| Literature DB >> 24349034 |
Abstract
The lack of recovery in Norwegian populations of the kelp Saccharina latissima (Linnaeus) C. E. Lane, C. Mayes, Druehl & G. W. Saunders after a large-scale disturbance that occurred sometime between the late 1990s and early 2000s has raised considerable concerns. Kelp forests are areas of high production that serve as habitats for numerous species, and their continued absence may represent the loss of an entire ecosystem. Some S. latissima populations remain as scattered patches within the affected areas, but today, most of the areas are completely devoid of kelp. The question is if natural recolonization by kelp and the reestablishment of the associated ecosystem is possible. Previous studies indicate that a high degree of reproductive synchrony in macrophytes has a positive effect on their potential for dispersal and on the connectivity between populations, but little is known about the patterns of recruitment in Norwegian S. latissima. More is, however, known about the development of fertile tissue (sori) on adult individuals, which is easily observed. The present study investigated the degree of coupling between the appearance of sori and the recruitment on clean artificial substrate beneath adult specimens. The pattern of recruitment was linked to the retreat of visible sori (i.e. spore release) and a seasonal component unrelated to the fertility of the adults. The formation and the retreat of visible sori are processes that seem synchronized along the south coast of Norway, and the link between sori development and recruitment may therefore suggest that the potential for S. latissima dispersal is relatively large. These results support the notion that the production and dispersal of viable spores is unlikely to be the bottleneck preventing recolonization in the south of Norway, but studies over larger temporal and spatial scales are still needed to confirm this hypothesis.Entities:
Mesh:
Year: 2013 PMID: 24349034 PMCID: PMC3861309 DOI: 10.1371/journal.pone.0081092
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Figure 1Summary of results from the field experiment (December 2007–May 2008).
Boxplot A shows the number of recruits observed on the tiles. Boxplot B shows sori coverage observed on the new parts of each blade, while C shows sori coverage observed on the older parts of each blade.
Hurdle model selection.
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| Which | Count | Zero | Count | Zero | Count | Zero |
| Family | Pois | Bin | Negbin | Bin | Negbin | Bin |
| Duration (D) |
| 0.154 | 0.251 | 0.154 | 0.233 | 0.154 |
| Month (M) |
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| Sori new (SN) | 0.0705 |
| 0.218 |
| 0.109 |
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| Sori old (SO) |
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| 0.065 |
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| D x M |
| 0.058 | 0.119 | 0.058 | 0.132 | 0.058 |
| SN x SO |
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| 0.613 |
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| AIC | 20833 | 5372 | 5370 | |||
Models with different error distributions were tested (Pois = Poisson, Bin = Binomial, Negbin = Negative Binomial). The Zero part of each model predicts the probability of recruitment, while the Count part predicts the number of recruits given Zero≠0. Significant P-values are indicated by bold formatting. The interactions between Month and Sori (both new and old) were not significant in any of the models. Because it had the lowest AIC value, the best model was HNb3a.
Figure 2Graphical presentation of the model predictions in relation to varying time of tile deployment, sori cover on new tissue, and sori cover on old tissue.
Different line types represent different durations of tile deployment. A, B, and C show the predicted probability of observing recruitment. D, E, and F show the predicted number of recruits where recruits are present, while G, H, and I show overall count predictions.
GLMM models of recruitment in the lab.
| Hours after initiation | <1 hrs | 1–6 hrs | >6 hrs | ||
| Interval duration | 10 min | 20 min | 30 min | 60 min | 120 min |
| Intercept (late) | 0.536 | 0.728 |
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| 0.379 |
| Season (early vs late) | 0.154 | 0.539 | 0.053 |
| 0.319 |
| Time (late) |
| 0.333 | 0.437 |
| 0.970 |
| Density (late) |
| 0.816 | 0.465 |
| 0.791 |
| Time x Season (early vs late) | 0.0506 | 0.886 | 0.411 |
| 0.792 |
| Density x Season (early vs late) | 0.8051 |
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| 0.065 | 0.407 |
| Time x Density |
| 0.208 | 0.871 |
| 0.053 |
One model was made per interval duration. The interval durations were correlated with Time because the intervals were shorter early in the experiment and subsequently longer as time progressed. After the 120 min intervals were completed (16 hours into the experiment), too little settlement was observed to perform any analysis. Season refers to early (Northern Hemisphere winter) and late (Northern Hemisphere spring) in the reproductive period. Year was included as a random factor. Significant P-values are indicated by bold formatting. Plots showing the effects of the significant parameters on the predictions are presented in the Supporting Information.
Figure 3Histogram showing the frequency of kelp recruit counts on the cover slides.