Limited differences among habitats in deep‐sea macro‐infaunal communities off New Zealand: implications for their vulnerability to anthropogenic disturbance

The spread of human activities into the deep sea may pose a high risk to benthic communities and affect ecosystem integrity. The deep sea is characterized by physical and biological heterogeneity and different habitat types are likely to differ in their vulnerability to anthropogenic impacts. However, across‐habitat comparisons are rare, and no comprehensive ecological risk assessment has yet been developed. To address this gap in our knowledge, we compared macro‐infaunal community structure in four habitats (slope, canyons, seamounts and methane seeps) at depths between 700 and 1500 m in the Hikurangi Margin and Bay of Plenty regions off New Zealand. The most striking contrast in community structure was between the two study regions, due to an order of magnitude difference in macro‐infaunal abundance that we believe was caused by differences in surface productivity and food availability at the sea bed. We found differences in structural and functional attributes of macro‐infaunal communities among some habitats in the Hikurangi Margin (slope, canyon and seep), but not in the Bay of Plenty. We posit that differences between canyon and slope communities on the Hikurangi Margin are due to enhanced food availability inside canyons compared with adjacent slope habitats. Seep communities were characterized by elevated abundance of both symbiont‐bearing and heterotrophic taxa, and were the most distinct, and variable, among the habitats that we considered on the Hikurangi Margin. Communities of seamounts were not distinct from slope or canyon communities on the Hikurangi Margin, probably reflecting similar environmental conditions in these habitats. The communities of deep‐sea canyon and seep habitats on the Hikurangi Margin were sufficiently dissimilar from each other and from slope habitats to warrant separate management consideration. By contrast, the low dissimilarity between communities of canyon and slope habitats in the Bay of Plenty suggests that habitat‐based management is not required in this region, for macro‐infauna at least. Although the two study regions share similar species pools, populations of the Hikurangi Margin region may be less vulnerable than the sparser populations of the Bay of Plenty due to the higher availability of potential colonizers and faster population growth. Thus regions, and habitats in some regions, should be subject to separate ecological risk assessment to help identify the key risks and consequences of human activities, and to inform options for reducing or mitigating impacts.     

Benthic Carbon Mineralization and Nutrient Turnover in a Scottish Sea Loch: An Integrative In Situ Study

Based on in situ microprofiles, chamber incubations and eddy covariance measurements, we investigated the benthic carbon mineralization and nutrient regeneration in a ~65-m-deep sedimentation basin of Loch Etive, UK. The sediment hosted a considerable amount of infauna that was dominated by the brittle star A. filiformis. The numerous burrows were intensively irrigated enhancing the benthic in situ O₂ uptake by ~50 %, and inducing highly variable redox conditions and O₂ distribution in the surface sediment as also documented by complementary laboratory-based planar optode measurements. The average benthic O₂ exchange as derived by chamber incubations and the eddy covariance approach were similar (14.9 ± 2.5 and 13.1 ± 9.0 mmol m^?2 day^?1) providing confidence in the two measuring approaches. Moreover, the non-invasive eddy approach revealed a flow-dependent benthic O₂ flux that was partly ascribed to enhanced ventilation of infauna burrows during periods of elevated flow rates. The ratio in exchange rates of ΣCO₂ and O₂ was close to unity, confirming that the O₂ uptake was a good proxy for the benthic carbon mineralization in this setting. The infauna activity resulted in highly dynamic redox conditions that presumably facilitated an efficient degradation of both terrestrial and marine-derived organic material. The complex O₂ dynamics of the burrow environment also concurrently stimulated nitrification and coupled denitrification rates making the sediment an efficient sink for bioavailable nitrogen. Furthermore, bioturbation mediated a high efflux of dissolved phosphorus and silicate. The study documents a high spatial and temporal variation in benthic solute exchange with important implications for benthic turnover of organic carbon and nutrients. However, more long-term in situ investigations with like approaches are required to fully understand how environmental events and spatio-temporal variations interrelate to the overall biogeochemical functioning of coastal sediments.     

