The ecological niche concept has regained interest under environmental change (e.g., climate change, eutrophication, and habitat destruction), especially to study the impacts on niche shift and conservatism. Here, we propose the within outlying mean indexes (WitOMI), which refine the outlying mean index (OMI) analysis by using its properties in combination with theK-select analysis species marginality decomposition. The purpose is to decompose the ecological niche into subniches associated with the experimental design, i.e., taking into account temporal and/or spatial subsets. WitOMI emphasize the habitat conditions that contribute (1) to the definition of species’ niches using all available conditions and, at the same time, (2) to the delineation of species’ subniches according to given subsets of dates or sites. The latter aspect allows addressing niche dynamics by highlighting the influence of atypical habitat conditions on species at a given time and/or space. Then, (3) the biological constraint exerted on the species subniche becomes observable within Euclidean space as the difference between the existing fundamental subniche and the realized subniche. We illustrate the decomposition of published OMI analyses, using spatial and temporal examples. The species assemblage’s subniches are comparable to the same environmental gradient, producing a more accurate and precise description of the assemblage niche distribution under environmental change. The WitOMI calculations are available in the open-access R package “subniche.”

Global environmental change modifies the phytoplankton community, which leads to variations in their phenology and potentially causes a temporal mismatch between primary producers and consumers. In parallel, phytoplankton community change can favor the appearance of harmful species, which makes the understanding of the mechanisms involved in structuring phytoplankton ecological niches paramount for preventing future risk. In this study, we aimed to assess for the first time the relationship between environmental conditions, phenology and niche ecology of harmful species Phaeocystis globosa and the complex Pseudo-nitzschia along the French coast of the eastern English Channel. A new method of bloom detection within a time-series was developed, which allowed the characterization of 363 blooms by 22 phenological variables over 11 stations from 1998 to 2019. The pairwise quantification of asymmetric dependencies between the phenological variables revealed the implication of different mechanisms, common and distinct between the taxa studied. A PERMANOVA helped to reveal the importance of seasonal change in the environmental and community variables. The Outlying Mean and the Within Outlying Mean indexes allowed us to position the harmful taxa niche among the rest of community and quantify how their respective phenology impacted the dynamic of their subniches. We also discussed the possible hypothesis involved and the perspective of predictive models.

The ecological niche concept has a revival interest under climate change, especially to study its impact on niche shift and/or conservatism. Here, we propose the Within Outlying Mean Indexes (WitOMI), which refines the Outlying Mean Index (OMI) analysis by using its properties in combination with the K-select analysis species marginality decomposition. The purpose is to decompose the ecological niche, into subniches associated to the experimental design, i.e. taking into account temporal or spatial subsets. WitOMI emphasizes the habitat conditions that contribute 1) to the definition of species’ niches using all available conditions and, at the same time, 2) to the delineation of species’ subniches according to given subsets of dates or sites. This latter aspect allows addressing niche dynamics by highlighting the influence of atypical habitat conditions on species at a given time or space. 3) Then, the biological constraint exerted on the species subniche becomes observable within the Euclidean space as the difference between the potential subniche and the realized subniche. We illustrate the decomposition of published OMI analysis, using spatial and temporal examples. The species assemblage’s subniches are comparable to the same environmental gradient, producing a more accurate and precise description of the assemblage niche distribution under climate change.

The ecological niche concept has a revival interest under climate change, especially to study its impact on niche shift and/or conservatism. Here, we propose the Within Outlying Mean Indexes (WitOMI), which refines the Outlying Mean Index (OMI) analysis by using its properties in combination with the K-select analysis species marginality decomposition. The purpose is to decompose the ecological niche, into subniches associated to the experimental design, i.e. taking into account temporal or spatial subsets. WitOMI emphasizes the habitat conditions that contribute 1) to the definition of species’ niches using all available conditions and, at the same time, 2) to the delineation of species’ subniches according to given subsets of dates or sites. This latter aspect allows addressing niche dynamics by highlighting the influence of atypical habitat conditions on species at a given time or space. 3) Then, the biological constraint exerted on the species subniche becomes observable within the Euclidean space as the difference between the potential subniche and the realized subniche. We illustrate the decomposition of published OMI analysis, using spatial and temporal examples. The species assemblage’s subniches are comparable to the same environmental gradient, producing a more accurate and precise description of the assemblage niche distribution under climate change.