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Understanding spatial distributions of invasive plant species at early infestation stages is critical for assessing the dynamics and underlying factors of invasions. Recent progress in very high resolution remote sensing is facilitating this task by providing high spatial detail over whole-site extents that are prohibitive to comprehensive ground surveys. This study assessed the opportunities and constraints to characterize landscape distribution of the invasive grass medusahead (Elymus caput-medusae) in a ∼36.8 ha grassland in California, United States from 0.15m-resolution visible/near-infrared aerial imagery at the stage of late spring phenological contrast with dominant grasses. We compared several object-based unsupervised, single-run supervised and hierarchical approaches to classify medusahead using spectral, textural, and contextual variables. Fuzzy accuracy assessment indicated that 44–100% of test medusahead samples were matched by its classified extents from different methods, while 63–83% of test samples classified as medusahead had this class as an acceptable candidate. Main sources of error included spectral similarity between medusahead and other green species and mixing of medusahead with other vegetation at variable densities. Adding texture attributes to spectral variables increased the accuracy of most classification methods, corroborating the informative value of local patterns under limited spectral data. The highest accuracy across different metrics was shown by the supervised single-run support vector machine with seven vegetation classes and Bayesian algorithms with three vegetation classes; however, their medusahead allocations showed some “spillover” effects due to misclassifications with other green vegetation. This issue was addressed by more complex hierarchical approaches, though their final accuracy did not exceed the best single-run methods. However, the comparison of classified medusahead extents with field segments of its patches overlapping with survey transects indicated that most methods tended to miss and/or over-estimate the length of the smallest patches and under-estimate the largest ones due to classification errors. Overall, the study outcomes support the potential of cost-effective, very high-resolution sensing for the site-scale detection of infestation hotspots that can be customized to plant phenological schedules. However, more accurate medusahead patch delineation in mixed-cover grasslands would benefit from testing hyperspectral data and using our study’s framework to inform and constrain the candidate vegetation classes in heterogeneous locations.

A number of spider species within the family Theridiidae exhibit a dramatic abdominal (opisthosomal) color polymorphism. The polymorphism is inherited in a broadly Mendelian fashion and in some species consists of dozens of discrete morphs that are convergent across taxa and populations. Few genomic resources exist for spiders. Here, as a first necessary step towards identifying the genetic basis for this trait we present the near complete transcriptomes of two species: the Hawaiian happy-face spider Theridion grallator and Theridion californicum. We mined the gene complement for pigment-pathway genes and examined differential expression (DE) between morphs that are unpatterned (plain yellow) and patterned (yellow with superimposed patches of red, white or very dark brown).

Results:

By deep sequencing both RNA-seq and normalized cDNA libraries from pooled specimens of each species we were able to assemble a comprehensive gene set for both species that we estimate to be 98-99% complete. It is likely that these species express more than 20,000 protein-coding genes, perhaps 4.5% (ca. 870) of which might be unique to spiders. Mining for pigment-associated Drosophila melanogaster genes indicated the presence of all ommochrome pathway genes and most pteridine pathway genes and DE analyses further indicate a possible role for the pteridine pathway in theridiid color patterning.

Conclusions:

Based upon our estimates, T. grallator and T. californicum express a large inventory of protein-coding genes. Our comprehensive assembly illustrates the continuing value of sequencing normalized cDNA libraries in addition to RNA-seq in order to generate a reference transcriptome for non-model species. The identification of pteridine-related genes and their possible involvement in color patterning is a novel finding in spiders and one that suggests a biochemical link between guanine deposits and the pigments exhibited by these species.

Conflict between livestock producers and wild predators is a central driver of large predator declines and simultaneously may imperil the lives and livelihoods of livestock producers. There is a growing recognition that livestock–predator conflict is a socio‐ecological problem, but few case studies exist to guide conflict research and management from this point of view. Here we present a case study of coyote‐sheep predation on a California ranch in which we combine methods from the rapidly growing field of predation risk modeling with participatory mapping of perceptions of predation risk. Our findings reveal an important selection bias that may occur when producer perceptions and decisions are excluded from ecological methods of studying conflict. We further demonstrate how producer inputs, participatory mapping, and ecological modeling of conflict can inform one another in understanding patterns, drivers, and management opportunities for livestock–predator conflict. Finally, we make recommendations for improving the interoperability of ecological and social data about predation risk. Collectively our methods offer a socio‐ecological approach that fills important research gaps and offers guidance to future research.

Academic libraries want to collect the materials most useful to researchers, yet how can libraries know how successful they are? While Berkeley’s George and Mary Foster Anthropology Library collects data on which books circulate, it is difficult to evaluate how materials are actually being used to further the discipline of anthropology. In this article, we examine sources cited by our a) faculty members, b) dissertation writers, and c) honors thesis students to better understand how anthropologists read when conducting research. This paper compares materials used across subfields and research levels to highlight patterns in citations within this discipline, leading to new insights that will improve collection development among anthropology librarians.