Identification of Uranyl Minerals Using Oxygen K‐Edge X‐Ray Absorption Spectroscopy

Although most of the world's uranium exists as pitchblende or uraninite, this mineral can be weathered to a great variety of secondary uranium minerals, most containing the uranyl cation. Anthropogenic uranium compounds can also react in the environment, leading to spatial–chemical alterations that could be useful for nuclear forensics analyses. Soft X‐ray absorption spectroscopy (XAS) has the advantages of being non‐destructive, element‐specific and sensitive to electronic and physical structure. The soft X‐ray probe can also be focused to a spot size on the order of tens of nanometres, providing chemical information with high spatial resolution. However, before XAS can be applied at high spatial resolution, it is necessary to find spectroscopic signatures for a variety of uranium compounds in the soft X‐ray spectral region. To that end, we collected the near edge X‐ray absorption fine structure (NEXAFS) spectra of a variety of common uranyl‐bearing minerals, including uranyl carbonates, oxyhydroxides, phosphates and silicates. We find that uranyl compounds can be distinguished by class (carbonate, oxyhydroxide, phosphate or silicate) based on their oxygen K‐edge absorption spectra. This work establishes a database of reference spectra for future spatially resolved analyses. We proceed to show scanning X‐ray transmission microscopy (STXM) data from a schoepite particle in the presence of an unknown contaminant.     

Upstream—Downstream Shifts in Peak Recruitment of the Native Olympia Oyster in San Francisco Bay During Wet and Dry Years

Understanding the conditions that drive variation in recruitment of key estuarine species can be important for effective conservation and management of their populations. The Olympia oyster (Ostrea lurida) is native to the Pacific coast of North America and has been a target of conservation efforts, though relatively little information on larval recruitment exists across much of its range. This study examined the recruitment of Olympia oysters at biweekly to monthly intervals at four sites in northern San Francisco Bay from 2010 to 2015 (except 2013). Mean monthly temperatures warmed at all sites during the study, while winter (January–April) mean monthly salinity decreased significantly during a wet year (2011), but otherwise remained high as a result of a drought. A recurring peak in oyster recruitment was identified in mid-estuary, in conditions corresponding to a salinity range of 25–30 and >16 °C at the time of settlement (April–November). Higher average salinities and temperatures were positively correlated with greater peak recruitment. Interannual variation in the timing of favorable conditions for recruitment at each site appears to explain geographic and temporal variation in recruitment onset. Higher winter/spring salinities and warmer temperatures at the time of recruitment corresponded with earlier recruitment onset within individual sites. Across all sites, higher winter/spring salinities were also correlated with earlier onset and earlier peak recruitment. Lower winter salinities during 2011 also resulted in a downstream shift in the location of peak recruitment.     

Characterization,modeling, and remediation of karst in a changing environment

This introductory editorial paper provides a review and prospective outlook of the achievements and challenges in karst research under a changing environment. A brief discussion of the past and future karst research has been focused on: (1) data and new technologies; (2) modeling of karst flow and reactive transport; (3) responses of karst hydrosystems to climate variability and changes across scales.     

Characterization of fluid inclusions from mineralized pegmatites of the Damara Belt,Namibia: insight into late-stage fluid evolution and implications for mineralization

Mineralogy and Petrology - Mineralized NYF and LCT pegmatites occur throughout the northeast-trending Neoproterozoic Damara Belt, Namibia. Mineralization in the pegmatites varies geographically,...     

