Assessing the use of marine protected areas by loggerhead sea turtles (Caretta caretta) tracked from the western Mediterranean.

Up to date 264 Marine Protected Areas (MPAs) have been declared in the western Mediterranean Sea. The management plans of 25 of these MPAs include the loggerhead sea turtle (Caretta caretta) as a priority species to protect. However, the actual use of these MPAs by the species remains unknown. Therefore, it is important to assess their contribution to loggerhead conservation in the area. To this end, satellite tracking data of 103 loggerhead turtles of varying sizes and life stages released in Spanish Mediterranean waters and Southern Tyrrhenian Sea over the 2003-2018 period were herein used. Home range and use of MPAs by tracked loggerhead turtles were analysed using post-processed state-space model locations. The tracked turtles visited several Mediterranean MPAs, but barely used them (mean percentage of monitoring time = 12.6 ± 18.2 %). There was very little overlap between turtle's core areas and tracks with the protected areas. Indeed, most of the core areas and high-density areas estimated (>85 %) were not included within any of the MPAs. Furthermore, less than 5 % of the Mediterranean MPAs were used by any tracked loggerhead sea turtles. Most of these MPAs have no protection measures that focus on this species. Loggerheads mainly use wide oceanic zones and international waters, which are difficult to protect. A high-use core area was identified for loggerhead turtles, located at the western waters of the Algerian Basin, an important fishing area outside any designated MPA and with no protection measures that focus on marine turtle conservation. We conclude that existing MPAs in the western Mediterranean may not contribute enough to loggerhead turtle conservation. We propose potential MPAs designations to be considered for loggerhead sea turtle conservation in the Mediterranean Sea at the Alboran Sea, the Algerian basin, the Northern area of the Strait of Sicily, Northeast Tunisian waters, waters around Malta, waters at the Tyrrhenian Sea and at the Ionian Sea

Priorities for Mediterranean marine turtle conservation and management in the face of climate change

As climate-related impacts threaten marine biodiversity globally, it is important to adjust conservation efforts to mitigate the effects of climate change. Translating scientific knowledge into practical management, however, is often complicated due to resource, economic and policy constraints, generating a knowledge-action gap. To develop potential solutions for marine turtle conservation, we explored the perceptions of key actors across 18 countries in the Mediterranean. These actors evaluated their perceived relative importance of 19 adaptation and mitigation measures that could safeguard marine turtles from climate change. Of importance, despite differences in expertise, experience and focal country, the perceptions of researchers and management practitioners largely converged with respect to prioritizing adaptation and mitigation measures. Climate change was considered to have the greatest impacts on offspring sex ratios and suitable nesting sites. The most viable adaptation/mitigation measures were considered to be reducing other pressures that act in parallel to climate change. Ecological effectiveness represented a key determinant for implementing proposed measures, followed by practical applicability, financial cost, and societal cost. This convergence in opinions across actors likely reflects long-standing initiatives in the Mediterranean region towards supporting knowledge exchange in marine turtle conservation. Our results provide important guidance on how to prioritize measures that incorporate climate change in decision-making processes related to the current and future management and protection of marine turtles at the ocean-basin scale, and could be used to guide decisions in other regions globally. Importantly, this study demonstrates a successful example of how interactive processes can be used to fill the knowledge-action gap between research and management.This work was conducted under FutureMares EU project that received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 869300. The Mediterranean Marine Turtle Working Group was established in 2017 and is continuously supported by MedPAN and the National Marine Park of Zakynthos. The work of AC was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “First Call for H.F.R.I. Research Projects to support Faculty members and Researchers and the procurement of high-cost research equipment grant” (Project Number: 2340).Peer reviewe

Performance assessment of two whole-lake acoustic positional telemetry systems--is reality mining of free-ranging aquatic animals technologically possible?

