River regulation and its influence on organic carbon dynamics, zooplankton community structure and the early life history of Murray cod in selected temperate floodplain rivers

The impacts of instream reservoirs on the origins, transformation and fate of organic resources in rivers are largely unknown. In this thesis I compare longitudinal patterns in organic carbon character and concentration (Chapter 3) and zooplankton community structure (Chapter 4) between a free-flowing and a flow regulated temperate floodplain river and investigate the influence of river regulation on carbon sources and abiotic factors supporting the growth of larval Maccullochella peelii, Murray cod (Chapter 5). Finally, these results are modelled in a conceptual framework (Chapter 6). Results demonstrate changes in character from fresh humic and microbial DOM above the reservoir, to hydrophilic DOM below the reservoir on the Broken River. Conversely, DOM showed gradual longitudinal change in the Ovens River and was dominated by fresh humic and microbial DOM and less degraded DOM (Chapter 3). Abundances of zooplankton were higher in benthic habitats than pelagic and increased longitudinally, though decreased below the reservoir on the Broken River. Both Benthic and pelagic communities responded significantly to temperature, discharge and DOM concentration. Additionally, Benthic communities responded to peak C:M and peak C:T fluorescence ratios. Inferred feeding methods of benthic zooplankton based on their response to fluorescence ratios found the Broken River proportionally greater in taxa feeding allochthonously than the Ovens River (Chapter 4). Murray cod growth rate was higher in free-flowing/lower regulation rivers than heavily regulated rivers and decreased from endogenous to exogenous feeding stages. Additionally, interaction between these factors was significant and growth rate increased with water temperature. Differences in δ13C and δ15N occurred between catchments and a trend for increasing terrestrial contributions to bulk carbon was found with increasing flow regulation (Chapter 5). Shifts seen towards degraded allochthonous carbon in flow regulated systems has affected the dynamic nature of biofilms, the continuity of zooplankton communities and potentially the feeding breadth and growth rates of drifting larval Murray Cod. As significant descriptors of these changes for many taxa, modelling temperature, discharge and organic carbon character as ‘abiotic waves’ through time may provide insights into the occurrence of optimal condition windows for these taxa across an annual river wave (Chapter 6)

Interactive Drivers of Activity in a Free-Ranging Estuarine Predator

Animal activity patterns evolve as an optimal balance between energy use, energy acquisition, and predation risk, so understanding how animals partition activity relative to extrinsic environmental fluctuations is central to understanding their ecology, biology and physiology. Here we use accelerometry to examine the degree to which activity patterns of an estuarine teleost predator are driven by a series of rhythmic and arrhythmic environmental fluctuations. We implanted free-ranging bream Acanthopagrus australis with acoustic transmitters that measured bi-axial acceleration and pressure (depth), and simultaneously monitored a series of environmental variables (photosynthetically active radiation, tidal height, temperature, turbidity, and lunar phase) for a period of approximately four months. Linear modeling showed an interaction between fish activity, light level and tidal height; with activity rates also negatively correlated with fish depth. These patterns highlight the relatively-complex trade-offs that are required to persist in highly variable environments. This study demonstrates how novel acoustic sensor tags can reveal interactive links between environmental cycles and animal behavior

Actogram representative of fish activity (acceleration) across diel and tidal periods (a; data are for fish 3 in Table 1, between the dates 20^th June 2011 and 26^th June 2011), and frequency histogram of acceleration values measured in the study (b).

<p>Tidal height (a; secondary <i>y-</i>axis) is represented by the solid black line, and grey shading indicates night and white shading indicates day.</p

Tagging information for yellowfin bream (<i>Acanthopagrus australis</i>) tracked in the Georges River, showing the numbers of days on which data were recorded during the study period, the temporal window within which these data were recorded (e.g. for Fish 1, data were recorded on 89 days within a window of 100 d), and the number of activity and depth measurements from each tag recorded by the receivers shown in Figure 1.

<p>Tagging information for yellowfin bream (<i>Acanthopagrus australis</i>) tracked in the Georges River, showing the numbers of days on which data were recorded during the study period, the temporal window within which these data were recorded (e.g. for Fish 1, data were recorded on 89 days within a window of 100 d), and the number of activity and depth measurements from each tag recorded by the receivers shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080962#pone-0080962-g001" target="_blank">Figure 1</a>.</p

Sequential model runs using a first-order auto-correlation structure, and corresponding difference in AIC values.

<p>The P-value of the term removed from each model is given, and the best model is highlighted in <b>bold</b>.</p

Optimisation of the autocorrelation function, showing the auto-regressive (AR, <i>φ</i>_n) and moving-average (MA, <i>θ</i>_n) correlation parameters for models of increasing order.

<p>The AIC for each model was used to select the model which best described the error structure (shown in <b>bold</b>). As increasing complexity failed to produce models with a lower AIC, models with more than 2 auto-regressive and 1 moving average parameters were not run <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080962#pone.0080962-Zuur1" target="_blank">[39]</a>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080962#pone.0080962-Schabenberger1" target="_blank">[44]</a>.</p