Estimating urban above ground biomass with multi-scale LiDAR

Background

Urban trees have long been valued for providing ecosystem services (mitigation of the “heat island” effect, suppression of air pollution, etc.); more recently the potential of urban forests to store significant above ground biomass (AGB) has also be recognised. However, urban areas pose particular challenges when assessing AGB due to plasticity of tree form, high species diversity as well as heterogeneous and complex land cover. Remote sensing, in particular light detection and ranging (LiDAR), provide a unique opportunity to assess urban AGB by directly measuring tree structure. In this study, terrestrial LiDAR measurements were used to derive new allometry for the London Borough of Camden, that incorporates the wide range of tree structures typical of an urban setting. Using a wall-to-wall airborne LiDAR dataset, individual trees were then identified across the Borough with a new individual tree detection (ITD) method. The new allometry was subsequently applied to the identified trees, generating a Borough-wide estimate of AGB.

Results

Camden has an estimated median AGB density of 51.6 Mg ha^–1 where maximum AGB density is found in pockets of woodland; terrestrial LiDAR-derived AGB estimates suggest these areas are comparable to temperate and tropical forest. Multiple linear regression of terrestrial LiDAR-derived maximum height and projected crown area explained 93% of variance in tree volume, highlighting the utility of these metrics to characterise diverse tree structure. Locally derived allometry provided accurate estimates of tree volume whereas a Borough-wide allometry tended to overestimate AGB in woodland areas. The new ITD method successfully identified individual trees; however, AGB was underestimated by ≤?25% when compared to terrestrial LiDAR, owing to the inability of ITD to resolve crown overlap. A Monte Carlo uncertainty analysis identified assigning wood density values as the largest source of uncertainty when estimating AGB.

Conclusion

Over the coming century global populations are predicted to become increasingly urbanised, leading to an unprecedented expansion of urban land cover. Urban areas will become more important as carbon sinks and effective tools to assess carbon densities in these areas are therefore required. Using multi-scale LiDAR presents an opportunity to achieve this, providing a spatially explicit map of urban forest structure and AGB.

     

Testing for similarity in area‐based spatial patterns: Alternative methods to Andresen's spatial point pattern test

Andresen's spatial point pattern test (SPPT) compares two spatial point patterns on defined areal units; it identifies areas where the spatial point patterns diverge and aggregates these local (dis)similarities to one global measure. We discuss the limitations of the SPPT and provide two alternative methods to calculate differences in the point patterns. In the first approach we use differences in proportions tests corrected for multiple comparisons. We show how the size of differences matters, as with large point patterns many areas will be identified by SPPT as statistically different, even if those differences are substantively trivial. The second approach uses multinomial logistic regression, which can be extended to identify differences in proportions over continuous time. We demonstrate these methods by identifying areas where pedestrian stops by the New York City Police Department are different from violent crimes for 2006–2016.     

MARLI: a mobile application for regional landslide inventories in Ecuador

The regions of Central and South America most susceptible to the occurrence of landslides will become even more vulnerable in the context of climate change. The Josefina disaster, in 1993, demonstrated both the vulnerability of local infrastructures and communities in the Paute River basin (Ecuador). Since this natural phenomena, several landslide inventories and susceptibility studies were developed, revealing the vulnerability of the Paute River basin to unstable terrain and the need for further studies throughout the basin. Despite this, no studies have been done since then to update the information generated. This paper describes a Mobile Application for Regional Landslide Inventories (MARLI), a simple but efficient open-access platform to report landslide events using the Open Data Kit system. Its design makes reporting fast, simple and cost-effective with an added benefit, and a specialized knowledge is not required for its use. MARLI was tested for the collection of landslides in Cuenca (Ecuador). From the data taken in the field, it was possible to analyze the performance and suitability of collected data and compare the results with regional inventories in the same area. Additionally, these results can be used for the elaboration and update of large-scale inventories or the training of automatic identification systems of landslides and later evaluation of their precision in a small-medium scale. Likewise, this product constitutes a fundamental input for the formulation of mitigation strategies, to formulate the appropriate response and in time, also the elaboration of reconstruction plans before the increase in the occurrence of such phenomena.

     

Stochastic Local Interaction Model: An Alternative to Kriging for Massive Datasets

Mathematical Geosciences - Classical geostatistical methods face serious computational challenges if they are confronted with large spatial datasets. The stochastic local interaction (SLI) approach...