Estimating density of forest bats and their long-term trends in a climate refuge.

For many species, estimating density is challenging, but it is important for conservation planning and understanding the functional role of species. Bats play key ecological roles, yet little is known about their free-ranging density. We used a long-term banding study of four species caught in an extensively forested climate refuge and spatial capture-recapture models (SCR) to estimate density and its change over time. Between 1999 and 2020, there were 3671 captures of four bat species, which were all edge-space foragers. Recaptures represented 16% (n = 587) of all captures, of which 89 were between-trap-cluster movements. Closed spatial mark-recapture models estimated plausible densities that varied with elevation. Preferred elevations differed between species, with density averaging 0.63 ha-1 for Vespadelus darlingtoni (high elevation), 0.43 ha-1 for V. pumilus (low elevation), 0.19 ha-1 for Chalinolobus morio (high elevation), and 0.08 ha-1 for V. regulus (high elevation). Overall, densities were higher than most previous published estimates for bats. Forest disturbance history (past timber harvesting) had no detectable effect on density. Density also varied substantially across years, and although annual maximum temperature and rainfall were not supported in models, some time periods showed an apparent relationship between density and annual rainfall (+ve) and/or annual maximum temperature (-ve). The most notable change was an increase in the density of V. pumilus after 2013, which tracked an increase in annual temperature at the site, reflecting a warming climate. Bat densities in forests outside of climate refugia are likely to be more sensitive to climate change, but more studies are needed in different habitats and continents and outside climate refugia to place the densities we estimated into a broader context.

Ecosystem approach to harvesting in the Arctic: Walking the tightrope between exploitation and conservation in the Barents Sea.

Projecting the consequences of warming and sea-ice loss for Arctic marine food web and fisheries is challenging due to the intricate relationships between biology and ice. We used StrathE2EPolar, an end-to-end (microbes-to-megafauna) food web model incorporating ice-dependencies to simulate climate-fisheries interactions in the Barents Sea. The model was driven by output from the NEMO-MEDUSA earth system model, assuming RCP 8.5 atmospheric forcing. The Barents Sea was projected to be > 95% ice-free all year-round by the 2040s compared to > 50% in the 2010s, and approximately 2 °C warmer. Fisheries management reference points (FMSY and BMSY) for demersal fish (cod, haddock) were projected to increase by around 6%, indicating higher productivity. However, planktivorous fish (capelin, herring) reference points were projected to decrease by 15%, and upper trophic levels (birds, mammals) were strongly sensitive to planktivorous fish harvesting. The results indicate difficult trade-offs ahead, between harvesting and conservation of ecosystem structure and function.

Shine a light: Under-ice light and its ecological implications in a changing Arctic Ocean.

The Arctic marine ecosystem is shaped by the seasonality of the solar cycle, spanning from 24-h light at the sea surface in summer to 24-h darkness in winter. The amount of light available for under-ice ecosystems is the result of different physical and biological processes that affect its path through atmosphere, snow, sea ice and water. In this article, we review the present state of knowledge of the abiotic (clouds, sea ice, snow, suspended matter) and biotic (sea ice algae and phytoplankton) controls on the underwater light field. We focus on how the available light affects the seasonal cycle of primary production (sympagic and pelagic) and discuss the sensitivity of ecosystems to changes in the light field based on model simulations. Lastly, we discuss predicted future changes in under-ice light as a consequence of climate change and their potential ecological implications, with the aim of providing a guide for future research.

Improved bathymetry leads to >4000 new seamount predictions in the global ocean - but beware of phantom seamounts!

