0000000000199047

AUTHOR

Joël M. Durant

showing 5 related works from this author

Ticket to spawn: Combining economic and genetic data to evaluate the effect of climate and demographic structure on spawning distribution in Atlantic…

2019

Abstract Climate warming and harvesting affect the dynamics of species across the globe through a multitude of mechanisms, including distribution changes. In fish, migrations to and distribution on spawning grounds are likely influenced by both climate warming and harvesting. The Northeast Arctic (NEA) cod (Gadus morhua) performs seasonal migrations from its feeding grounds in the Barents Sea to spawning grounds along the Norwegian coast. The distribution of cod between the spawning grounds has historically changed at decadal scales, mainly due to variable use of the northern and southern margins of the spawning area. Based on historical landing records, two major hypotheses have been put f…

0106 biological sciencesdemography010504 meteorology & atmospheric sciencesClimate ChangeFisheriesClimate change2306 Global and Planetary Change10125 Paleontological Institute and MuseumFish stock010603 evolutionary biology01 natural sciences2300 General Environmental Scienceddc:590spawning distributionGadusEnvironmental ChemistryAnimalsPrimary Research Article14. Life underwaterAtlantic Ocean0105 earth and related environmental sciencesGeneral Environmental ScienceGlobal and Planetary ChangebiologyEcologyNorwayReproductionGlobal warmingbiology.organism_classificationPrimary Research ArticlesSpawn (biology)FisheryGeographyHabitatArctic560 Fossils & prehistoric lifeGadus morhua2304 Environmental Chemistrysize truncationgenetic dataeconomic dataAtlantic cod2303 EcologyAnimal DistributionGlobal change biology
researchProduct

Non‐linearity in interspecific interactions in response to climate change: cod and haddock as an example

2020

Climate change has profound ecological effects, yet our understanding of how trophic interactions among species are affected by climate change is still patchy. The sympatric Atlantic haddock and cod are co-occurring across the North Atlantic. They compete for food at younger stages and thereafter the former is preyed by the latter. Climate change might affect the interaction and coexistence of these two species. Particularly, the increase in sea temperature (ST) has been shown to affect distribution, population growth and trophic interactions in marine systems. We used 33-year long time series of haddock and cod abundances estimates from two data sources (acoustic and trawl survey) to analy…

0106 biological sciences010504 meteorology & atmospheric sciencesClimate ChangePopulation DynamicsClimate change010603 evolutionary biology01 natural sciencesAbundance (ecology)AnimalsEnvironmental ChemistryPopulation growthEcosystemVDP::Mathematics and natural science: 4000105 earth and related environmental sciencesGeneral Environmental ScienceTrophic levelGlobal and Planetary ChangeEcologybiologyEcologyPopulation sizeBayes TheoremInterspecific competitionHaddockbiology.organism_classificationGadiformesSympatric speciationEnvironmental science
researchProduct

Empirical evidence of non-linearity in bottom-up effect in a marine predator-prey system

2022

Strength of species interaction may have profound effects on population dynamics. Empirical estimates of interaction strength is often based on the assumption that the interaction strengths are constant. Barents Sea cod and capelin are two fish populations for which such interaction has been acknowledged and used, under the assumption of constant interaction strength, when studying their population dynamics. However, species interaction can often be non-linear in marine ecosystems and might profoundly change our understanding of food chains. Analysing 37 years long survey time series in the Arcto-Boreal Barents Sea with a state-space modelling framework, we demonstrate that the effect of ca…

Food ChainOsmeriformesPredatory BehaviorPopulation DynamicsAnimalsVDP::Matematikk og Naturvitenskap: 400General Agricultural and Biological SciencesAgricultural and Biological Sciences (miscellaneous)Ecosystem
researchProduct

Attuning to a changing ocean

2020

The ocean is a lifeline for human existence, but current practices risk severely undermining ocean sustainability. Present and future social−ecological challenges necessitate the maintenance and development of knowledge and action by stimulating collaboration among scientists and between science, policy, and practice. Here we explore not only how such collaborations have developed in the Nordic countries and adjacent seas but also how knowledge from these regions contributes to an understanding of how to obtain a sustainable ocean. Our collective experience may be summarized in three points: 1) In the absence of long-term observations, decision-making is subject to high risk arising from na…

Underpinning010504 meteorology & atmospheric sciencesmedia_common.quotation_subjectSubject (philosophy)Climate changeSocial Sciences01 natural sciencesSustainability Science/dk/atira/pure/sustainabledevelopmentgoals/life_below_water03 medical and health sciencesClimate changesPolitical sciencePerceptionVDP::Matematikk og Naturvitenskap: 400::Basale biofag: 47014. Life underwaterNatural variabilitySDG 14 - Life Below WaterScientific disciplinesVDP::Landbruks- og Fiskerifag: 900::Fiskerifag: 9209030304 developmental biology0105 earth and related environmental sciencesmedia_common0303 health sciencesVDP::Agriculture and fishery disciplines: 900::Fisheries science: 920Multidisciplinarybusiness.industrykansainvälinen yhteistyöympäristöpolitiikkamarinePublic relationsilmastonmuutoksetBiological Sciencesclimate changeAction (philosophy)13. Climate actionSustainabilitytutkimuspolitiikkaPerspectiveekologinen kestävyysbusinessmeretympäristönmuutoksetEnvironmental SciencesbiologicalProceedings of the National Academy of Sciences of the United States of America
researchProduct

Durant_CapelinCod_BiolLett_Aug2022_Supplementary_revision2 from Empirical evidence of nonlinearity in bottom up effect in a marine predator–prey syst…

2022

Figure S1. Sensitivity test of the process to observation error variance ratio to the estimated process and observation error variance. Figure S2. Comparison of the estimated posteriors process errors for cod and capelin showing no significant correlation. Figure S3. Calculated log-likelihood for each potential threshold value within the 20 and 80 percentiles. Figure S4. Posteriors distribution for of the models’ parameters with indicated the Highest Density Interval (HDI) and the zero line (dotted line). Figure S5. Posterior distribution of Bayesian R square for the capelin (plot A) and cod (plot B). Methods. Codes developed for the analysis

researchProduct