Next Article in Journal
Investigation of Disease Outbreaks in Farmed Nile Tilapia in Coastal Tanzania (Pwani region) Reveals Pseudomonas aeruginosa as the Most Frequently Isolated Pathogen
Previous Article in Journal
Novel Integrative Mobilizable Elements (IMEs) in Vibrio Chromosomes Linked to Translucent Post-Larvae Disease (TPD)
Previous Article in Special Issue
The Influence of Habitat on Intra-Specific Variation in Fish Mating Systems
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Editorial

Habitat as a Template for Life Histories of Fish

Norwegian Institute for Nature Research, Sognsveien 68, 0855 Oslo, Norway
Fishes 2026, 11(8), 442; https://doi.org/10.3390/fishes11080442
Submission received: 7 July 2026 / Accepted: 23 July 2026 / Published: 28 July 2026
(This article belongs to the Special Issue Habitat as a Template for Life Histories of Fish)

Abstract

Life history traits are heritable and evolve through natural selection to maximize organisms’ Darwinian fitness in their specific environments. The theory of life history evolution has developed during the last 100 years, and is rooted in the idea that these traits, to a certain extent, are heritable. Concurrently, ecologists have acquired evidence in support of the theory. Thus, a central focus of the present Special Issue is the adaptiveness of natural fish populations, and how environmental variables affect developmental processes within and across generations, which influence phenotypic developments. Habitat selection in stable and stochastic environments dampen abundance fluctuations and promotes phenotypically plastic life histories with morphs using different habitats. Reproduction is a major event in every life history, and the structure of mating systems depends on factors that allow males to obtain and monopolize mating resources. Habitat use and management, and the conservation of populations, are the other central themes of the volume. All habitats used by species require concern so that management actions do not impinge on their habitat selection. It is demonstrated how adult bull sharks use a seascape. For small demersal species, the structure and particle size in the bottom substratum is critical to secure feeding opportunities and shelter. Shelter is particularly important when invasive predators are introduced, and the native fauna meet a new threat against which they have no behavioral defense. Future research directions are discussed at the end of this introduction and in several of the separate papers.

