Reconstructing the realized niche of phytoplankton species from environmental data: fitness versus abundance approach

Abstract

The classification of the ecological niche and the grouping of species into generalists and specialists are established ecological concepts. In this study, we compare two methods for the calculation of the realized ecological niche from long-term species data. As the first method, we present a new approach to reconstruct the realized niche not in terms of abundance but via a measure of fitness (optimal niche), which we call the Optimal Niche Estimate (ONE). The second method, the outlying mean index (OMI) analysis, is performed with abundance data for calculating the ecological niche. We demonstrate and discuss differences between methods by applying them to time series of three phytoplankton species from the Helgoland Roads long-term data set: Ceratium fusus, Odontella regia, and Paralia sulcata.

Changes in the phytoplankton community at Helgoland, North Sea: lessons from single spot time series analyses

“…As recently pointed out by Grüner et al (2011), the so far existing methods of niche reconstruction weigh environmental factors with species' abundance. This, however, is misleading since the peaks of a bloom often reflect senescence and rapid physiological change.…”

“…Finally, to separate small from intermediate and the latter from large niches, we tested the statistical significance via a Monte Carlo resampling method. A more detailed description of the method can be found in Grüner et al (2011).…”

“…This in turn is closer to the inflection point than to the peak of an abundance time series. To detect changes in the fitness-based realized niche of phytoplankton, we employed a recently published method (Grüner et al 2011). This method, the optimal niche estimate (ONE), determines the niche of single phytoplankton species via a multivariate statistical analysis of environmental factors.…”

Projecting effects of climate change on marine systems: is the mean all that matters?

“…Furthermore, it is difficult to imagine that environmental conditions can be better on days with lower growth rates. The approach of Grü ner et al [20] used more than one environmental variable, and of course, it could be the case that not all of the environmental variables are optimal at the point of highest population growth, however, there is no real way to correct for this.…”

“…Subsequently, we used these data to establish the temperature where population growth of the different algal species was maximal. For this, we computed the inflection points of the ascending part of the smoothed abundance curves of every bloom, using the method described by Grü ner et al [20]. Net population growth rates are highest at this inflection point, thus, we propose that the growing conditions for the taxon are optimal on this day.…”