This case study recounts a process of course design, conduct, and evaluation for a single-session chemical information literacy class using guided and team-based learning. This approach incorporates active learning, worked examples, process worksheets, and POGIL elements. The instruction followed an iterative cycle of learning exercises whereby (1) the instructor introduces an information problem or task through a short presentation, (2) student teams collaboratively work through process worksheets that guide them through the technical and analytical tasks of resolving the information problem or task, (3) the instructor serves as a facilitator to address learning needs that arise during the exercise, while student teams analyze and reflect upon the learning activity and concepts, and afterwards, (4) the class engages in a discussion as an opportunity for evaluation, further exploration, and peer instruction. Overall, the guided and team-based learning approach offers opportunities to observe student progress closely and forges a collaborative spirit between students and the instructor for an engaging and rewarding experience.

Even the largest research library can no longer build comprehensive collections from all countries and in all languages. The pressure to justify acquisitions can be great on non-English language materials, which are often low-use in North American universities. Determining the research need for these materials, and assessing how well it is being met, is challenging. This paper analyzes impact by examining the language of cited references in doctoral dissertations at Berkeley, 2008-2015.

The Copyright Alternative in Small-Claims Enforcement Act of 2020 (CASE Act) was swept into law during the final days of 2020 as a part of the 5,500 page federal spending bill. In theory, the CASE Act aims to provide a venue for individual creators (such as photographers, graphic artists, musicians) to address smaller copyright infringement claims without spending the time and money required to pursue a copyright infringement lawsuit in Federal court. In reality, however, this additional bureaucratic structure created outside of the traditional court system is fraught with problems that will mostly incentivize large, well-resourced rightsholders or overly litigious copyright owners to take advantage of the system. At the same time, it will confuse and harm innocuous users of content, who may not understand the complexities of copyright law, and who do not know whether or how to respond to a notice of infringement via this small claims process. From our perspective, it will chill users who rely on crucial statutory exceptions to copyright, such as fair use, in their research and teaching activities.

UC Berkeley Library secured a grant from the National Endowment for the Humanities to support an Institute for Advanced Topics in the Digital Humanities to help key stakeholders to learn to better navigate legal issues in text data mining. UC Berkeley Library’s Office of Scholarly Communication Services led a national team from more than a dozen institutions and organizations to teach humanities researchers, librarians, and research staff how to confidently navigate the major legal issues that arise in text data mining research. 

Our institute was called Building Legal Literacies for Text Data Mining (Building LLTDM), and ran from June 23-26, 2020.

This white paper describes the institute’s origins and goals, project overview and activities, and reflections and possible follow-on actions.

Legal Literacies for Text Data Mining - Cross-Border (“LLTDM-X”) is a National Endowment for the Humanities Level 1 Advancement Grant project addressing legal and ethical issues faced by U.S. digital humanities (DH) practitioners whose text data mining (TDM) research and practice intersects with foreign-held or - licensed content, or involves international cooperations.

LLTDM-X is a collaboration between the University of California Berkeley Library and Internet Archive, and builds upon the previous NEH-sponsored institute, Building Legal Literacies for Text Data Mining (Building LLTDM). That institute provided guidance and strategies to DH TDM researchers on navigating legal literacies for text data mining (including copyright, contracts, privacy, and ethics) within a U.S. context.

A common challenge highlighted during Building LLTDM was the fact that TDM practitioners encounter numerous and complex legal problems in cross-border TDM research. These occur when: (i) the materials practitioners want to mine are housed in a foreign jurisdiction, or are otherwise subject to foreign database licensing or laws; (ii) the human subjects they are studying or who created the underlying content reside in another country; or, (iii) the colleagues with whom they are collaborating reside abroad, yielding uncertainty about which country’s laws, agreements, and policies apply.

We designed LLTDM-X to identify and better understand the cross-border issues that DH TDM practitioners face, with the aim of using these issues to inform prospective research and education. We also hoped that LLTDM-X would yield preliminary guidance to benefit researchers in the meantime, as instructional materials are being developed. In early 2023, we hosted a series of three online round tables with U.S.-based cross-border TDM practitioners (“Practitioners”), and law and ethics experts (“Experts”) practicing in six countries. The round table conversations were structured to illustrate the empirical issues that researchers face, and also for the Practitioners to benefit from guidance on legal and ethical challenges. Upon the completion of the round tables, the LLTDM-X project team created a robust and hypothetical case study that (i) reflects the observed cross-border LLTDM issues and (ii) contains analysis to facilitate the development of future instructional materials.