1. Introduction

Life history is the science of how individuals in populations grow and survive where traits change in accordance with how the organisms allocate energy for growth, maintenance and reproduction. Life histories quantify how individual traits are expressed in response to how environmental variables change. The central theory is that traits, such as migration and dispersal, age at first maturity, length of life span, egg size and fecundity are heritable and evolve through natural selection to maximize organisms’ Darwinian fitness in a specific environment [1,2].
Life history is a discipline in evolutionary ecology. The theory of life history has been developing with seminal papers such as Write [3], forming the concept of adaptive landscapes that map the relationship between life history traits and fitness. Peaks in the map represent optimal life history traits and valleys represent traits giving low survival. The evolution of a trait is a hill-climbing process. Then, Cole [4] observed that life history traits, such as age at first reproduction, fecundity and length of life span, are connected and evolve together to maximize an organism’s reproductive fitness. Furthermore, Hamilton [5] developed a theory concerning aging, and Schaffer [6] demonstrated theoretically how environmental stability and demographic trade-offs dictate whether an organism evolves to breed once (semelparity) or multiple times (iteroparity), with contrasting effects of juvenile and adult mortality. In addition, there are several other highly influential theoretical papers such as [7,8], on how energy is allocated for survival versus reproduction, development and growth, and whether individuals should reproduce a few large or more but smaller offspring. Such trade-offs shape life histories of populations and species. It was realized that there are direct relationships between generation time, life history traits and the ability of populations to recover from disturbances, and that reaction norms of life history variables help us predict how individuals and their offspring react to future environmental impacts. The latter is a cornerstone of evolutionary ecology and conservation biology [9,10,11].
These early theoretical works inspired ecologists to seek empirical evidence for the fundamental relationships [12,13]. Fish ecologists realized the importance of studying the entire life cycle to understand life histories and modeled how to best manage harvested species [14,15]. It became important to include influences, such as temperature experienced by embryos and larvae, which affect later life history decisions such as metabolic rates [16,17,18], growth [16,19], migration [20] and reproductive effort [21,22]. Other variables affecting embryos and larvae, such as predator presence [23], chemical environment [24], salinity and oxygen content [25], have knock-on effects on later life history stages. Even environmental experiences perceived by parents can be transferred to offspring and affect life history variables across generations [26,27].
Movement ecology is an important part of life history studies with a recent shift from individual tagging studies to telemetry, biologging and global telemetry networks [28,29]. Fish move to find food, for predator avoidance and to find a safe place to reproduce [30,31]. Migration studies reveal how and when fish disperse and return [32,33], and how they navigate over long distances in the ocean [34,35]. By mapping their spatial dynamics, fisheries can accurately assess stock sizes, optimize the design of marine reserves, and regulate fishing pressure to prevent overexploitation [36]. Another important aspect is that migratory fish transport energy across ecosystems [37]. For example, fish that migrate from nutrient-rich seas into freshwater to spawn bring valuable marine nutrients into river systems, enriching the food web through excretions and carcass decomposition [38,39]. Human activities, such as dam building and alterations of waterways, disrupt migration routes. Selective overfishing is another widespread problem. Studying these paths allows scientists to evaluate where aquatic connectivity has been severed, design functional fishways and inform fishing regulators to protect fish during vulnerable stages such as under synchronized migration and spawning periods [40,41]. But still, these regulation issues are far from solved.
Many fish populations are divided in migratory and non-migratory (resident) individuals, a phenomenon called partial migration [42]. Partial migration is widespread among fish taxa, including anadromous, catadromous, potamodromous and oceanodromous fishes. It is also widely distributed across orders, with examples in many species from Salmonidae to Pleuronectidae [43]. However, in what way partial migration is genetically regulated is still open for discussion. Are migratory and resident phenotypes genetically distinct forms or are they polyphenic variants cued by environmental stimuli? Typically, in juveniles of Atlantic salmon, Salmo salar L. 1759, rapid growth increases the chance of early maturation and residency, instead of seaward migration and feeding in the ocean, suggesting that the forms are phenotypically plastic. In contrast, in whitebait Galaxias brevipinnis Günther, 1866, the migratory and resident phenotypes are genetically distinct. Iwikau et al. [44] found that migratory whitebait populations include jackpot individuals that carry allele sequences essential for residency. Because of these gene sequences, populations can exist as a non-migratory form after land-locking. A similar mechanism may exist in brown trout, where residency is chiefly genetically determined [45], although in anadromous populations, the growth rate of juveniles may influence whether they will remain or migrate. Thus, there may be a continuum from phenotypical plasticity to genetically determined partially migratory populations, and the degree of heritability differs among conspecific populations.
Until recently, the genetics of life history traits was little investigated, but recent population genomics studies in Atlantic salmon have identified two unlinked genomic regions surrounding the genes six6 in chromosome 9 and vgll3 of chromosome 25, which are associated with life history traits of Atlantic salmon lineages [46,47]. Genes at the six6 locus are associated with head morphology, which is crucial for their feeding strategy, and those at the vgll3 locus are associated with swimming performance [48], aggressiveness, metabolic rate and aerobic scope [49,50]. Both loci influence age and size at first maturity and iteroparity, which are important for the fitness of the fish [47,48,49,50]. Thus, many life history traits in this species are strongly influenced by natural selection, and it may also be so for other fishes.

2. The Studies

The studies in the present Special Issue are grouped in one of two categories, (1) adaptive life histories and (2) habitat use, management and conservation.

2.1. Adaptive Life Histories

Fish populations are often polymorphic with different sized morphs. One morph is typically slow-growing and small-sized, attaining maturity at a young age, flaunting no or few secondary sexual characters in contrast to the other, faster-growing and larger-sized morph. In a literature review, Jonsson [51] summarizes how these morphs are adapted to different niches by living in different habitats and feeding on different food items. Environmental stimuli affect the diversification, but it is an open question to what extent genetic and epigenetic differences affect the morph divergence.
How environmental factors give cues leading to population diversification is central in Skúlason’s [52] paper. How can environmental variables such as temperature, density, or predator presence affect developmental processes within and across generations that influence their phenotypic development? There seem to be inherited reaction norms related to specific signals that affect development. Such responses can even be transferred across generations.
Adaptive life histories through environmentally dependent effects are also a focus of Morris and Lundberg [53]. In a theoretical study, they simulated habitat selection in stable and stochastic environments. They demonstrated that ideal habitat selection dampen abundance fluctuations. Furthermore, habitat selection promotes phenotypically plastic life histories with morphs using different habitats as described above [51].
Reproduction is a major event in every life history, and Weir [54] reviewed how the structure of mating systems depends on factors that allow males to obtain and monopolize mating resources. Increases in temperature beyond optimal levels or decreases in oxygen availability may reduce the energy available for mating and for the defense of resources, and decrease variance in mating success. If individuals cannot monopolize resources, increases in density, extreme skews in sex ratios or the presence of alternative mating strategies within a sex can affect the nature of competition among individuals, with a change in mating system to an even or random distribution. Habitat alterations that result in increases in complexity because of vegetation or turbidity can affect the distribution of reproductive successes. While polygamy is typically considered the basal mating system of fishes, deviations from this mating system can be related to habitat features that influence the fitness of the individuals.

