information Technology ◽  
Time Series ◽  
Health Information Technology ◽  
Health Information ◽  
Unintended Consequences ◽  
Adverse Outcomes ◽  
Future Research ◽  
Health It ◽  
Recorded Data ◽  
The Impact

SummaryObjective: To summarize recent research on unintended consequences associated with implementation and use of health information technology (health IT). Included in the review are original empirical investigations published in English between 2014 and 2015 that reported unintended effects introduced by adoption of digital interventions. Our analysis focuses on the trends of this steam of research, areas in which unintended consequences have continued to be reported, and common themes that emerge from the findings of these studies.Method: Most of the papers reviewed were retrieved by searching three literature databases: MEDLINE, Embase, and CINAHL. Two rounds of searches were performed: the first round used more restrictive search terms specific to unintended consequences; the second round lifted the restrictions to include more generic health IT evaluation studies. Each paper was independently screened by at least two authors; differences were resolved through consensus development.Results: The literature search identified 1,538 papers that were potentially relevant; 34 were deemed meeting our inclusion criteria after screening. Studies described in these 34 papers took place in a wide variety of care areas from emergency departments to ophthalmology clinics. Some papers reflected several previously unreported unintended consequences, such as staff attrition and patients’ withholding of information due to privacy and security concerns. A majority of these studies (71%) were quantitative investigations based on analysis of objectively recorded data. Several of them employed longitudinal or time series designs to distinguish between unintended consequences that had only transient impact, versus those that had persisting impact. Most of these unintended consequences resulted in adverse outcomes, even though instances of beneficial impact were also noted. While care areas covered were heterogeneous, over half of the studies were conducted at academic medical centers or teaching hospitals. Conclusion: Recent studies published in the past two years represent significant advancement of unintended consequences research by seeking to include more types of health IT applications and to quantify the impact using objectively recorded data and longitudinal or time series designs. However, more mixed-methods studies are needed to develop deeper insights into the observed unintended adverse outcomes, including their root causes and remedies. We also encourage future research to go beyond the paradigm of simply describing unintended consequences, and to develop and test solutions that can prevent or minimize their impact.

scholarly journals Limited evidence for sardine and anchovy asynchrony: re-examining an old story

2020 ◽  
Vol 287 (1922) ◽  
pp. 20192781
Author(s):  
Margaret C. Siple ◽  
Timothy E. Essington ◽  
Lewis A. K. Barnett ◽  
Mark D. Scheuerell
Keyword(s):  
Time Series ◽  
Food Webs ◽  
Low Frequency ◽  
Single Species ◽  
The Other ◽  
Generalist Predators ◽  
Frequency Variation ◽  
Limited Evidence ◽  
Short Time Series ◽  
Short Time

Asynchronous fluctuations in abundance between species with similar ecological roles can stabilize food webs and support coexistence. Sardine ( Sardinops spp.) and anchovy ( Engraulis spp.) have long been used as an example of this pattern because low-frequency variation in catches of these species appears to occur out of phase, suggesting that fisheries and generalist predators could be buffered against shifts in productivity of a single species. Using landings data and biomass and recruitment estimates from five regions, we find that species do not have equivalent peak abundances, suggesting that high abundance in one species does not compensate for low abundance in the other. We find that globally there is a stronger pattern of asynchrony in landings compared to biomass, such that landings data have exaggerated the patterns of asynchrony. Finally, we show that power to detect decadal asynchrony is poor, requiring a time series more than twice the length of the period of fluctuation. These results indicate that it is unlikely that the dynamics of these two species are compensatory enough to buffer fisheries and predators from changes in abundance, and that the measurements of asynchrony have largely been a statistical artefact of using short time series and landings data to infer ecology.

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