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Marine bivalves are important components of ecosystems and exploited by humans for food across the world, but the intrinsic vulnerability of exploited bivalve species to global changes is poorly known. Here, we expand the list of shallow-marine bivalves known to be exploited worldwide, with 720 exploited bivalve species added beyond the 81 in the United Nations FAO Production Database, and investigate their diversity, distribution and extinction vulnerability using a metric based on ecological traits and evolutionary history. The added species shift the richness hotspot of exploited species from the northeast Atlantic to the west Pacific, with 55% of bivalve families being exploited, concentrated mostly in two major clades but all major body plans. We find that exploited species tend to be larger in size, occur in shallower waters, and have larger geographic and thermal ranges—the last two traits are known to confer extinction-resistance in marine bivalves. However, exploited bivalve species in certain regions such as the tropical east Atlantic and the temperate northeast and southeast Pacific, are among those with high intrinsic vulnerability and are a large fraction of regional faunal diversity. Our results pinpoint regional faunas and specific taxa of likely concern for management and conservation.

 

We present a psychometric evaluation of the Cybersecurity Curriculum Assessment (CCA), completed by 193 students from seven colleges and universities. The CCA builds on our prior work developing and validating a Cybersecurity Concept Inventory (CCI), which measures students' conceptual understanding of cybersecurity after a first course in the area. The CCA deepens the conceptual complexity and technical depth expectations, assessing conceptual knowledge of students who had completed multiple courses in cybersecurity. We review our development of the CCA and present our evaluation of the instrument using Classical Test Theory and Item-Response Theory. The CCA is a difficult assessment, providing reliable measurements of student knowledge and deeper information about high-performing students. 

To quantify the volatility of organic aerosols (OA), a comprehensive campaign was conducted in the Chinese megacity. Volatility distributions of OA and particle‐phase organic nitrate (pON) were estimated based on five methods: (a) empirical method and (b) kinetic model based on the measurement of a thermodenuder (TD) coupled with an aerosol mass spectrometer; (c) Formula‐based SIMPOL model‐driven method; (d) Element‐based estimations using molecular formula measurements of OA; and (e) gas/particle partitioning. Our results demonstrate that the ambient OA volatility distribution shows good agreement between the two heating methods and the formula‐based method when assuming ambient OA was mainly composed of organic nitrate (pON), organic sulfate and acid groups using the SIMPOL model. However, the element‐based method tends to overestimate the volatility of OA compared to the above three methods, suggesting large uncertainties in the parameterizations or in the representativeness of the molecular measurements that need further refinement. The volatility of ambient OA is generally lower than that of the laboratory‐derived secondary OA, emphasizing the impact of aging. A large fraction at the higher and lower volatility ranges (approximately logC* ≤ −9 and ≥2 μg m⁻³) was found for pON, implying the importance of both extremely low volatile and semi‐volatile species. Overall, this study evaluates different methods for volatility estimation and gives new insight into the volatility of OA and pON in urban areas.

 

Parasites are a major component of global ecosystems, yet spatial variation in parasite diversity is poorly known, largely because their occurrence data are limited and thus difficult to interpret. Using a recently compiled database of parasite occurrences, we compare different models which we use to infer parasite geographic ranges and parasite species richness across the globe.

To date, most studies exploring spatial patterns of parasite diversity assumed, with little validation, that the geographic range of a parasite species can be represented by the collective geographic range of its host species. Our study compares this assumption with a suite of other methods to infer parasite distribution from parasite occurrence data (e.g., based on data density, ecoregions and climatic conditions). We highlight diversity hotspots identified by the various methods and compare the effects of sampling intensities in different regions, a crucial factor determining observed parasite diversity.

The type of model used to infer parasite distributions affects estimates of both total species richness and spatial patterns of hotspots of parasite richness. Overall, the models based on reported occurrences share similar areas of high parasite richness that tend to be biased towards areas of high sampling effort. In contrast, the model based on host distributions showed hotspots of parasite diversity that are biased towards areas of high host species richness. Accounting for sampling effort could only help to reconcile the outcome from the different models in some regions. Further, the non‐saturated species accumulation curves even for the best studied regions of the world such as Europe and North America serve as a call for further sampling effort and development of effective analytic tools that can provide robust accounts of global parasite diversity.