Repply to: Brito, A.C., Brotas, V., Caetano, M., Coutinho, T.P., Bordalo, A.A., Icely, J., Neto, J.M., Serôdio, J., Moita, T. (2012) "Defining phytoplankton class boundaries in Portuguese transitional waters: an evaluation of the ecological quality status according to the Water Framework Directive" [Ecological Indicators 19, 5-14]

We write to comment on the recently published paper “Defining phytoplankton class boundaries in Portuguese transitional waters: an evaluation of the ecological quality status according to the Water Framework Directive” (Brito et al., 2012). This paper presents an integrated methodology to analyse the ecological quality status of several Portuguese transitional waters, using phytoplanktonrelated metrics. One of the systems analysed, the Guadiana estuary in southern Portugal, is considered the most problematic estuary, with its upstream water bodies classified as Poor in terms of ecological status. We strongly disagree with this conclusion and we would like to raise awareness to some methodological constraints that, in our opinion, are the basis of such deceptive conclusions and should therefore not be neglected when using phytoplankton to assess the ecological status of natural waters.

Landscape metrics as indicators of coastal morphology and its use in ecological niche modelling of seagrass species

Dependence of some species on landscape structure has been proved in numerous studies. So far, however, little progress has been made in the integration of landscape metrics in the prediction of species associated with coastal features. Specific landscape metrics were tested as predictors of coastal shape using three coastal features of the Iberian Peninsula (beaches, capes and gulfs) at different scales. We used the landscape metrics in combination with environmental variables to model the niche and find suitable habitats for a seagrass species (Cymodocea nodosa) throughout its entire range of distribution. Landscape metrics able to capture variation in the coastline enhanced significantly the accuracy of the models, despite the limitations caused by the scale of the study. We provided the first global model of the factors that can be shaping the environmental niche and distribution of C. nodosa throughout its range. Sea surface temperature and salinity were the most relevant variables. We identified areas that seem unsuitable for C. nodosa as well as those suitable habitats not occupied by the species. We also present some preliminary results of testing historical biogeographical hypotheses derived from distribution predictions under Last Glacial Maximum conditions and genetic diversity data.