- E-postjarl.giske@uib.no
- Telefon+47 55 58 22 1099205975
- BesøksadresseThormøhlensgate 53BBergenRom3H20
- PostadressePostboks 78035020 Bergen
English:
My current research interest is how to evolve adaptations. The major tool for this is the Genetic Algorithm. Currently I use it to evolve decisions, behaviour and life histories in fish.
My interest in decisions has been a long walk starting with life-history-based optimizations. Triggered by how organisms are able to perform decisions that (seemingly) simultaneously can incorporate state-, age-, density-, and environment-dependent trade-off, I started with Geir Huse to model adaptations through Artificial Neural Networks, Genetic Algorithms, and Individual-Based Modelling. Later, I have focused (with Sergey Budaev, Marc Mangel and other TE colleagues) even more on how the decision archtecture in fish works, and how this can be utilised in modelling.
Norsk:
Jarl Giskes forskning er fokusert på forståelse av atferd, livssyklus og romlig utbredelse av dyreplankton og fisk. Dynamikken i økosystemet er summen av alle hendelser hos alle individer i alle arter. Det enkelte individs atferd er nesten alltid påvirket av mange faktorer samtidig, så som risiko for å bli spist, mulighet til å finne mat, temperatur og årstid. Matematisk modellering kan derfor være et nødvendig redskap for å forstå begivenhetene. Evolusjonen har gjennom naturlig seleksjon formet livssyklusene og atferdene til akvatiske organismer, slik at de er tilpasset både naturforholdene og andre levende organismer. Selv om det enkelte individ ikke har innsikt i sitt eget liv, så har evolusjonen formet sanseapparet og atferdsresponsene slik at organismen reagerer "fornuftig" på miljøforholdene. For å forstå dynamikken i et økosystem er det derfor nødvendig å forstå hva som motiverer organismene til å ha den atferden de har. Giskes forskning har derfor konsentrert seg om å forstå hva som motiverer individene til å handle. Giske har også (sammen med Per Jakobsen) skrevet en lærebok på norsk om evolusjon og økologi.
BIO 110 Evolusjon og økologi
VIT 210 Mennesket: natur og kultur
Updated publication list can be found here:
http://bio.uib.no/te/jg/publications.php
Artikler, leserbrev og kronikker på norsk finnes her:
http://bio.uib.no/te/jg/samfunnsdebatt.php
- (2007). Evolusjon og økologi. En innføring. 2. utgave. Fagbokforlaget.
- (1999). Evolusjon og økologi - en innføring. Fagbokforlaget.
- (2023). Does fishing dismantle fish culture and ecosystem structure? Questions about the implications of social learning among fish and fishers. Fish and Fisheries. 889-895.
- (2023). Adaptive host responses to infection can resemble parasitic manipulation. Ecology and Evolution.
- (2020). The ODD protocol for describing agent-based and other simulation models: A second update to improve clarity, replication, and structural realism. JASSS : Journal of Artificial Societies and Social Simulation. 1-20.
- (2020). Hormones as adaptive control systems in juvenile fish. Biology Open. 1-16.
- (2020). Hormonal adjustments to future expectations impact growth and survival in juvenile fish. Oikos. 41-51.
- (2019). Decision-making from the animal perspective: Bridging ecology and subjective cognition. Frontiers in Ecology and Evolution. 1-14.
- (2018). AHA: A general cognitive architecture for Darwinian agents. Biologically Inspired Cognitive Architectures. 51-57.
- (2016). The proximate architecture for decision-making in fish. Fish and Fisheries. 680-695.
- (2016). The global potential for carbon capture and storage from forestry. Carbon Balance and Management.
- (2016). Impact of hatch-date on early life growth and survival of Mueller's pearlside (Maurolicus Muelleri) larvae and life-history consequences. Canadian Journal of Fisheries and Aquatic Sciences. 163-176.
- (2016). Impact of hatch date on early life growth and survival of Mueller’s pearlside (Maurolicus muelleri) larvae and life-history consequences. Canadian Journal of Fisheries and Aquatic Sciences. 163-176.
- (2016). From sensing to emergent adaptations: Modelling the proximate architecture for decision-making. Ecological Modelling. 90-100.
- (2015). What difference does it make if viruses are strain-, rather than speciesspecific? Frontiers in Microbiology.
- (2014). The emotion system promotes diversity and evolvability. Proceedings of the Royal Society of London. Biological Sciences.
- (2014). Optimal defense strategies in an idealized microbial food web under trade-off between competition and defense. PLOS ONE.
- (2014). Marine ecosystem acoustics (MEA): Quantifying processes in the sea at the spatio-temporal scales on which they occur. ICES Journal of Marine Science. 2357-2369.
- (2014). A theoretical analysis of how strain-specific viruses can control microbial species diversity. Proceedings of the National Academy of Sciences of the United States of America. 7813-7818.
- (2013). The Scaled Subspaces Method: A new trait-based approach to model communities of populations with largely inhomogeneous density. Ecological Modelling. 173-186.
- (2013). Successful strategies in size structured mixotrophic food webs. Aquatic Ecology. 329-347.
- (2013). Effects of the emotion system on adaptive behavior. The American Naturalist. 689-703.
- (2012). Selective consequences of catastrophes for growth rates in a stream-dwelling salmonid. Oecologia. 393-404.
