The World Spider Catalog is the first fully searchable online database covering spider taxonomy, but it has a longer history of predecessors which started with Pierre Bonnet (University of Toulouse, France) and Carl Friedrich Roewer (Bremen, Germany). Bonnet's seven scholarly books of his Bibliographia araneorum, published in three volumes 1945-1961, were fully comprehensive and covered literature on all aspects of spider biology through 1939, on more than 6400 pages. Roewer's Katalog der Araneae von 1758 bis 1940 (three books, published in two volumes, more than 2700 pages) were published 1942-1955 and covered the taxonomically useful literature through 1940 or 1954 (depending on the taxon).

The next important step was performed by Paolo M. Brignoli (University of Aquila, Italy) with his Catalogue of the Araneae described between 1940 and 1981, published 1983. This 750 pages volume filled many of the post-Roewer gaps (through 1980, with scattered coverage of later papers as well). Brignoli intended to issue Catalogue supplements at periodic intervals but this stopped due to his untimely death in 1986. Fortunately, Brignoli’s idea could be continued because Norman I. Platnick (American Museum of Natural History, New York) accepted the challenge to take over the task of preparing supplements to Brignoli's volume. In the next decade, three supplement volumes (1989, 1993, 1997) of Advances in Spider Taxonomy with together 2500 pages were published, covering the literature from 1981 through 1995 and including all synonyms, transfers, and re-descriptions from 1940 to 1980.

By the end of the 20th century it became obvious that the increasing quantity of taxonomic information could no longer be managed in the conventional way. So far more than 10’000 catalog pages and (currently) an annual influx of more than 300 taxonomic publications with descriptions of ca. 900 new species need an internet based solution. Platnick started this task with a first online version of his World Spider Catalog in 2000 and continued through 2014, with two updated versions per year, a total of 30 updates. The catalog was hosted at the American Museum of Natural History and served as HTML files per family. You can find a complete archive.

With the retirement of Platnick in 2014, the Natural History Museum Bern (Switzerland) accepted to continue Platnick’s work and took over the World Spider Catalog. All data provided by the catalog version 14.5 has been processed in order to fit into a relational database. One of the major achievements of a true database is that it is fully searchable over the complete content of spider taxonomy since 1757 when the first now acknowledged 68 spider species were described by Carl Clerck. Another important novelty is the link to the World Spider Catalog Association (WSCA) which intends to provide access to more than 12’000 taxonomic publications which are behind this database information.

The World Spider Catalog considers all taxonomically useful published work. Unpublished statements – even if correct – will not be taken over here. Also contents of websites that are not published elsewhere are not considered. Roewer and Platnick set standards for the Catalog that persist largely until today. Basically, this includes all descriptions of new species, transfers, synonymies and all taxonomically useful (i.e., illustrated) references to previously described taxa. Electronic supplements can be considered in combination with the corresponding main article. Not included are subfamilial or subgeneric divisions and allocations, or mentions of taxa in purely faunistic works (unless accompanied by useful illustrations).

The catalog entries for literature prior to 1940 do not reflect a complete re-check of the classical literature. Roewer's listings based on the classical literature have largely been accepted, and only discrepancies detected between Roewer's and Bonnet's treatments have been re-checked and resolved. These listings are not intended to supplant either Roewer's or Bonnet's volumes, but rather to provide a quick, electronically searchable guide to the most important literature on spider systematics, worldwide. Investigators doing original research should still check the listings in Roewer and Bonnet; we hope that omissions are few, but no project of this magnitude could ever be error-free.

In certain cases, published nomenclatural or taxonomical changes will not be taken over by the catalog. This includes for example cases with violations of the provisions of the International Code of Zoological Nomenclature. In debatable cases (e.g. purely typological genus-splitting without phylogenetic reasons), an expert board will decide the case democratically. However, if some published alterations are not taken over by the catalog, the respective information and reference is given anyway.