2.2. Habitat Use, Management and Conservation of Populations

Several of the studies concern population preservation. Morris and Lundberg [53] maintain that all different habitats used by a species require concern, so that management actions do not impinge on their habitat selection. Thus, one needs to know all habitats and areas used by populations.
Venables et al. [55] used acoustic telemetry when studying how adult bull sharks Carcharhinus leucas (Valenciennes, 1839) used the Bazaruto Seascape, Mosambique. They showed that the important habitat for resident bull sharks extended beyond the protected seascape, and that migratory individuals from other parts of the coast visited the protected area. Thus, there is a need to look at the size of the protected area to protect the resident sharks, and develop a strategy for how one can protect individuals from other aggregations moving along the coast.
Bottom particle size is important for demersal fishes, and habitat selection can differ with the size and sex of species. Yu et al. [56] showed how Leptobotia elongata (Bleeker, 1870) in the Yangtze River preferred coarse gravel and stones associated with habitat variability, good feeding opportunities and the formation of low-velocity refuges. Thus, restoring coarse substrate particles in the river will provide a good habitat for Leptobotia elongata and other species with similar habitat requirements.
Salmonidae include some of the world’s most invasive species, such as rainbow trout Oncorhynchus mykiss (Walbaum, 1792), which pose a threat to the southern smelt, dwarf galaxias Galaxias divergens Stockell, 1959 in New Zealand. Experimental research by Coughlan and Canning [57] demonstrated that dwarf galaxias do not change habitat in presence of this foreign intruder, making them vulnerable to predation. However, maintaining a coarse bottom substrate provides this galaxiid with shelter, and reducing fine substrate in rivers is a positive management action supporting dwarf galaxias in their home rivers.
Body sizes of similar-aged pairs of coho salmon Oncorhynchus kisutch (Walbaum, 1972) and cutthroat trout Oncorhynchus clarkii (Richardson, 1836) vary among stream and populations [58]. Important causes for size variations are the size of the catchment area, physical habitat structures such as substrate particle size, pools, boulders and dead wood, and salmonid density. Water temperature appears less important for growth variations in these fish. Management actions, such as improving the physical habitat by adding instream wood and creating pool areas, ensure a natural range of body sizes across watersheds, typical for healthy populations.
Body size influences activity levels of fish, and Dziubinska et al. [59] found that, in round goby Neogobius melanostomus (Pallas, 1814), large individuals shift habitats between day and night to a larger extent than smaller ones. Large individuals spend more time in vegetated areas during the day. At night, they showed a greater tendency to move to bare and rocky areas for feeding. Higher activity of larger individuals may be related to a reduced danger of mortality and a greater need for food. Thus, restoring benthic habitats provides good conditions for round goby.
Similarly, Chen et al. [60] showed habitat differences between small and larger gray snapper Lutjanus griseus (L., 1758). These are young and small fish, typically less than one year of age. Small juveniles were most often observed along the shore line and larger juveniles occurred more often on oyster reefs. Thus, habitat selection varies with size, as the niche requirements of small and large conspecifics are typically different, and often more so than those of competing species of similar-sized fish.
Thus, in a time with decreasing fish abundances, loss of habitat is a major threat, and habitat restoration is an urgently needed management action and a growing aspect of many life history studies of fish.