Acoustic positional telemetry systems (APTs) represent a novel approach to study the behaviour of free ranging aquatic animals in the wild at unprecedented detail. System manufactures promise remarkably high temporal and spatial resolution. However, the performance of APTs has rarely been rigorously tested at the level of entire ecosystems. Moreover, the effect of habitat structure on system performance has only been poorly documented. Two APTs were deployed to cover two small lakes and a series of standardized stationary tests were conducted to assess system performance. Furthermore, a number of tow tests were conducted to simulate moving fish. Based on these data, we quantified system performance in terms of data yield, accuracy and precision as a function of structural complexity in relation to vegetation. Mean data yield of the two systems was 40% (Lake1) and 60% (Lake2). Average system accuracy (acc) and precision (prec) were Lake1: acc = 3.1 m, prec = 1.1 m; Lake2: acc = 1.0 m, prec = 0.2 m. System performance was negatively affected by structural complexity, i.e., open water habitats yielded far better performance than structurally complex vegetated habitats. Post-processing greatly improved data quality, and sub-meter accuracy and precision were, on average, regularly achieved in Lake2 but remained the exception in the larger and structurally more complex Lake1. Moving transmitters were tracked well by both systems. Whereas overestimation of moved distance is inevitable for stationary transmitters due to accumulation of small tracking errors, moving transmitters can result in both over- and underestimation of distances depending on circumstances. Both deployed APTs were capable of providing high resolution positional data at the scale of entire lakes and are suitable systems to mine the reality of free ranging fish in their natural environment. This opens important opportunities to advance several fields of study such as movement ecology and animal social networks in the wild. It is recommended that thorough performance tests are conducted in any study utilizing APTs. The APTs tested here appear best suited for studies in structurally simple ecosystems or for studying pelagic species. In such situations, the data quality provided by the APTs is exceptionally high

Data from: Performance assessment of two whole-lake acoustic positional telemetry systems - is reality mining of free-ranging aquatic animals technologically possible?

Acoustic positional telemetry systems (APTs) represent a novel approach to study the behaviour of free ranging aquatic animals in the wild at unprecedented detail. System manufactures promise remarkably high temporal and spatial resolution. However, the performance of APTs has rarely been rigorously tested at the level of entire ecosystems. Moreover, the effect of habitat structure on system performance has only been poorly documented. Two APTs were deployed to cover two small lakes and a series of standardized stationary tests were conducted to assess system performance. Furthermore, a number of tow tests were conducted to simulate moving fish. Based on these data, we quantified system performance in terms of data yield, accuracy and precision as a function of structural complexity in relation to vegetation. Mean data yield of the two systems was 40 % (Lake1) and 60 % (Lake2). Average system accuracy (acc) and precision (prec) were Lake1: acc = 3.1 m, prec = 1.1 m; Lake2: acc = 1.0 m, prec = 0.2 m. System performance was negatively affected by structural complexity, i.e., open water habitats yielded far better performance than structurally complex vegetated habitats. Post-processing greatly improved data quality, and sub-meter accuracy and precision were, on average, regularly achieved in Lake2 but remained the exception in the larger and structurally more complex Lake1. Moving transmitters were tracked well by both systems. Whereas overestimation of moved distance is inevitable for stationary transmitters due to accumulation of small tracking errors, moving transmitters can result in both over- and underestimation of distances depending on circumstances. Both deployed APTs were capable of providing high resolution positional data at the scale of entire lakes and are suitable systems to mine the reality of free ranging fish in their natural environment. This opens important opportunities to advance several fields of study such as movement ecology and animal social networks in the wild. It is recommended that thorough performance tests are conducted in any study utilizing APTs. The APTs tested here appear best suited for studies in structurally simple ecosystems or for studying pelagic species. In such situations, the data quality provided by the APTs is exceptionally high

Depth sensor performance in Lake1.

<p>True depth measured in the field versus depth estimated from pressure sensors in the stationary transmitters. Solid line is the regression line, broken and dotted lines are 95% confidence and predictions intervals, respectively.</p

Apparent movement.

<p>Apparent movement per obtained position calculated as average of trial means grouped by habitat category. Standard deviation of trial means are given in brackets. N_Trial indicates number of trials yielding positions / number of trials in each habitat type.</p><p>Apparent movement.</p

Calculated positions.

<p>Calculated positions from the stationary tests before (raw data) and after (filtered data) applying the Hidden Markov Model. Green points indicate true positions of the stationary tests (N_Lake1: 90; N_Lake2: 50) and black dots indicate calculated positions. a: Lake1, raw data (N = 54.653); b: Lake1, filtered data (N = 52,015); c: Lake2, raw data (N = 44.024); d: Lake2, filtered data (N = 43,676).</p