The following abbreviations are used: Male or female signs (m or f) alone indicate that palpal or epigynal illustrations are included (hence figure references without such annotations include only somatic characters, generally through scanning electron micrographs; citations are not provided for cases where authors supplied only a general view of the body). The letter D indicates an original description, either of a taxon or of a previously unknown sex. The letter T indicates that one or both sexes have been transferred from a specified genus to the one under consideration; tentative statements indicating that a species "possibly belongs" or "may belong" elsewhere are not included as transfers (or synonymies). The letter S indicates that details of one or more new synonymies can be found immediately under the generic listing; an S followed by a male or female sign indicates that a previously unknown sex has been added through a synonymy. The type species of each genus is marked with an asterisk (*).

The organization of the entries is hierarchically determined; hence synonymies at the generic level are indicated under the family (and cross-referenced under the appropriate generic) listings, but affected species are listed separately only if there are significant references to them in particular. Similarly, synonymies at the species level are listed under generic, rather than familial, headings. The brief descriptions of geographic ranges are provided only as a general guide; no attempt has been made to ensure that they are comprehensive.

Users who detect errors, of any sort, are urged to bring them to our attention (email to wsc(at)nmbe.ch).

A global database on the media representation of human-spider encounters in the global press. The database is fully described in this publication, which should be cited when using it:Mammola, S. et al. 2022. An expert-curated global database of online newspaper articles on spiders and spider bites. Scientific Data, doi: 10.1038/s41597-022-01197-6An Excel file (.xslx) and a tab-delimited (.csv) version of the database is provided. Columns are explained in the metadata file.------ Change-log version 2:We updated the database following the publication of:Nanni V, Moioli I, Scott C, Mammola S (2025). Social media filtering of sensationalistic news on spiders—a global overview. People & Nature, in press.We corrected several typos and added new variables (Deadly, Facebook interactions, Facebook shares). See Meta_Data_V2.pdf for details.

Dataset Card for Spider Schema

  Dataset Summary

Spider is a large-scale complex and cross-domain semantic parsing and text-to-SQL dataset annotated by 11 Yale students The goal of the Spider challenge is to develop natural language interfaces to cross-domain databases. This dataset contains the 166 databases used in the Spider dataset.

  Yale Lily Spider Leaderboards

The leaderboard can be seen at https://yale-lily.github.io/spider

  Languages

The text in… See the full description on the dataset page: https://huggingface.co/datasets/richardr1126/spider-schema.

Datasets from the World Spider Trait database

Dataset Card for Spider

  Dataset Summary

Spider is a large-scale complex and cross-domain semantic parsing and text-to-SQL dataset annotated by 11 Yale students. The goal of the Spider challenge is to develop natural language interfaces to cross-domain databases.

  Supported Tasks and Leaderboards

The leaderboard can be seen at https://yale-lily.github.io/spider

  Languages

The text in the dataset is in English.

  Dataset Structure





  Data… See the full description on the dataset page: https://huggingface.co/datasets/xlangai/spider.

Background:There is an increasing demand for databases including species trait information for biodiversity and community ecology studies. The existence of trait databases is useful for comparative studies within taxa or geographical regions, but there is low availability of databases for certain organisms. Here we present an open access functional trait database for spiders from Macaronesia and the Iberian Peninsula, recording several morphological and ecological traits related to the species life histories, microhabitat and trophic preferences. New information:We present a database that includes 12 biological traits for 506 spider species present in natural forests of the Iberian Peninsula (Spain) and three Macaronesian archipelagoes (Azores, Madeira and Canary Islands). The functional trait database consists of two sections:individual-level data for six morphological traits (total body size, prosoma length, prosoma width, prosoma height, tibia I length and fang length), based on direct measurements of 2844 specimens of all spider species; andspecies-level aggregate data for 12 traits (same 6 morphological traits as in the previous section plus dispersal ability, vertical stratification, circadian activity, foraging strategy, trophic specialization and colonization status), based on either the average of the direct measurements or bibliographic searches.This functional trait database will serve as a data standard for currently ongoing analyses that require trait and functional diversity statistics.

Spider species-level data collected from pan traps across four habitat types in Cambrige Bay Nunavut. Two wet habitat types and two dry habitat types were examined. Samples continuously taken from July 3rd to August 11th 2014, but broken down into sampling periods which are, on average, 6 days long.