3. Future Research Directions

Anthropogenic-induced stress on aquatic habitats are stronger than ever before, and to better understand the meaning of these stresses for fishes, one needs to study the tolerance limits of the stressors by estimating reaction norms for life history traits in relation to the stressors, and to study the degree to which species perform adaptive developmental plasticity reactions [61,62]. Embryos and larvae are highly sensitive to the influences of environmental variables, such as temperature, oxygen concentration, salinity, water chemistry, turbidity and cues of predator presence, which may alter metabolic and developmental rates with a major effect on life history trajectories. Research into the breadth of reaction norms of traits to environmental stressors is in its infancy and needs to be conducted across conspecific populations.
The effects of the rapidly warming climate are presently of particular interest [63,64,65]. To what degree can species adapt genetically to a warmer habitat, and to what degree do they have short-term plastic life history responses developed in the past, which cause phenotypic changes making them more able to cope with the warming? Do they have adequate phenotypic mechanisms that dampen negative effects, and if so, how are these regulated by genetic and/or epigenetic mechanisms, and what are the limits of the adaptations? The limits may well vary among conspecific populations depending on their past history, but this has not yet been much studied.
Is there a relationship between developmental rate and the sensitivity to a warmer climate? Wang et al. [66] found by studying the literature that demersal and reef fish were more sensitive to a warmer climate than pelagic fish. They also found that slowly developing and long-lived fish were less sensitive to a warmer climate than faster developing, short-lived fish. To what degree are there general relationships between habitat use, life histories and the vulnerability to climate change? Are there universal laws that can be found?
Climate warming changes species ranges both horizontally and vertically towards colder water in search of a thermally optimal habitat [67]. However, feeding opportunities at higher latitudes or at greater depth may be poorer resulting in slower growth rate and smaller adult size, and may change age at maturity. Because of climate change, the strength and direction of ocean currents may be adjusted and nfluence the distribution of pelagic fish larvae, and if so, will the need for early feeding match with the opportunities to feed? This may affect local food webs. The match–mismatch hypothesis of larval presence relative to feeding opportunities is a prevailing theory for year-class variation in abundance of fish [68,69], and a mismatch is a likely outcome of climate warming.
Among anthropogenic stressors are size-selective fishing and the introduction of predatory fish variables that affect the life histories of fish [70]. With a growing human demand for fish protein, many populations are over-harvested and the life history effects of this can be strong [71], but more research is needed to see the full spectra of effects of these human actions.

Funding

The author has received no external funding.

Acknowledgments

My sincere thanks go to all authors who have contributed to the Special Issue.

Conflicts of Interest

The author declares no conflicts of interest.

