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Understanding and predicting the distribution of organisms in heterogeneous environments lies at the heart of ecology. The spatial distribution of fish populations observed in the wild results from the complex interactions of multiple controls both external or internal to the fish populations. Whilst species distribution models (SDMs) have been mostly concerned with static description of species distribution as a function of environmental constraints, models of animal movements (MAMs) have focussed on the dynamic nature of spatial distribution of groups of individuals under a number of constraints external and internal to the population. Besides SDMs and MAMs, modelling the spatial distribution of fish populations can be achieved by models that are fundamentally static (like SDMs) but can also incorporate many hypotheses on the control of fish spatial distribution (like MAMs). The hypotheses underlying these models need to make sense at the population level - rather than at the individual or species level -we term these 'population distribution models' (PDMs). PDMs are statistical models that rely on several hypotheses, which include: (i) control through geographical attachment, (ii) environmental conditions, (iii) density-dependent habitat selection, (iv) spatial dependency, (v) population demographic structure, (vi) species interactions and (vii) population memory. We review the basis behind each of these conceptual models and we examine corresponding numerical applications. We argue that the conceptual models are complementary rather than competing, that existing numerical applications are still rarely compared and combined, and that PDMs can offer a statistical framework to achieve this. We recommend that the numerical models associated with different hypotheses be constructed within such a common general framework. This will permit evaluation, comparison and combination of the multiple hypotheses on fish spatial distribution. It will ultimately lead to a more comprehensive understanding of the factors controlling the spatial distribution of fish populations and to more accurate predictions in which model uncertainty is accounted for. [ABSTRACT FROM AUTHOR]

Cadrin, S. X., Bernreuther, M., Daníelsdóttir, A. K., Hjörleifsson, E., Johansen, T., Kerr, L., Kristinsson, K., Mariani, S., Nedreaas, K., Pampoulie, C., Planque, B., Reinert, J., Saborido-Rey, F., Sigurðsson, T., and Stransky, C. 2010. Population structure of beaked redfish, Sebastes mentella: evidence of divergence associated with different habitats. – ICES Journal of Marine Science, 67: 1617–1630.Throughout their range, Sebastes spp. are adapted to a diversity of ecological niches, with overlapping spatial distributions of different species that have little or no morphological differences. Divergence of behavioural groups into depth-defined adult habitats has led to reproductive isolation, adaptive radiation, and speciation in the genus Sebastes. Recent genetic research, supported by life-history information, indicates four biological stocks of Sebastes mentella in the Irminger Sea and adjacent waters: a western stock, a deep-pelagic stock, a shallow-pelagic stock, and an Iceland slope stock. Congruent differences in fatty acids and parasites suggest that these genetically distinct populations are adapted to disparate trophic habitats in pelagic waters (shallower and deeper than the deep-scattering layer) and in demersal habitats on the continental slope. Morphology of pelagic forms is also more streamlined than demersal forms. Although genetic differences and evidence for reproductive isolation are clear, these populations appear to share common nursery habitats on the Greenland shelf. We propose a redefinition of practical management units near the Irminger Sea based on geographic proxies for biological stocks and minimizing mixed-stock catches according to the spatial patterns of the recent fishery. [ABSTRACT FROM PUBLISHER]

