| Literature DB >> 30425264 |
Ashley M Fowler1, Rowan C Chick2, John Stewart3.
Abstract
Knowledge of connectivity and population structure is integral to the sustainable management of fished populations, yet such information is unavailable for many species over scales relevant to their exploitation. We examined broad-scale patterns and drivers of adult movement for a putatively mobile carangid (Pseudocaranx georgianus) on Australia's southeast coast using an angler tag-recapture dataset. More than 6300 individuals were tagged and released across 1007 km of coastline, with anglers recapturing 157 (2.48%) individuals during a 14-year period. Median distance moved was 5 km and a substantial proportion of individuals (19%) were recaptured at their release location. Recapture latitude was also strongly predicted by release latitude (r2 = 0.87). However, a broad range of movements were observed (0-508 km), with 6% of individuals moving further than 100 km. Most individuals recaptured in areas now designated as Marine Protected Areas (MPAs) were originally released in the same area (79.2%). Larger body size, longer periods at liberty, and releases during Spring all positively influenced distance moved. Results support restricted movement over an intermediate scale, punctuated by occasional large movements. Our findings suggest adult movement of P. georgianus in southeastern Australia primarily occurs over smaller distances than the current spatial scale of management.Entities:
Mesh:
Year: 2018 PMID: 30425264 PMCID: PMC6233199 DOI: 10.1038/s41598-018-34922-6
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Map of Australia’s southeast coast indicating the proportion of releases (black bars) and recaptures (white bars) of Pseudocaranx georgianus across southern latitudes. White lines on the map delineate state borders.
Figure 2Distribution of distances moved (km) for Pseudocaranx georgianus across latitudes.
Figure 3Largest movements of Pseudocaranx georgianus recorded along the NSW coast. These movements were undertaken by nine individuals (6%) and ranged between 119 and 508 km. White lines on the map delineate state borders.
The best model candidates for (a) the odds of movement (‘yes’ or ‘no’) and (b) the distance moved (km) selected using AICc.
| Model | df | AICc | ∆AICc | Weight | Null deviance | Deviance explained (%) |
|---|---|---|---|---|---|---|
|
| ||||||
| ~Days | 2 | 147.6 | 0.00 | 0.41 | 154.7 | 7.2 |
| ~Latitude + Days | 3 | 148.4 | 0.77 | 0.28 | 154.7 | 8.0 |
| ~Days + Length | 3 | 149.4 | 1.80 | 0.16 | 154.7 | 7.4 |
| ~Latitude + Days + Length | 4 | 149.6 | 1.91 | 0.16 | 154.7 | 8.7 |
|
| ||||||
| ~Days + Length + Season | 7 | 982.92 | 0 | 0.48 | 181.6 | 28.2 |
| ~Days + Direction + Length + Season | 8 | 983.86 | 0.94 | 0.30 | 183.3 | 29.0 |
| ~Days + Latitude + Length + Season | 8 | 984.49 | 1.58 | 0.22 | 182.5 | 28.6 |
Binary logistic models were used to model the odds of movement, while negative binomial models were used to model the distance moved. df indicates the number of model parameters.
Model-averaged coefficients for models of (a) the odds of movement and (b) the distance moved (km).
| Model term | Estimate | Confidence interval | |
|---|---|---|---|
| 2.5% | 97.5% | ||
|
| |||
| (Intercept) | 0.212 | 0.000 | 400.439 |
| Days | 1.004 | 1.001 | 1.008 |
| Latitude | 1.067 | 0.860 | 1.324 |
| Length | 1.005 | 0.977 | 1.034 |
|
| |||
| (Intercept) | 3.312 | 0.085 | 129.454 |
| Days | 1.001 | 1.000 | 1.002 |
| Length | 1.035 | 1.013 | 1.056 |
| SeasonSpring | 2.022 | 1.055 | 3.874 |
| SeasonSummer | 1.458 | 0.683 | 3.112 |
| SeasonWinter | 0.510 | 0.270 | 0.964 |
| DirectionS | 1.087 | 0.763 | 1.547 |
| Latitude | 1.017 | 0.919 | 1.124 |
Estimates are back-transformed values indicating (a) odds ratios of movement, and (b) multiplicative effects on the distance moved. If confidence intervals include 1, there is no significant effect of the model term on the dependent variable at the 0.05 level.