References

  1. Endler, J.A. Natural Selection in the Wild; Princeton University Press: Princeton, NJ, USA, 1986. [Google Scholar]
  2. Dobson, F.S. A lifestyle view of life-history evolution. Proc. Natl. Acad. Sci. USA 2007, 104, 17565–17566. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  3. Write, S. The roles of mutation, inbreeding and selection in evolution. Proc. Int. Congr. Genet. 1932, 6, 356–366. [Google Scholar]
  4. Cole, L. The population, consequences of life history phenomena. Q. Rev. Biol. 1954, 29, 103–137. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  5. Hamilton, W.D. The moulding of senescence by natural selection. J. Theor. Biol. 1966, 12, 12–45. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  6. Schaffer, W.M. Optimal reproductive effort in fluctuating environments. Am. Nat. 1974, 108, 783–790. [Google Scholar] [CrossRef] [Scilit]
  7. Gadgil, M.; Bossert, W.H. Life history consequences of natural selection. Am. Nat. 1970, 104, 1–24. [Google Scholar] [CrossRef] [Scilit]
  8. Smith, C.C.; Fretwell, S.D. The optimal balance between size and number of offspring. Am. Nat. 1974, 108, 499–506. [Google Scholar] [CrossRef] [Scilit]
  9. Stearns, S.C. The Evolution of Life Histories; Oxford University Press: London, UK, 1992. [Google Scholar]
  10. Fox, C.W.; Roff, D.A.; Fairbairn, D.J. (Eds.) Evolutionary Ecology: Concepts and Case Studies; Oxford University Press: New York, NY, USA, 2001. [Google Scholar]
  11. Van Dyke, F.; Lamb, R.L. Conservation Biology: Foundations, Concepts, Applications, 3rd ed.; Springer: Cham, Switzerland, 2020. [Google Scholar]
  12. Stearns, S.C. The evolution of life-history traits in mosquitofish since their introduction to Hawaii in 1905—Rates of evolution, heritabilities, and developmental plasticity. Am. Zool. 1983, 23, 65–75. [Google Scholar] [CrossRef] [Scilit]
  13. Jonsson, B.; Hindar, K.; Northcote, T.G. Optimal age at sexual maturity of sympatric and experimentally allopatric cutthroat trout and Dolly Varden charr. Oecologia 1984, 61, 319–325. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  14. Catalán, I.A.; Reglero, P.; Álvarez, I. Research on early life stages of fish: A lively field. Mar. Ecol. Prog. Ser. 2020, 650, 1–5. [Google Scholar] [CrossRef] [Scilit]
  15. Mahardja, B.; Smith, W.E.; Healy, B.D.; Koizumi, C.; Nobriga, M.L.; Acuña, S.; Crawford, B.; Arend, K.K.; Runge, M.C. The effects of scientific uncertainty and values trade-offs on flow management decisions for an endangered fish. Ecosphere 2026, 17, e70558. [Google Scholar] [CrossRef] [Scilit]
  16. Schnurr, M.E.; Yin, Y.; Scott, G.R. Temperature during embryonic development has persistent effects on metabolic enzymes in the muscle of zebrafish. J. Exp. Biol. 2014, 217, 1370–1380. [Google Scholar] [PubMed]
  17. Durtsche, R.D.; Jonsson, B.; Greenberg, L.A. Thermal conditions during embryogenesis influence metabolic rates of juvenile brown trout Salmo trutta. Ecosphere 2021, 12, e03374. [Google Scholar] [CrossRef] [Scilit]
  18. Melendez, C.L.; Mueller, C.A. Effect of increased embryonic temperature during developmental windows on survival, morphology and oxygen consumption of rainbow trout (Oncorhynchus mykiss). Comp. Biochem. Physiol. A Mol. Integr. Physiol. 2021, 252, 110834. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  19. Finstad, A.G.; Jonsson, B. Effect of incubation temperature on growth performance in Atlantic salmon. Mar. Ecol. Prog. Ser. 2012, 454, 75–82. [Google Scholar] [CrossRef] [Scilit]
  20. Jonsson, B.; Greenberg, L. Egg incubation temperature influences population specific outmigration rate of juvenile brown trout Salmo trutta. J. Fish Biol. 2022, 100, 909–917. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  21. Jonsson, B.; Jonsson, N.; Finstad, A.G. Linking embryonic temperature with adult reproductive investment. Mar. Ecol. Prog. Ser. 2014, 515, 217–226. [Google Scholar] [CrossRef] [Scilit]
