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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 blacktip sharks in gill-nets and highly influential variables.Shading represents 95% confidence intervals and points are partial residuals. Effects were plotted with additional variables held at their medians. The model containing turbidity, distance to mangroves and depth had dispersion statistic = 1.15 and negative binomial variance parameter k = 0.32. Note that low values of secchi depth indicate high turbidity.
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pone.0121346.g004: Modelled relationships between the abundance of immature blacktip sharks in gill-nets and highly influential variables.Shading represents 95% confidence intervals and points are partial residuals. Effects were plotted with additional variables held at their medians. The model containing turbidity, distance to mangroves and depth had dispersion statistic = 1.15 and negative binomial variance parameter k = 0.32. Note that low values of secchi depth indicate high turbidity.

Mentions: A total of 86 and 161 blacktip sharks were captured using longlines and gill-nets, respectively. Of these, 60 and 141 immature individuals were included in longline and gill-net analyses, respectively. For longlines, a weakly significant effect of mangrove proximity was detected (Table 4), however the explained deviance of 4% indicated that the influence of this variable was negligible. Turbidity and depth were highly influential in gill-net samples (Fig. 4; Table 4). In addition, the influence of mangrove proximity in gill-net samples corroborated the otherwise equivocal longline results. Overall, blacktip shark abundance decreased with decreasing turbidity (i.e. increasing secchi depth) and distance from mangroves, and increased with depth (Fig. 4). These three variables were present in all best-performing models (Table 3) and together explained 18% of deviance in blacktip shark abundance in gill-nets.


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 blacktip sharks in gill-nets and highly influential variables.Shading represents 95% confidence intervals and points are partial residuals. Effects were plotted with additional variables held at their medians. The model containing turbidity, distance to mangroves and depth had dispersion statistic = 1.15 and negative binomial variance parameter k = 0.32. 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.g004: Modelled relationships between the abundance of immature blacktip sharks in gill-nets and highly influential variables.Shading represents 95% confidence intervals and points are partial residuals. Effects were plotted with additional variables held at their medians. The model containing turbidity, distance to mangroves and depth had dispersion statistic = 1.15 and negative binomial variance parameter k = 0.32. Note that low values of secchi depth indicate high turbidity.
Mentions: A total of 86 and 161 blacktip sharks were captured using longlines and gill-nets, respectively. Of these, 60 and 141 immature individuals were included in longline and gill-net analyses, respectively. For longlines, a weakly significant effect of mangrove proximity was detected (Table 4), however the explained deviance of 4% indicated that the influence of this variable was negligible. Turbidity and depth were highly influential in gill-net samples (Fig. 4; Table 4). In addition, the influence of mangrove proximity in gill-net samples corroborated the otherwise equivocal longline results. Overall, blacktip shark abundance decreased with decreasing turbidity (i.e. increasing secchi depth) and distance from mangroves, and increased with depth (Fig. 4). These three variables were present in all best-performing models (Table 3) and together explained 18% of deviance in blacktip shark abundance in gill-nets.

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.