Global threats to ocean biodiversity have generated a worldwide movement to take actions to improve conservation and management. Several international initiatives have recommended the adoption of marine protected areas (MPAs) in national and international waters. National governments and the Commission for the Conservation of Antarctic Marine Living Resources have successfully adopted multiple MPAs in the Southern Ocean despite the challenging nature of establishing MPAs in international waters. But are these MPAs representative of Southern Ocean biodiversity? Here we answer this question for both existing and proposed Antarctic MPAs, using benthic and pelagic regionalizations as a proxy for biodiversity. Currently about 11.98% of the Southern Ocean is protected in MPAs, with 4.61% being encompassed by no-take areas. While this is a relatively large proportion of protection when compared to other international waters, current Antarctic MPAs are not representative of the full range of benthic and pelagic ecoregions. Implementing additional protected areas, including those currently under negotiation, would encompass almost 22% of the Southern Ocean. It would also substantially improve representation with 17 benthic and pelagic ecoregions (out of 23 and 19, respectively) achieving at least 10% representation.

1. Large-scale, long-term biodiversity monitoring is essential to conservation, land management and identifying threats to biodiversity. However, multispecies surveys are prone to various types of observation error, including false-positive/ false-negative detection and misclassification, where a species is thought to have been encountered but not correctly identified. Previous methods assume an imperfect classifier produces species-level classifications, but in practice, particularly with human observers, we may end up with extraspecific classifications including 'unknown', morphospecies designations and taxonomic identifications coarser than species. Disregarding these types of species misclassification in biodiversity monitoring datasets can bias estimates of ecologically important quantities such as demographic rates, occurrence and species richness. 2. Here we present a joint classification-occupancy model that accounts for species non-detection and misclassification. Our framework accommodates extinction and colonization dynamics, allows for additional uncertain 'morphospecies' designations and makes use of individual specimens with known species identities in a semi-supervised setting. We compare the performance of our model to a classification-only model that discards information about occupancy and encounter rate. We illustrate our model with an empirical case study of the carabid beetle (Carabidae) community at the National Ecological Observatory Network Niwot Ridge Mountain Research Station, near Boulder, CO, USA. We also use simulations to evaluate model performance through validation metrics where varying fractions of the data are confirmed. 3. The model supported imperfect classifier accuracy and favoured certain true species classifications strongly for some morphospecies. The model outperformed (e.g. precision) the reduced model that discarded occupancy information, and these differences were most pronounced for abundant species. 4. Spatial and temporal dynamics from modelled occupancy and encounter rates may inform species misclassification probability, but this idea has not yet been | 1529 Methods in Ecology and Evoluঞon SPIERS et al.

The opportunity to participate in and contribute to emerging fields is increasingly prevalent in science. However, simply thinking about stepping outside of your academic silo can leave many students reeling from the uncertainty. Here, we describe 10 simple rules to successfully train yourself in an emerging field, based on our experience as students in the emerging field of ecological forecasting. Our advice begins with setting and revisiting specific goals to achieve your academic and career objectives and includes several useful rules for engaging with and contributing to an emerging field.

Concentration‐discharge (C‐Q) relationships are often used to quantify source water contributions and biogeochemical processes occurring within catchments, especially during discrete hydrological events. Yet, the interpretation of C‐Q hysteresis is often confounded by complexity of the critical zone, such as numerous source waters and hydrochemical nonstationarity. Consequently, researchers must often ignore important runoff pathways and geochemical sources/sinks, especially the hyporheic zone because it lacks a distinct hydrochemical signature. Such simplifications limit efforts to identify processes responsible for the transience of C‐Q hysteresis over time. To address these limitations, we leverage the hydrologic simplicity and long‐term, high‐frequency Q and electrical conductivity (EC) data from streams in the McMurdo Dry Valleys, Antarctica. In this two end‐member system, EC can serve as a proxy for the concentration of solutes derived from the hyporheic zone. We utilize a novel approach to decompose loops into subhysteretic EC‐Q dynamics to identify individual mechanisms governing hysteresis across a wide range of timescales. We find that hydrologic and hydraulic processes govern EC response to diel and seasonal Q variability and that the effects of hyporheic mixing processes on C‐Q transience differ in short and long streams. We also observe that variable hyporheic turnover rates govern EC‐Q patterns at daily to interannual timescales. Last, subhysteretic analysis reveals a period of interannual freshening of glacial meltwater streams related to the effects of unsteady flow on hyporheic exchange. The subhysteretic analysis framework we introduce may be applied more broadly to constrain the processes controlling C‐Q transience and advance understanding of catchment evolution.