  22. Lema, S.C.; Luckenbach, J.A.; Yamamoto, Y.; Housh, M.J. Fish reproduction in a warming world: Vulnerable points in hormone regulation from sex determination to spawning. Philos. Trans. R. Soc. Lond. B Biol. Sci. 2024, 379, 20220516. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  23. Jonsson, B.; Jonsson, N.; Hansen, M.M. Knock-on effects of environmental factors on ectothermic vertebrates with special reference to embryo temperature. Q. Rev. Biol. 2022, 97, 95–139. [Google Scholar] [CrossRef] [Scilit]
  24. Santee, N.S.; Conwey, K.W.; Nowlin, W.H.; Smith, D.; Perkin, J.S. Alterations to water quality and quantity elicit similar stream fish functional trait responses in three North American rivers. Ecol. Ind. 2024, 169, 112917. [Google Scholar] [CrossRef] [Scilit]
  25. Chung, M.H.J.; Noble, D.W.A.; Fox, R.J.; Harrison, L.M.; Jennions, M.D. Fluctuating salinity during development impacts fish life histories. J. Anim. Ecol. 2025, 94, 1848–1865. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  26. Burton, T.; Metcalfe, N.B. Can environmental conditions experienced in early life influence future generations? Proc. Biol. Sci. 2014, 281, 20140311. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  27. Massey, M.D.; Dalzel, A.C. Parental early life environments drive transgenerational plasticity of offspring metabolism in a freshwater fish (Danio rerio). Biol. Lett. 2023, 19, 20230266. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  28. Mourier, J.; Murray, T.S.; Lennox, R.J.; Birnie-Gauvin, K. Advances in telemetry approaches and technologies applied to fish ecology and management. J. Fish Biol. 2025, 106, 1257–1259. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  29. Klimley, A.P.; Cogliati, K.M.; Kuroki, M.; Docker, M.F. A review of molecular, physiological, behavioral, and ecological studies in a special issue devoted to the movement ecology of fishes. Environ. Biol. Fish. 2022, 105, 1683–1695. [Google Scholar] [CrossRef] [Scilit]
  30. Brönmark, C.; Skov, C.; Brodersen, J.; Nilsson, P.A.; Hansson, L.A. Seasonal migration determined by a trade-off between predator avoidance and growth. PLoS ONE 2008, 3, e1957. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  31. Ciepiela, L.; Walters, A.W. Life-history variation of two inland salmonids revealed through otolith microchemistry analysis. Can. J. Fish. Aquat. Sci. 2019, 76, 1971–1981. [Google Scholar] [CrossRef] [Scilit]
  32. Hultén, K.; Chapman, B.B.; Nilsson, P.A.; Hansson, L.A.; Skov, C.; Brodersen, J.; Brönmark, C. Timing and synchrony of migration in a freshwater fish: Consequences for survival. J. Anim. Ecol. 2022, 91, 2103–2112. [Google Scholar] [CrossRef] [Scilit]
  33. Oedeix, M.; Casals, F. Why and when do freshwater fish migrate? Observations of migration patterns of the native fishes from the Iberian Peninsula (SW Europe). Limnetica 2024, 43, 9–28. [Google Scholar] [CrossRef] [Scilit]
  34. Mouritsen, H. Long-distance navigation and magnetoreception in migratory animals. Nature 2018, 558, 50–59. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  35. Sibeaux, A.; Newport, C.; Green, J.P.; Karlsson, C.; Engelmann, J.; de Perera, T.B. Taking a shortcut: What mechanisms do fish use? Comm. Biol. 2024, 7, 578. [Google Scholar] [CrossRef] [Scilit]
  36. Edwards, J.E.; Bruijse, A.D.; Winter, H.V. A multi-scale tracking approach for conserving large migratory fish in an open coastal environment. Estuar. Coast. Shelf Sci. 2024, 301, 108737. [Google Scholar] [CrossRef] [Scilit]
  37. Kurasawa, A.; Onishi, Y.; Koba, K.; Fukushima, K.; Uno, H. Sequential migrations of diverse fish community provide seasonally prolonged and stable nutrient inputs to a river. Sci. Adv. 2024, 10, eadq0945. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  38. Jonsson, B.; Jonsson, N. Migratory Atlantic salmon as vector for the transfer of energy and nutrients to freshwater environments. Freshw. Biol. 2003, 48, 21–27. [Google Scholar]
  39. Walsh, J.C.; Pendray, J.E.; Godwin, S.C.; Artelle, K.A.; Kindsvater, H.K.; Field, R.D.; Harding, J.N.; Swain, N.R.; Reynolds, J.D. Relationships between Pacific salmon and aquatic and terrestrial ecosystems: Implications for ecosystem-based management. Ecology 2020, 101, e03060. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  40. Mo, Y.; Wan, H.; Cai, Y.; Zhang, X.; Li, R.; Wang, Y. Re-establishing fish migration channel of large reservoirs in Jinsha River Basin of China by using an eco-friendly reservoir operation method. J. Hydrol. Reg. Stud. 2023, 47, 101412. [Google Scholar] [CrossRef] [Scilit]