This folder contains the Spider-Realistic dataset used for evaluation in the paper "Structure-Grounded Pretraining for Text-to-SQL". The dataset is created based on the dev split of the Spider dataset (2020-06-07 version from https://yale-lily.github.io/spider). We manually modified the original questions to remove the explicit mention of column names while keeping the SQL queries unchanged to better evaluate the model's capability in aligning the NL utterance and the DB schema. For more details, please check our paper at https://arxiv.org/abs/2010.12773.

It contains the following files:

- spider-realistic.json
# The spider-realistic evaluation set
# Examples: 508
# Databases: 19
- dev.json
# The original dev split of Spider
# Examples: 1034
# Databases: 20
- tables.json
# The original DB schemas from Spider
# Databases: 166
- README.txt
- license

The Spider-Realistic dataset is created based on the dev split of the Spider dataset realsed by Yu, Tao, et al. "Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-sql task." It is a subset of the original dataset with explicit mention of the column names removed. The sql queries and databases are kept unchanged.
For the format of each json file, please refer to the github page of Spider https://github.com/taoyds/spider.
For the database files please refer to the official Spider release https://yale-lily.github.io/spider.

This dataset is distributed under the CC BY-SA 4.0 license.

If you use the dataset, please cite the following papers including the original Spider datasets, Finegan-Dollak et al., 2018 and the original datasets for Restaurants, GeoQuery, Scholar, Academic, IMDB, and Yelp.

@article{deng2020structure,
title={Structure-Grounded Pretraining for Text-to-SQL},
author={Deng, Xiang and Awadallah, Ahmed Hassan and Meek, Christopher and Polozov, Oleksandr and Sun, Huan and Richardson, Matthew},
journal={arXiv preprint arXiv:2010.12773},
year={2020}
}

@inproceedings{Yu&al.18c,
year = 2018,
title = {Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task},
booktitle = {EMNLP},
author = {Tao Yu and Rui Zhang and Kai Yang and Michihiro Yasunaga and Dongxu Wang and Zifan Li and James Ma and Irene Li and Qingning Yao and Shanelle Roman and Zilin Zhang and Dragomir Radev }
}

@InProceedings{P18-1033,
author = "Finegan-Dollak, Catherine
and Kummerfeld, Jonathan K.
and Zhang, Li
and Ramanathan, Karthik
and Sadasivam, Sesh
and Zhang, Rui
and Radev, Dragomir",
title = "Improving Text-to-SQL Evaluation Methodology",
booktitle = "Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
year = "2018",
publisher = "Association for Computational Linguistics",
pages = "351--360",
location = "Melbourne, Australia",
url = "http://aclweb.org/anthology/P18-1033"
}

@InProceedings{data-sql-imdb-yelp,
dataset = {IMDB and Yelp},
author = {Navid Yaghmazadeh, Yuepeng Wang, Isil Dillig, and Thomas Dillig},
title = {SQLizer: Query Synthesis from Natural Language},
booktitle = {International Conference on Object-Oriented Programming, Systems, Languages, and Applications, ACM},
month = {October},
year = {2017},
pages = {63:1--63:26},
url = {http://doi.org/10.1145/3133887},
}

@article{data-academic,
dataset = {Academic},
author = {Fei Li and H. V. Jagadish},
title = {Constructing an Interactive Natural Language Interface for Relational Databases},
journal = {Proceedings of the VLDB Endowment},
volume = {8},
number = {1},
month = {September},
year = {2014},
pages = {73--84},
url = {http://dx.doi.org/10.14778/2735461.2735468},
}

@InProceedings{data-atis-geography-scholar,
dataset = {Scholar, and Updated ATIS and Geography},
author = {Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Jayant Krishnamurthy, and Luke Zettlemoyer},
title = {Learning a Neural Semantic Parser from User Feedback},
booktitle = {Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)},
year = {2017},
pages = {963--973},
location = {Vancouver, Canada},
url = {http://www.aclweb.org/anthology/P17-1089},
}

