Seascape variability may confound assessments on the effectiveness of no-take marine reserves (NTMRs) in conserving biodiversity. In most cases baseline data are lacking, resulting in evaluations of NTMR effectiveness being Control Impact (CI) assessments. Even with independent replicate areas among management zones, this approach can make it difficult to detect zone effects if seascape attributes, such as habitat structural complexity varies among experimental areas. To determine the importance of structural complexity in evaluations of NTMR effectiveness we performed assessments on the abundance of a targeted fish, yellowtail kingfish (Seriola lalandi), in the Lord Howe Island Marine Park (LHIMP). We compared assessments which did and did not account for structural complexity, quantified using high resolution multibeam bathymetry. Despite almost 3 times more S. lalandi in NTMRs, the traditional CI assessment explained only 3% of the variation in the abundance of S. lalandi and revealed no clear effect of protection. Incorporating structural complexity into the assessment increased the deviance explained to 65% and uncovered an important interaction between zone and structural complexity. Greater abundances of S. lalandi were detected in NTMRs compared to fished zones but only on highly complex reefs. By accounting for structural complexity, we demonstrate that the precision and accuracy of NTMR assessments can be improved, leading to a better understanding of ecological change in response to this conservation strategy. Consequently, where marine park zones vary greatly in structural complexity, we strongly advocate for quantifying and accounting for such variability in assessments of NTMR performance. HIGHLIGHTS 22 No-take marine reserve assessments were compared with and without habitat structure 23  Abundances of yellowtail kingfish were greater in NTMRs but only on complex reef 24  Including habitat structure increased deviance explained from 3% to 65% 25  This reduced the standard error of mean abundances in NTMRs by 40% 26  Assessment precision & accuracy improved, providing robust outcomes for 27 management 28 29 ABSTRACT 30Seascape variability may confound assessments on the effectiveness of no-take marine 31 reserves (NTMRs) in conserving biodiversity. In most cases baseline data are lacking, resulting in 32 evaluations of NTMR effectiveness being Control Impact (CI) assessments. Even with independent 33 replicate areas among management zones, this approach can make it difficult to detect zone effects if 34 seascape attributes, such as habitat structural complexity varies among experimental areas. To 35 determine the importance of structural complexity in evaluations of NTMR effectiveness we 36 performed assessments on the abundance of a targeted fish, yellowtail kingfish (Seriola lalandi), in 37 the Lord Howe Island Marine Park (LHIMP). We compared assessments which did and did not 38 account for structural complexity, quantified using high resolution multibeam bathymetry. Despite 39 almost 3 time...

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Christmas Island is situated in the tropical eastern Indian Ocean on a biogeographic border where Indian and Pacific Ocean faunas meet. Detailed field studies in 2004, 2007 and 2008, of the island’s fish fauna revealed 30 new records from 15 families. For six families (Dasyatidae, Chanidae, Bramidae, Mugilidae, Siganidae, Molidae) this is the first time a species has been recorded at Christmas Island. Many of the newly recorded fishes appear to have recently colonised the island, and establishing populations will be dependent on the availability of suitable habitat and conspecific mates. These new records illustrate that Christmas Island is important for range expansion because it serves as a critical stepping-stone in the dispersal of Pacific Ocean species into the Indian Ocean and vice versa. Contact between Indian and Pacific Ocean sister species has also resulted in hybridisation at Christmas Island.

Active acoustic tracking suggests that soft sediment fishes can show site attachment: a preliminary assessment of the movement patterns of the blue-spotted flathead (Platycephalus caeruleopunctatus) Fetterplace et al. Animal Biotelemetry Fetterplace et al. Anim Biotelemetry (2016) AbstractBackground: It is generally considered that on relatively homogenous marine soft sediment habitats, such as sand, fish are unlikely to show site attachment. This poses challenges for management and the evaluation of the efficacy of marine protected areas, in which soft sediments often make up more than 70 % of habitats. The blue-spotted flathead is a commercially and recreationally targeted species found on soft sediments in coastal marine waters of southeastern Australia. There are no published data on its movement patterns. Here, using active acoustic telemetry, we aim to (a) quantify movement and habitat use of blue-spotted flathead, (b) compare area usage to no-take sanctuary zone size and (c) obtain data to aid in the design of a large passive receiver array to be used in long-term comprehensive tracking of soft sediment fish. Results:Three of five blue-spotted flathead that were tagged exhibited strong site attachment and were detected close to their release points for the entire 60-day study period. The two other fish were not detected after 4 and 25 days and were likely to have moved out of the study area (search radius ≈ 3 km). For the three fish tracked over 60 days, the area used was compact (mean ± SE = 0.021 km 2 ± 0.037) and two patterns of movement were apparent: (1) a small activity space used in its entirety each day (two fish) and (2) a larger activity space in which a separate area is utilised each day (one fish). Conclusions:Our study is the first to document the movement of blue-spotted flathead, and these preliminary results demonstrate two broad movement patterns shown by this species on soft sediments in Jervis Bay. Over the course of 60 days, a majority of fish in this study showed strong site attachment; however, a number of fish also made larger-scale movements. Finally, our study suggests that a tightly spaced, passive acoustic array would provide meaningful results for this species, although strategically placed receivers outside this array would be required to detect any longer range movements.

Effective conservation planning requires biotic data across an entire region. In data-poor ecosystems conservation planning is informed by using environmental surrogates (e.g. temperature) predominantly in two ways: to develop habitat classification schemes (1) or develop species distribution models (2). We test the utility of both approaches for conservation planning of marine ecosystems, and rank environmental surrogates, such as depth and distance from shore, according to their power to predict the distribution and abundance of biotic species. Specifically, we compared a habitat classification scheme; based on coarse levels of habitat types derived from depth and distance from shore; against species distribution models, which predict fish abundance and prevalence as a function of environmental surrogates (depth, distance from shore, latitude, reef area, zoning, and several metrics of habitat structural complexity). We consistently set conservation target levels to 21% of each conservation feature, following global standards and a sensitivity analyses. Thus when running scenarios to protect fish species we aimed to protect at least 21% of each species, and when running scenarios of habitat classes, we aimed to protect at least 21% of each habitat class. We found that when aiming to protect 21% of the chosen conservation targets, distribution models protected 21% of the predicted abundance/occurrence of all modelled species and functional groups, but did not protect most habitats. Contrastingly, using a habitat classification scheme protected 21% of all habitat types and 34% of all species and functional groups, but required protecting three times more area. Thus, using only distribution models as targets in data-poor ecosystems could be a risky conservation planning strategy. Ultimately the best conservation outcomes were achieved by incorporating local knowledge to synthesize the conservation outcomes of both scenarios.