  41. Prestes, L.; Barthem, R.; Mello-Filho, A.; Anderson, E.; Correa, S.B.; Couto, T.B.D.; Venticinque, E.; Forsberg, B.; Cañas, C.; Bentes, B.; et al. Proactively averting the collapse of Amazon fisheries based on three migratory flagship species. PLoS ONE 2022, 17, e0264490. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  42. Jonsson, B.; Jonsson, N. Partial migration: Niche shift versus sexual maturation in fishes. Rev. Fish Biol. Fish. 1993, 3, 348–365. [Google Scholar] [CrossRef] [Scilit]
  43. Chapman, B.B.; Hulthén, K.; Brodersen, J.; Nilsson, P.A.; Hansson, L.A.; Brönmark, C. Partial migration in fishes: Causes and consequences. J. Fish Biol. 2012, 81, 456–478. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  44. Iwikau, A.; Augspurger, J.; Baillie, M.A.; McCulloch, G.A.; Darestani, M.M.; King, T.M.; Closs, G.P.; Ingram, T.; Lokman, P.M.; Deangle, B.; et al. Migrating jackpot individuals fuel rapid ecotype shifts in Galaxias fishes. Nat. Comm. 2026. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  45. Jonsson, B. Diadromous and resident trout Salmo trutta: Is their difference due to genetics? Oikos 1982, 38, 297–300. [Google Scholar] [CrossRef] [Scilit]
  46. Barson, N.J.; Aykanat, T.; Hindar, K.; Baranski, M.; Bolstad, G.H.; Fiske, P.; Jacq, C.; Jensen, A.J.; Johnston, S.E.; Karlsson, S.; et al. Sex dependent dominance at a single locus maintains variation in age at maturity in salmon. Nature 2015, 528, 405–408. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  47. Pritchard, V.L.; Makinen, H.; Vaha, J.P.; Erkinaro, J.; Orell, P.; Primmer, C.R. Genomic signatures of fine-scale local selection in Atlantic salmon suggest involvement of sexual maturation, energy homeostasis and immune defence-related genes. Mol. Ecol. 2018, 27, 2560–2575. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  48. Aykanat, T.; Debes, P.V.; Jansouz, S.; Gueguen, L.; House, A.H.; Roukolainen, A.; Erkinaro, J.; Prichard, V.L.; Primmer, C.R.; Bolstad, G.H. Large effect life-history genomic regions are associated with functional morphological traits in Atlantic salmon. G3 Genes Genomes Genet. 2025, 15, jkaf106. [Google Scholar] [CrossRef] [Scilit]
  49. Bangura, P.B.; Tiira, K.; Niemela, P.T.; Erkinaro, J.; Liljeström, P.; Toikkanen, A.; Primmer, C.R. Linking vgll3 genotype and aggressive behaviour in juvenile Atlantic salmon (Salmo salar). J. Fish Biol. 2022, 100, 1264–1271. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  50. Prokkola, J.M.; Åsheim, E.R.; Morozov, S.; Bangura, P.; Erkinaro, J.; Ruokolainen, A.; Primmer, C.R.; Aykanat, T. Genetic coupling of life-history and aerobic performance in Atlantic salmon. Proc. R. Soc. Lond. B 2022, 289, 20212500. [Google Scholar] [CrossRef] [Scilit]
  51. Jonsson, B. Stunted versus normally growing fish: Adapted to different niches. Fishes 2025, 10, 376. [Google Scholar] [CrossRef] [Scilit]
  52. Skúlason, S. Life history choices of fishes in response to diverse environments. Fishes 2026, 11, 329. [Google Scholar] [CrossRef] [Scilit]
  53. Morris, D.W.; Lundberg, P. Habitat-selecting life history. Fishes 2026, 11, 55. [Google Scholar] [CrossRef] [Scilit]
  54. Weir, L.K. The influence of habitat on intra-specific variation in fish mating systems. Fishes 2026, 11, 375. [Google Scholar] [CrossRef] [Scilit]
  55. Venables, S.K.; Måuller, L.; Rohner, C.A.; Marshall, A.D.; van Rijn, J.; de Catarina, N.; Filmalter, J.D.; Daly, R. Habitat use, residency, and connectivity of bull sharks (Carcharhinus leucas) in the Bazaruto Seascape, Mozambique. Fishes 2026, 11, 291. [Google Scholar] [CrossRef] [Scilit]
  56. Yu, L.; Wang, M.; Li, J.; Zhu, F.; Yuan, Y.; Tian, H.; Liu, M.; Dong, W.; Yang, J.; Lin, C.; et al. Differences in habitat substrate preference selection among sexes and populations of Leptobotia elongata. Fishes 2026, 11, 137. [Google Scholar] [CrossRef] [Scilit]