@inproceedings{data-geography-original
dataset = {Geography, original},
author = {John M. Zelle and Raymond J. Mooney},
title = {Learning to Parse Database Queries Using Inductive Logic Programming},
booktitle = {Proceedings of the Thirteenth National Conference on Artificial Intelligence - Volume 2},
year = {1996},
pages = {1050--1055},
location = {Portland, Oregon},
url = {http://dl.acm.org/citation.cfm?id=1864519.1864543},
}

@inproceedings{data-restaurants-logic,
author = {Lappoon R. Tang and Raymond J. Mooney},
title = {Automated Construction of Database Interfaces: Intergrating Statistical and Relational Learning for Semantic Parsing},
booktitle = {2000 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora},
year = {2000},
pages = {133--141},
location = {Hong Kong, China},
url = {http://www.aclweb.org/anthology/W00-1317},
}

@inproceedings{data-restaurants-original,
author = {Ana-Maria Popescu, Oren Etzioni, and Henry Kautz},
title = {Towards a Theory of Natural Language Interfaces to Databases},
booktitle = {Proceedings of the 8th International Conference on Intelligent User Interfaces},
year = {2003},
location = {Miami, Florida, USA},
pages = {149--157},
url = {http://doi.acm.org/10.1145/604045.604070},
}

@inproceedings{data-restaurants,
author = {Alessandra Giordani and Alessandro Moschitti},
title = {Automatic Generation and Reranking of SQL-derived Answers to NL Questions},
booktitle = {Proceedings of the Second International Conference on Trustworthy Eternal Systems via Evolving Software, Data and Knowledge},
year = {2012},
location = {Montpellier, France},
pages = {59--76},
url = {https://doi.org/10.1007/978-3-642-45260-4_5},
}

This dataset consists of count data (by gender) for all species of spider collected from three habitats (mire, dwarf-shrub heath, pine woodland) at the Cairngorms Environmental Change Network (ECN) site between 2004 and 2019. Spiders were collected in pitfall traps on a two-weekly basis between March and early November. Each habitat contained 10 pitfall traps, spaced 10 m apart. Samples were aggregated by habitat and collection date prior to analysis. The number of male and females of each species was recorded by the same expert araneologist for the duration (2004-2019). Data was collected to look at long-term trends in invertebrate ground predators. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.

Spider diagram with Journey to Work Origin / Destination data from CTPP/ACS 2006-2010. Each vector indicates the number of work commuters traveling from Origin (Residence) to Destination (Workplace).

Historical data of spiders caught in Poland. Specimens of spiders identified to species can be found in Professor Andrzej Myrcha University Center of Nature, University of Białystok.

No missing values

Dataset Card for Spider Context Validation

  Dataset Summary

Spider is a large-scale complex and cross-domain semantic parsing and text-to-SQL dataset annotated by 11 Yale students The goal of the Spider challenge is to develop natural language interfaces to cross-domain databases. This dataset was created to validate spider-fine-tuned LLMs with database context.

  Yale Lily Spider Leaderboards

The leaderboard can be seen at https://yale-lily.github.io/spider… See the full description on the dataset page: https://huggingface.co/datasets/richardr1126/spider-context-validation.

AbstractIneffective hunters in cooperative foraging groups may be shielded from natural selection by their more effective group mates, whereas those living solitarily would starve and thus be removed from the population. The problem may be exacerbated in large groups where it may be easier for individuals to withhold participation. Group foragers may thus be ineffective individual hunters or exhibit greater inter-individual variation in hunting abilities, in particular when living in large groups. We test these hypotheses in spider species of the genus Anelosimus that differ in their level of sociality and, among social species, in colonies of different sizes. We found that individuals from the more social species, and those from larger groups, reacted more slowly to prey than those from solitary species or small groups. Individuals from these categories also had greater inter-individual variation in reaction times. Individuals from large social groups also had lower prey capture success than those from small ones. These differences may have been driven by the size of the group from which the social individuals were taken, as those from small colonies behaved similarly to individuals of the two less social species. This finding suggests that hunting ability may develop as a phenotypically plastic trait. Usage notesIndividual hunt data - summarizedDemographic and prey capture data on each spider tested. Data include female size, colony size and population, average web volume and average capture rate over three feeding trials.Individual hunt data - trial dataTrial data for each of the 3 trials that each spider was subjected to. Data include reaction times, outcomes, and size of webbing.

