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Ecological drivers of shark distributions along a tropical coastline.

Yates PM, Heupel MR, Tobin AJ, Simpfendorfer CA - PLoS ONE (2015)

Bottom Line: In particular, turbid environments were especially important for all species at typical oceanic salinities.Mangrove proximity, depth, and water temperature were also important; however, their influence varied between species.Ecological drivers may promote spatial diversity in habitat use along environmentally heterogeneous coastlines and may therefore have important implications for population resilience.

View Article: PubMed Central - PubMed

Affiliation: Centre for Sustainable Tropical Fisheries and Aquaculture and College of Marine and Environmental Sciences, James Cook University, Townsville, Queensland, Australia.

ABSTRACT
As coastal species experience increasing anthropogenic pressures there is a growing need to characterise the ecological drivers of their abundance and habitat use, and understand how they may respond to changes in their environment. Accordingly, fishery-independent surveys were undertaken to investigate shark abundance along approximately 400 km of the tropical east coast of Australia. Generalised linear models were used to identify ecological drivers of the abundance of immature blacktip Carcharhinus tilstoni/Carcharhinus limbatus, pigeye Carcharhinus amboinensis, and scalloped hammerhead Sphyrna lewini sharks. Results indicated general and species-specific patterns in abundance that were characterised by a range of abiotic and biotic variables. Relationships with turbidity and salinity were similar across multiple species, highlighting the importance of these variables in the functioning of communal shark nurseries. In particular, turbid environments were especially important for all species at typical oceanic salinities. Mangrove proximity, depth, and water temperature were also important; however, their influence varied between species. Ecological drivers may promote spatial diversity in habitat use along environmentally heterogeneous coastlines and may therefore have important implications for population resilience.

No MeSH data available.


Modelled relationships between the abundance of immature pigeye sharks and highly influential variables in longline (A) and gill-net (B, C) samples.Shading represents 95% confidence intervals and points are partial residuals. Effects were plotted with additional variables held at their medians. To visualise interactions, cross-sections were taken at the 10th, 50th and 90th percentiles of the second variable of interest. The plotted longline model had dispersion statistic = 1.00 and negative binomial variance parameter k = 0.13. The plotted gill-net model had dispersion statistic = 0.84 and k = 0.11. Note that low values of secchi depth indicate high turbidity.
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pone.0121346.g005: Modelled relationships between the abundance of immature pigeye sharks and highly influential variables in longline (A) and gill-net (B, C) samples.Shading represents 95% confidence intervals and points are partial residuals. Effects were plotted with additional variables held at their medians. To visualise interactions, cross-sections were taken at the 10th, 50th and 90th percentiles of the second variable of interest. The plotted longline model had dispersion statistic = 1.00 and negative binomial variance parameter k = 0.13. The plotted gill-net model had dispersion statistic = 0.84 and k = 0.11. Note that low values of secchi depth indicate high turbidity.

Mentions: Coefficients are on the linear (log) scale and so their effect is additive. Variables are listed according to mean RVI across species/sampling-method combinations. Asterisks denote variables that were not significant in model averaging but were significant (P < 0.05*; P < 0.0001**) in a single model containing only high-RVI variables. Although the coefficients for turbidity for pigeye and scalloped hammerhead sharks were positive, strong interaction with salinity or depth produced an overall negative relationship with decreasing turbidity (Fig. 5; Fig. 6).


Ecological drivers of shark distributions along a tropical coastline.

Yates PM, Heupel MR, Tobin AJ, Simpfendorfer CA - PLoS ONE (2015)

Modelled relationships between the abundance of immature pigeye sharks and highly influential variables in longline (A) and gill-net (B, C) samples.Shading represents 95% confidence intervals and points are partial residuals. Effects were plotted with additional variables held at their medians. To visualise interactions, cross-sections were taken at the 10th, 50th and 90th percentiles of the second variable of interest. The plotted longline model had dispersion statistic = 1.00 and negative binomial variance parameter k = 0.13. The plotted gill-net model had dispersion statistic = 0.84 and k = 0.11. Note that low values of secchi depth indicate high turbidity.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4390147&req=5

pone.0121346.g005: Modelled relationships between the abundance of immature pigeye sharks and highly influential variables in longline (A) and gill-net (B, C) samples.Shading represents 95% confidence intervals and points are partial residuals. Effects were plotted with additional variables held at their medians. To visualise interactions, cross-sections were taken at the 10th, 50th and 90th percentiles of the second variable of interest. The plotted longline model had dispersion statistic = 1.00 and negative binomial variance parameter k = 0.13. The plotted gill-net model had dispersion statistic = 0.84 and k = 0.11. Note that low values of secchi depth indicate high turbidity.
Mentions: Coefficients are on the linear (log) scale and so their effect is additive. Variables are listed according to mean RVI across species/sampling-method combinations. Asterisks denote variables that were not significant in model averaging but were significant (P < 0.05*; P < 0.0001**) in a single model containing only high-RVI variables. Although the coefficients for turbidity for pigeye and scalloped hammerhead sharks were positive, strong interaction with salinity or depth produced an overall negative relationship with decreasing turbidity (Fig. 5; Fig. 6).

Bottom Line: In particular, turbid environments were especially important for all species at typical oceanic salinities.Mangrove proximity, depth, and water temperature were also important; however, their influence varied between species.Ecological drivers may promote spatial diversity in habitat use along environmentally heterogeneous coastlines and may therefore have important implications for population resilience.

View Article: PubMed Central - PubMed

Affiliation: Centre for Sustainable Tropical Fisheries and Aquaculture and College of Marine and Environmental Sciences, James Cook University, Townsville, Queensland, Australia.

ABSTRACT
As coastal species experience increasing anthropogenic pressures there is a growing need to characterise the ecological drivers of their abundance and habitat use, and understand how they may respond to changes in their environment. Accordingly, fishery-independent surveys were undertaken to investigate shark abundance along approximately 400 km of the tropical east coast of Australia. Generalised linear models were used to identify ecological drivers of the abundance of immature blacktip Carcharhinus tilstoni/Carcharhinus limbatus, pigeye Carcharhinus amboinensis, and scalloped hammerhead Sphyrna lewini sharks. Results indicated general and species-specific patterns in abundance that were characterised by a range of abiotic and biotic variables. Relationships with turbidity and salinity were similar across multiple species, highlighting the importance of these variables in the functioning of communal shark nurseries. In particular, turbid environments were especially important for all species at typical oceanic salinities. Mangrove proximity, depth, and water temperature were also important; however, their influence varied between species. Ecological drivers may promote spatial diversity in habitat use along environmentally heterogeneous coastlines and may therefore have important implications for population resilience.

No MeSH data available.