- (2012). Hva er et menneske? Hjernen mellom natur og kultur i et langt, historisk perspektiv. Arr - Idéhistorisk tidsskrift. 81-85.
- (2010). The ODD protocol A review and first update. Ecological Modelling. 2760-2768.
- (2009). Quantifying the adaptive value of learning in foraging behavior. The American Naturalist. 478-489.
- (2008). Benefitting from bibliometry. Ethics in Science and Environmental Politics. 79-81.
- (2007). Exploration or exploitation: life expectancy changes the value of learning in foraging strategies. Oikos. 513-523.
- (2006). Co-existence of learners and stayers maintains the advantage of social foraging. Evolutionary Ecology Research. 1311-1324.
- (2006). A standard protocol for describing individual-based and agent-based models. Ecological Modelling. 115-126.
- (2003). Explicit trade-off rules in proximate adaptive agents. Evolutionary Ecology Research. 835-865.
- (2002). The influence of turbidity on growth and survival of fish larvae: a numerical analysis. Hydrobiologia. 49-59.
- (2002). Artificial evolution of life history and behavior. The American Naturalist. 624-644.
- (2001). Spatial modelling for marine resource management, with a focus on fish. Sarsia. 405-410.
- (1999). Implementing behaviour in individual-based models using neural networks and genetic algorithms. Evolutionary Ecology. 469-483.
- (1999). A length-based hypothesis for feeding migrations in pelagic fish. Canadian Journal of Fisheries and Aquatic Sciences. 26-34.
- (1998). Modelling spatial dynamics of fish. Reviews in Fish Biology and Fisheries. 57-81.
- (1998). Ecology in Mare Pentium; an individual-based spatio-temporal model for fish with adapted behaviour. Fisheries Research. 163-178.
- (1997). The significance of optical properties in competition among visual and tactile planktivores: a theoretical study. Ecological Modelling. 123-136.
- (1995). Why Pelagic Planktivores should be Unselective Feeders. Journal of Theoretical Biology. 41-50.
- (1990). Vertical distribution and trophic interactions of zooplankton and fish in Masfjorden, Norway. Sarsia. 65-81.
- (1998). Geophysical/Economical Feasibility Study of Ocean Disposal of CO2 at Haltenbanken. 138. 138. .
- (1997). Biological impact of CO2 disposal in Norwegian waters: Preliminary review. 2. 2. .
- (2019). A 100 000 year aquatic journey with our southern African ancestors.
- (2011). Biologi, Fysikk, Kunst og de Store Spørsmål.
- (2006). Coexistence of mobile and sedentary strategies maintains the advantage of social foraging.
- (2003). Predictable, chaotic or stochastic; do we understand the nature of the oceanic ecosystem?
- (2003). Hedonic models of fish behaviour.
- (2003). Evolusjon og økologi.
- (2002). Modellering av hedonisk atferd.
- (2002). Evolutionary approaches to behaviour in individual-based modelling.
- (2000). Den evolverte hjernen. Bergens Tidende.
- (2000). Av natur er du kommet, til kultur er du blitt. Bergens Tidende.
- (2009). Hoffnarrens tale: et ID-blikk på Darwinjubileet og evolusjonsteorien. Naturen. 63-64.
- (2009). Gud + evolusjonen = sant + nyttig? Naturen. 61-62.
- (2003). Susan Blackmore: Memesket. Naturen. 188-190.
- (2003). Lærer vi av Darwin-debatten? Vårt land. 20-21.
- (2009). Bli liv! Evolusjonens motor og begynnelse. Naturen. 13-25.
- (2009). 150 år underveis mot den store syntesen. Vantro, tvil og tro på Darwin i ny sakprosa. Prosa - tidsskrift for skribenter. 20-26.
- (2003). Replikatologi. Naturen. 151-172.
- (2001). Millenium Man. Naturen. 30-34.
- (2009). Darwins farlige ide. Klassekampen.
- (2009). "Ida" er oversolgt. Aftenposten (morgenutg. : trykt utg.).
- (2003). Darwin på hjernen. Bergens Tidende.
- (2020). Modelling fish growth under hormonal regulation as a factor in Pace of Life.
- (1990). Habitat profitability for pelagic animals : adaptive values along continuous vertical gradients.
- (2012). Rådyre tidsskrifter kveler økonomien til universiteter og høyskoler.
- (2008). Skal skolen undervise skapelse?
- (2008). Hva skal vi med UiB.
- (2011). Cues and decision rules in animal migration. 20 sider.
- (2004). 33. Utilizing different levels of adaptation in individual-based modeling. 15 sider.
- (2002). Individual based modelling. 21 sider.
- (2001). Chapter 4. Theoretical and statistical models in natural resource management and research. 16 sider.
- (2000). Modelling zooplankton dynamics. 97 sider.
- (1999). Chapter 2. A model of enhancement potentials in open ecosystems. 15 sider.
- (1998). Evolutionary models for fisheries management. 10 sider.
- (1998). Ecological Modelling for Fisheries. 58 sider.
- (2003). Models and functioning of marine ecosystems. . I:
- (2003). Encyclopedia of Life Support Systems (EOLSS)[elektronisk ressurs]. x.
- (2002). hedonisk atferdmodellering.
- (2020). Computational animal welfare: Towards cognitive architecture models of animal sentience, emotion and wellbeing. Royal Society Open Science. 17 sider.
- (2015). Making predictions in a changing world: The benefits of individual-based ecology. BioScience. 140-150.