Geographic Coverage: The island of Ireland Temporal Coverage: 2011 to 2020 Species Groups recorded: spider (Araneae) Dataset Status: Complete up to January 2021

This dataset contains the digitized treatments in Plazi based on the original journal article Dankittipakul, Deeleman-Reinhold (2012): A new spider species of the genus Sudharmia from Sumatra, Indonesia (Araneae, Liocranidae). Zoological Research 33 (2): 187-190, DOI: 10.3724/Sp.J.1141.2012.02187, URL: https://www.researchgate.net/publication/223980105_A_new_spider_species_of_the_genus_Sudharmia_from_Sumatra_Indonesia_Araneae_Liocranidae

Wolf spiders are typically the most common group of arthropod predators on both lake and marine shorelines, because of the high prey availability in these habitats. However, shores are also harsh environments due to flooding and, in proximity to marine waters, to toxic salinity levels. Here, we describe the spider community, prey availabilities, and spider diets between shoreline sites with different salinities, albeit with comparatively small differences (5 vs. 7‰). Despite the small environmental differences, spider communities between low and higher-saline sites showed an almost complete species turnover. At the same time, differences in prey availability or spider gut contents did not match changes in spider species composition but rather changed with habitat characteristics within the region, where spiders collected at sites with thick wrack beds had a different diet than sites with little wrack. These data suggest that shifts in spider communities are due to habitat characteristics rather than prey availabilities, and the most likely candidate restricting species in high salinity would be saline sensitivity. At the same time, species' absences from low-saline habitats remain unresolved.

Spiders are an important animal group, with a long history. Details of their origins remain limited, with little knowledge of their stem group, and no insights into the sequence of character acquisition during spider evolution. We describe a new fossil arachnid, Idmonarachne brasieri gen. et sp. nov. from the late Carboniferous (Stephanian, ca. 305–299 Ma) of Montceau-les-Mines, France. It is three-dimensionally preserved within a siderite concretion, allowing both laboratory- and synchrotron-based phase-contrast computed tomography (CT) reconstruction. The latter is a first for siderite-hosted fossils, and has allowed us to investigate fine anatomical details. Although distinctly spider-like in habitus, this remarkable fossil lacks a key diagnostic character of Araneae: spinnerets on the underside of the opisthosoma. It also lacks a flagelliform telson found in the recently recognised, spider-related, Devonian–Permian Uraraneida. Cladistic analysis resolves our new fossil as sister gro...

Database of traits for European cave spiders, available as an Excel file (.xlsx) or a tab-delimited file (.csv). See Metadata file for an explanation of the columns.

The database is described in detail in the following publication:

Mammola S, Pavlek P, Huber BA, Isaia M, Ballarin F, Tolve M, Čupić I, Hesselberg T, Lunghi E, Mouron S, Graco Roza C, & Cardoso P. 2022. A trait database and updated checklist for European subterranean spiders. Scientific Data, doi: 10.1038/s41597-022-01316-3

Updated database to Version 2 on 27 Jan 2023.

Changelog:

1) Corrected a few typos in formatting 2) Measured some missing traits in Eidmannella pallida, Heteropoda variegata, Loxosceles rufescens, and Tegenaria pagana 3) Added missing species Phyxelida anatolica