Modelling habitat of species necessitates robust identification of relevant environmental variables linked to species distribution. To achieve this, we connect hierarchical patch theory and habitat modelling at multiple scales. We suggest discriminating between ‘circumstancial variables’ and ‘process variables’ on the basis of temporal evolution of the spatial links between species distribution and their environment at different scales. ‘Process variables’ are informative of the ecological processes driving the distribution of organisms at multiple scales. By opposition, ‘circumstantial variable’ provide little insight because their relationship with animal spatial distribution is subject to great variations through time. As a real case study, we investigate the relationships between auk distribution (mainly Uria aalge) and oceanographic landscapes over two scales (i.e. large ∼ 200 km and medium ∼ 50 km) during the wintering season in the Bay of Biscay. Surface salinity, mixed layer depth and chlorophyll a are identified as ‘process variables’ as they are invariably correlated with the spatial distribution of auks, whereas bottom temperature can be viewed as a ‘circumstantial variable’ since the correlation is non-constant through time at large scale. The process variables at large scale are used to model the potential habitat of auks in the Bay of Biscay during the wintering season. At medium scale, only the chlorophyll a is identified as ‘process variable’ and used to model preferential habitat of wintering auks in the Bay of Biscay. The analytical approach proposed here (i.e. multivariate factorial kriging in a temporal context) is an effective framework to model the potential and preferential habitat of a species and can be related to the ecological niche concept and by focusing explicitly on scale dependence, the distinction between the variables that can be used as niche descriptors into species distribution models. Then our method lead to the identification of variables that should be used to define the Grinnellian niche which is defined by environmental conditions on broad scales and the Eltonian niche which focuses on biotic interactions and resource–consumer dynamics that can be measured principally at local scales. [ABSTRACT FROM AUTHOR]

Large amplitude variations in recruitment of small pelagic fish result from interactions between a fluctuating environment and population dynamics processes such as spawning. The spatial extent and location of spawning, which is critical to the fate of eggs and larvae, can vary strongly from year to year, as a result of changing population structure and environmental conditions. Spawning habitat can be divided into ‘potential spawning habitat’, defined as habitat where the hydrographic conditions are suitable for spawning, ‘realized spawning habitat’, defined as habitat where spawning actually occurs, and ‘successful spawning habitat’, defined as habitat from where successful recruitment has resulted. Using biological data collected during the period 2000–2004, as well as hydrographic data, we investigate the role of environmental parameters in controlling the potential spawning habitat of anchovy and sardine in the Bay of Biscay. Anchovy potential spawning habitat appears to be primarily related to bottom temperature followed by surface temperature and mixed-layer depth, whilst surface and bottom salinity appear to play a lesser role. The possible influence of hydrographic factors on the spawning habitat of sardine seems less clear than for anchovy. Modelled relationships between anchovy and sardine spawning are used to predict potential spawning habitat from hydrodynamical simulations. The results show that the seasonal patterns in spawning are well reproduced by the model, indicating that hydrographic changes may explain a large fraction of spawning spatial dynamics. Such models may prove useful in the context of forecasting potential impacts of future environmental changes on sardine and anchovy reproductive strategy in the north-east Atlantic. [ABSTRACT FROM AUTHOR]

The spatial extent of small pelagic fish spawning habitat is influenced by environmental factors and by the state of the adult population. In return, the configuration of spawning habitat affects recruitment and therefore the future structure of the adult population. Interannual changes in spatial patterns of spawning reflect variations in adult population structures and their environment. The present study describes the historical changes in the spatial distribution of spawning of anchovy ( Engraulis encrasicolus) and sardine ( Sardina pilchardus) in the Bay of Biscay during two periods: 1967–72 and 2000–2004. Using data from egg surveys conducted in spring, the spatial distributions of anchovy and sardine eggs are characterized by means of geostatistics. For each survey, a map of probability of egg presence is constructed. The maps are then compared to define (1) recurrent spawning areas, (2) occasional spawning areas and (3) unfavourable spawning areas during each period. Sardine spawning habitat is generally fragmented and appears spatially limited by the presence of cold bottom water. It is confined to coastal or shelf break refuge areas in years of restricted spawning extent. For anchovy, recurrent spawning sites are found in Gironde and Adour estuaries whilst spawning can extend further offshore in years of more intense spawning. For both species, the mean pattern of spawning has changed between 1967–72 and 2000–2004. Noticeably, the spatial distribution of anchovy eggs in spring has expanded northward. This trend possibly results from changes in environmental conditions during the last four decades. [ABSTRACT FROM AUTHOR]