Seamounts are important marine habitats that are hotspots of species diversity. Relatively shallow peaks, increased productivity and offshore locations make seamounts vulnerable to human impact and difficult to protect. Present estimates of seamount numbers vary from anywhere between 10,000 to more than 60,000. Seamount locations can be estimated by extracting large, cone-like features from bathymetry grids (based on criteria of size and shape). These predicted seamounts are a useful reference for marine researchers and can help direct exploratory surveys. However, these predictions are dependent on the quality of the surveys underpinning the bathymetry. Historically, quality has been patchy, but is improving as mapping efforts step up towards the target of complete seabed coverage by 2030. This study presents an update of seamount predictions based on SRTM30 PLUS global bathymetry version 11 and examines a potential source of error in these predictions. This update was prompted by a seamount survey in the British Indian Ocean Territory in 2016, where locations of two putative seamounts were visited. These 'seamounts' were targeted based on previous predictions, but these features were not detected during echosounder surveys. An examination of UK hydrographic office navigational (Admiralty) charts for the area showed that the summits of these putative features had soundings reporting 'no bottom detected at this depth' where 'this depth' was similar to the seabed reported from the bathymetry grids: we suspect that these features likely resulted from an initial misreading of the charts. We show that 15 'phantom seamount' features, derived from a misinterpretation of no bottom sounding data, persist in current global bathymetry grids and updated seamount predictions. Overall, we predict 37,889 seamounts, an increase of 4437 from the previous predictions derived from an older global bathymetry grid (SRTM30 PLUS v6). This increase is due to greater detail in newer bathymetry grids as acoustic mapping of the seabed expands. The new seamount predictions are available at https://doi.pangaea.de/10.1594/PANGAEA.921688.

The Simrad EK60 echosounder dataset from the Malaspina circumnavigation.

We provide the raw acoustic data collected from the R/V Hesperides during the global Malaspina 2010 Spanish Circumnavigation Expedition (14th December 2010, Cádiz-14th July 2011, Cartagena) using a Simrad EK60 scientific echosounder operating at 38 and 120 kHz. The cruise was divided into seven legs: leg 1 (14th December 2010, Cádiz-13th January 2011, Rio de Janeiro), leg 2 (17th January 2011, Rio de Janeiro-6th February 2011, Cape Town), leg 3 (11th February 2011, Cape Town-13th March 2011, Perth), leg 4 (17th March 2011, Perth-30th March 2011, Sydney), leg 5 (16th April 2011, Auckland-8th May 2011, Honolulu), leg 6 (13th May 2011, Honolulu-10th June 2011, Cartagena de Indias) and leg 7 (19th June 2011, Cartagena de Indias-14th July 2011, Cartagena). The echosounder was calibrated at the start of the expedition and calibration parameters were updated in the data acquisition software (ER60) i.e., the logged raw data are calibrated. We also provide a data summary of the acoustic data in the form of post-processed products.

Biogeography of the Global Ocean's Mesopelagic Zone.

The global ocean's near surface can be partitioned into distinct provinces on the basis of regional primary productivity and oceanography [1]. This ecological geography provides a valuable framework for understanding spatial variability in ecosystem function but has relevance only partway into the epipelagic zone (the top 200 m). The mesopelagic (200-1,000 m) makes up approximately 20% of the global ocean volume, plays important roles in biogeochemical cycling [2], and holds potentially huge fish resources [3-5]. It is, however, hidden from satellite observation, and a lack of globally consistent data has prevented development of a global-scale understanding. Acoustic deep scattering layers (DSLs) are prominent features of the mesopelagic. These vertically narrow (tens to hundreds of m) but horizontally extensive (continuous for tens to thousands of km) layers comprise fish and zooplankton and are readily detectable using echosounders. We have compiled a database of DSL characteristics globally. We show that DSL depth and acoustic backscattering intensity (a measure of biomass) can be modeled accurately using just surface primary productivity, temperature, and wind stress. Spatial variability in these environmental factors leads to a natural partition of the mesopelagic into ten distinct classes. These classes demark a more complex biogeography than the latitudinally banded schemes proposed before [6, 7]. Knowledge of how environmental factors influence the mesopelagic enables future change to be explored: we predict that by 2100 there will be widespread homogenization of mesopelagic communities and that mesopelagic biomass could increase by approximately 17%. The biomass increase requires increased trophic efficiency, which could arise because of ocean warming and DSL shallowing.