| Literature DB >> 30897150 |
Sahira Y Bell1,2, Matthew W Fraser1, John Statton1, Gary A Kendrick1.
Abstract
The role of environmental-stress gradients in driving trophic processes like grazing, has potential to shape ecosystem responses to environmental change. In subtidal seagrass systems, however, the variation in top-down processes along stress gradients are poorly understood. We deployed herbivory assays using the five most common seagrassEntities:
Mesh:
Year: 2019 PMID: 30897150 PMCID: PMC6428295 DOI: 10.1371/journal.pone.0214308
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Fig 1Location of six study sites and coastal town of Denham in relation to the salinity gradient in Shark Bay, Western Australia.
Sites recorded the following average salinities in situ (north to south): 1 = 38 PSU, 2 = 39 PSU, 3 = 41 PSU, 4 = 44 PSU, 5 = 48 PSU and 6 = 51 PSU. Salinity contour lines are redrawn from Walker (1985) and are represented by solid black lines. Insert shows the location of Shark Bay relative to the rest of Western Australia.
Summary of the extent of the five most abundant seagrasses of Shark Bay, Western Australia, to a range of environmental conditions.
Table has been adapted from Walker et al. (1988).
| Species | Depth (m) | Salinity (‰) | Notes |
|---|---|---|---|
| 0–14 | 35–55 | On bands and channels | |
| 0–15 | 32–62.4 | Found under all conditions | |
| 0–14 | 38–50 | In sand patches or as understory | |
| Intertidal-14 | 35–64 | In sand flats or as understory | |
| Intertidal-14 | 35–55 | On sand flats or edge of banks |
Fig 2(a) Image of a deployed herbivory assay. NB: that pink flagging tape observed in the image was removed after assay deployment. Photo credit: Sahira Bell. (b) Schematic representation of herbivory assay deployment in situ. Schematic is not to scale.
Fig 3(a) Halodule uninervis, (b) Halophila ovalis, (c) Cymodocea angustata, (d) Posidonia australis and (e) Amphibolis antarctica leaves with signs of herbivory after being deployed for a period of 24 hrs. Images are not set to the same scale for bite mark clarity. Photo credit: Sahira Bell.
Results of ANOVA examining the total leaf biomass removed in summer and winter in response to Salinity (Sa), Species (Sp) and Season (Se).
Significant P values are highlighted in bold.
| Factor | F-value | ||
|---|---|---|---|
| Salinity | 5 | 77.25 | |
| Species | 4 | 16.25 | |
| Season | 1 | 21.74 | |
| Sa x Sp | 17 | 11.92 | |
| Sa x Se | 3 | 7.09 | 0.06 |
| Sp x Se | 3 | 3.63 | |
| Sa x Sp x Se | 5 | 3.92 | 0.619 |
Fig 4Proportion of leaf biomass removed in summer (left) and winter (right) for the five most common seagrass species of Shark Bay, Western Australia.
Seagrass species are arranged along the x-axis according to leaf turnover rates from the slowest to the fastest species. Median (horizontal line), first and third quartile (hinges) and 95% confidence intervals (notches) are shown. Letters correspond to significant differences in biomass removed (Tukey HSD).
Fig 5Seagrass leaf biomass removed (%) during summer (top) and winter (bottom) for the five most common seagrass species of Shark Bay, Western Australia.
Lines (blue) represent linear regression.
Average nutrient content by weight for each of the five sampled seagrass species.
Note that lower nutrient ratio values indicate species of greater quality i.e. higher relative N or P content.
| Species | C:N | C:P |
|---|---|---|
| 20.4 | 311.5 | |
| 23.2 | 373.9 | |
| 14.6 | 213.9 | |
| 18.4 | 231.6 | |
| 17.6 | 126.3 |