Growth performance of rhizomes has become among the most used descriptors for monitoring Posidonia oceanica seagrass dynamics and population status. However, ability to detect any change of growth in space or in time is often confounded by natural age-induced decline. To overcome this problem, we have produced reference growth charts, which in other areas are universally recognized as a very powerful tool for comparing growth of living beings during their ontogeny. Reference growth charts involving different P. oceanica growth performance measures (speed of growth and primary production of rhizomes) have been built using proper statistical frameworks (GLMM, Segmented and Quantile Regressions), based on more than 13 × 103 annual growth data recorded by lepidochronology on about 1600 shoots collected at 4-32 m depth range. Growth patterns exhibited distinct trends as regards the relationships with depth: neither speed of growth nor primary production of rhizomes depended on depth until 14 m, while at deeper stands significant linear decrease by 3.5-2.0% for 1 m increase in depth was observed. According to these results, the depth of 14 m was used as breakpoint for building two distinct sets of reference growth charts. The considerable size of the dataset allowed to estimate the accurate shapes of the percentile curves (5th, 10th, 25th, 50th, 75th, 90th, and 95th), revealing non monotonic relationships of growth performance with respect to shoot age with an initial increase followed by an overall decrease of about 40% during the following years of the explored lifespan. The accompanying model-based classification procedures described in this paper, allow to obtain comparable results also when age of shoots is largely different (up to 20 years). While this approach is flexible enough to produce satisfactory results using any growth measure (speed of growth and primary production of rhizomes, annual or cumulative), it maintains low complexity with trivial computations performed straightforwardly. The growth charts may represent a noteworthy tool for researchers involved in studying of different aspects of seagrass monitoring. It is hoped that the proposed framework will facilitate assessment of growth performance status and comparative analysis of growth data from different populations around the Mediterranean Sea.
|Numero di pagine||9|
|Stato di pubblicazione||Published - 2016|
All Science Journal Classification (ASJC) codes
- Decision Sciences(all)
- Ecology, Evolution, Behavior and Systematics