  57. Coughlan, A.; Canning, A. The influence of rainbow trout on dwarf galaxiid habitat preferences. Fishes 2025, 10, 456. [Google Scholar] [CrossRef] [Scilit]
  58. Martens, K.D.; Devine, W.D. Stream temperature, density dependence, catchment size, and physical habitat: Understanding salmonid size variation across small streams. Fishes 2025, 10, 368. [Google Scholar] [CrossRef] [Scilit]
  59. Dziubińska, A.; Sapota, M.; Socha, E. Habitat matters: Behavior and activity of round goby (Neogobius melanostomus) at different substrates. Fishes 2025, 10, 319. [Google Scholar] [CrossRef] [Scilit]
  60. Chen, W.; Carroll, J.L.; Cook, G.S. Quantifying age and growth rates of gray snapper (Lutjanus griseus) in Mosquito Lagoon, Florida. Fishes 2025, 10, 336. [Google Scholar] [CrossRef] [Scilit]
  61. Van Buskirk, J.; Steiner, U.K. The fitness costs of developmental canalization and plasticity. J. Evol. Biol. 2009, 22, 852–860. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  62. Shamsid-Deen, M.L.; Whitney, K.D. Phenotypic Plasticity in Arabidopsis thaliana Is fitness-neutral, and costs are lacking across experimental environments. Ecol. Evol. 2026, 16, e73427. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  63. Donelson, J.M.; Sunday, J.M.; Figueira, W.F.; Gaitán-Espitia, J.D.; Hobday, A.J.; Johnson, G.R.; Leis, J.M.; Ling, S.D.; Marshall, D.; Pandolfi, J.M.; et al. Understanding interactions between plasticity, adaptation and range shifts in response to marine environmental change. Philos. Trans. R. Soc. Lond. B Biol. Sci. 2019, 374, 20180186. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  64. Vallin, J.; Gerberon, F.; Lassus, R.; Floury, M.; Maire, A.; Daufresne, M.; Sentiset, A. Rapid and reversible plasticity of upper thermal limit, but no effects of multigenerational warming in medaka. J. Therm. Biol. 2025, 130, 104155. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  65. Strowbridge, N.; Gilbert, M.J.H.; Zhang, Y.; Metzger, D.C.H.; McKenzie, J.L.; Lima, L.; Farrell, A.P.; Fangue, N.A.; Schulte, P.M. Climate warming will test the limits of thermal plasticity in rainbow trout, a globally distributed fish. Cons. Physiol. 2025, 13, coaf034. [Google Scholar] [CrossRef] [Scilit]
  66. Wang, J.; Chen, L.; Tang, W.; Heino, J.; Jiang, X. Effects of dam construction and fish invasion on the species, functional and phylogenetic diversity of fish assemblages in the Yellow River Basin. J. Environ. Manag. 2021, 293, 112863. [Google Scholar] [CrossRef] [Scilit]
  67. Hastings, R.A.; Rutterford, L.A.; Freer, J.J.; Collins, R.A.; Simpson, S.D.; Genner, M. Climate change drives poleward increases and equatorward declines in marine species. Curr. Biol. 2020, 30, 1572–1577. [Google Scholar] [CrossRef] [Scilit] [PubMed]
  68. Cushing, D.H. Plankton production and year-class strength in fish populations. In Advances in Marine Biology; Blaxter, J.H.S., Southward, A.J., Eds.; Elsevier: London, UK, 1990. [Google Scholar]
  69. Mertz, G.; Myers, R.A. Match/mismatch predictions of spawning duration versus recruitment variability. Fish. Oceanogr. 1994, 3, 236–245. [Google Scholar] [CrossRef] [Scilit]
  70. Thambithurai, D.; Kuparinen, A. Environmental forcing alters fisheries selection. Trends Ecol. Evol. 2024, 39, 131–140. [Google Scholar] [CrossRef] [Scilit]
  71. Sharpe, D.M.T.; Hendry, A.P. Life history change in commercially exploited fish stocks: An analysis of trends across studies. Evol. Appl. 2009, 2, 260–275. [Google Scholar] [CrossRef] [Scilit] [PubMed]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Jonsson, B. Habitat as a Template for Life Histories of Fish. Fishes 2026, 11, 442. https://doi.org/10.3390/fishes11080442

AMA Style

Jonsson B. Habitat as a Template for Life Histories of Fish. Fishes. 2026; 11(8):442. https://doi.org/10.3390/fishes11080442

Chicago/Turabian Style

Jonsson, Bror. 2026. "Habitat as a Template for Life Histories of Fish" Fishes 11, no. 8: 442. https://doi.org/10.3390/fishes11080442

APA Style

Jonsson, B. (2026). Habitat as a Template for Life Histories of Fish. Fishes, 11(8), 442. https://doi.org/10.3390/fishes11080442

Article Metrics

Back to TopTop