Intraguild predation (IGP) – predation between generalist predators (IGPredator and IGPrey) that potentially compete for a shared prey resource – is a common interaction module in terrestrial food webs. Understanding temporal variation in webs with widespread IGP is relevant to testing food web theory. We investigated temporal constancy in the structure of such a system: the spider-focused food web of the forest floor. Multiplex PCR was used to detect prey DNA in 3,300 adult spiders collected from the floor of a deciduous forest during spring, summer, and fall over four years. Because only spiders were defined as consumers, the web was tripartite, with 11 consumer nodes (spider families) and 22 resource nodes: 11 non-spider arthropod taxa (order- or family-level) and the 11 spider families. Most (99%) spider-spider predation was on spider IGPrey, and ~90% of these interactions were restricted to spider families within the same broadly defined foraging mode (cursorial or web-spinning spiders). Bootstrapped-derived confidence intervals (BCI’s) for two indices of web structure, restricted connectance and interaction evenness, overlapped broadly across years and seasons. A third index, % IGPrey (% IGPrey among all prey of spiders), was similar across years (~50%) but varied seasonally, with a summer rate (65%) ~1.8x higher than spring and fall. This seasonal pattern was consistent across years. Our results suggest that extensive spider predation on spider IGPrey that exhibits consistent seasonal variation in frequency, and that occurs primarily within two broadly defined spider-spider interaction pathways, must be incorporated into models of the dynamics of forest-floor food webs. Methods Study system We collected spiders and potential non-spider prey from the oak-dominated (Quercus alba and Q. rubra) Swallow Cliff Woods (41° 40.519’ N, 87° 51.437’ W) within the 320-ha Swallow Cliff nature preserve in Palos Township, Illinois (USA). The preserve, which is within the Chicago metropolitan region, is managed by the Cook County Forest Preserve District. Forests in this region are actively managed for several invasive plants (23), and the forest floor at Swallow Cliffs contains a thick leaf-litter layer with an abundant and diverse arthropod community. Collecting spiders and non-spider prey Our goal was to search the ground layer and low understory as thoroughly as possible, so that we would collect enough spiders from less-abundant families to yield the same number of spiders per family analyzed for prey DNA. We did not estimate spider densities. All collections were made between 1000 and 1600 hours. We collected from a different location each day. The size of the area searched each day was not measured and varied with the number of searchers. Collecting areas were widely distributed throughout Swallow Cliff Woods, but we did not subdivide the Woods into sampling regions. Most terrain was upland forest, but some collections were taken from a few scattered wet/marshy areas. The number of collecting days in each season was spring (31), summer (33), and fall (29) over the years 2009, 2010, 2011 and 2012; the number of days per year was 33, 12, 34 and 14, respectively. On each collecting day, we used both litter sifting and simple searching to capture spiders from several microhabitats. For litter sifting, we placed litter collected by hand into a flat tray (58 cm x 17 cm x 15 cm) with a screen bottom. This tray was shaken over a second tray of the same size with a solid bottom, allowing arthropods to fall through the screen to be collected by hand or aspirator. Sifted litter was returned to its original location. Spiders were also collected by hand from the litter surface, open areas in the litter, logs, low vegetation up to ~1m, and tree trunks up to ~2m. Individual spiders were placed in separate labelled vials. Of the spiders that were eventually analyzed for prey DNA (see below), 81% were captured from either leaf litter (70%) or adjacent bare ground/logs (11%). Thus, most spiders were collected from the litter layer broadly defined. The litter layer is a fairly distinct subsystem with respect to rates of migration of arthropod predators and prey (24). Nevertheless, we did not limit our definition of the “forest floor” to the litter layer because many spiders spin webs in vegetation close to the ground. Also, some cursorial species move back and forth between the ground and lower understory vegetation and tree trunks (for example, 84% of the Corinnidae, a guild of “foliage runners” (25), were collected from leaf litter). Therefore, we also analyzed spiders that had been collected from low vegetation (10%) and tree trunks (9%). All specimens were placed on ice within one hour of capture. On the same day, spiders collected for detection of consumed prey using PCR were taken to the laboratory where they were weighed and stored at -20◦C in a 1.5-mL microcentrifuge tube containing 95% ethanol (EtOH). Spiders and non-spider prey (see below) intended for primer development or assay optimization (see below for details) were kept alive, weighed, placed individually into 60-mL glass vials, and provided with water ad libitum at room temperature. Spiders were identified to family and genus using identification guides (26-29). Voucher specimens (one adult male and female) for each genus (when available) were archived at The Field Museum (Chicago, Illinois). Over the four years, ~14,000 spiders (juveniles and adults) from 20 families were collected. Presence of prey DNA was tested for adult spiders from 11 abundant families (those with at least 300 adults) that live primarily on the forest floor. Spiders from six of these families (Corinnidae, Gnaphosidae, Lycosidae, Pisauridae, Salticidae, and Thomisidae) do not spin webs to capture prey (“cursorial” spiders). The other five families (Agelenidae, Dictynidae, Hahniidae, Linyphiidae, and Theridiidae) are “web spinners.” This dichotomy reflects basic differences in foraging behavior (16, 17), but the distinction is not absolute. The web spinners in our food web include genera of spiders that also forage for prey off their web (18). Non-spider arthropod prey were also collected for primer development. They were not sampled quantitatively, but were simply selected due to their apparent abundance in leaf litter and/or activity just above the litter layer, and their likely occurrence in the diets of at least one spider family (15-17, 30). Non-spider nodes of the food web were broadly defined taxonomically (at the Order level except for Gryllidae): flies (Diptera), moths/butterflies (Lepidoptera), springtails (Collembola), ants/bees/wasps (Hymenoptera), jumping bristletails (Archaeognatha), crickets (Gryllidae), pseudoscorpions (Pseudoscorpiones), harvestmen (Opiliones), beetles (Coleoptera), earwigs (Dermaptera), and pillbugs (Isopoda). Molecular techniques Primer development and optimization We utilized multiplex PCR to sequence DNA from at least ten spiders from each family and at least ten specimens from each non-spider prey taxon. Each spider was first starved for at least ten days to eliminate any gut-content DNA that may have been present. Specimens were then homogenized in 180 μL of phosphate-buffered saline (PBS) (Hoefer, San Francisco, CA). DNA was then extracted with a Qiagen DNEasy Tissue Kit (Valencia, CA) using the manufacturer’s protocol. Upon completion of DNA extraction, the 200μL of eluate was well-mixed, separated into 20μL aliquots, and stored at -20°C until analysis. The general arthropod primers LCO-1490 and HCO-2198 (31) were used to amplify DNA from the mitochondrial genome’s cytochrome oxidase I (COI) region. Eluate from DNA extractions was amplified and sequenced by The Field Museum (Chicago, IL) or Research Resources Center (RRC) at the University of Illinois, Chicago. Sequences were used to conduct BLASTN searches following the protocol developed by (32) using the databases GenBank and BOLD (the Barcode of Life Database). Following (33), database sequences were used only if they showed ≥97% match to submitted sequences. Sequences were aligned using the CLUSTALW or AMPLICON programs. Primers were designed with the assistance of the IDT (Integrated DNA Technologies, Coralville, IA) program PrimerQuest and tested for melting temperature and CG content using Sci-Tools OligoAnalyzer (IDT). Spider gut-content testing After a PCR assay was developed and optimized for a particular prey taxon (spider family or non-spider arthropod), frozen field-caught adult spiders were tested for the presence of the target-prey DNA. Spiders were thawed to room temperature and underwent DNA extraction and PCR amplification as described above. The entire spider was homogenized, except for the largest individuals, for which legs were removed to increase the prey/predator DNA ratio; coxae were left attached to the body when possible because spider guts often extend into the coxae (17). The homogenate was then mixed and 4uL were added to a well (on a 96-well plate) that contained 21 uL of Master Mix. Every run also included positive, negative, and blank controls to ensure that target DNA was amplified and that no contamination existed on the run. Positive controls consisted of DNA specific to the target taxon in question, negative controls contained the PCR Master Mix without DNA template, and blank controls were created from MBG water. A sample was considered positive for target-prey DNA within the spider’s gut if the Ct value of the amplification curve was above the background threshold, if the shape of the curve was sigmoidal, and if the positive and negative controls were acceptable. Samples that did not show amplification were re-analyzed using arthropod-general primers (31) before identifying them as negative results; questionable samples (low amplification or a non-sigmoidal shape) were re-tested. For constructing the food web, adult