Species conservation profiles of a random sample of world spiders I: Agelenidae to Filistatidae.

BACKGROUND: The IUCN Red List of Threatened Species is the most widely used information source on the extinction risk of species. One of the uses of the Red List is to evaluate and monitor the state of biodiversity and a possible approach for this purpose is the Red List Index (RLI). For many taxa, mainly hyperdiverse groups, it is not possible within available resources to assess all known species. In such cases, a random sample of species might be selected for assessment and the results derived from it extrapolated for the entire group - the Sampled Red List Index (SRLI). With the current contribution and the three following papers, we intend to create the first point in time of a future spider SRLI encompassing 200 species distributed across the world. NEW INFORMATION: A sample of 200 species of spiders were randomly selected from the World Spider Catalogue, an updated global database containing all recognised species names for the group. The 200 selected species where divided taxonomically at the family level and the familes were ordered alphabetically. In this publication, we present the conservation profiles of 46 species belonging to the famillies alphabetically arranged between Agelenidae and Filistatidae, which encompassed Agelenidae, Amaurobiidae, Anyphaenidae, Araneidae, Archaeidae, Barychelidae, Clubionidae, Corinnidae, Ctenidae, Ctenizidae, Cyatholipidae, Dictynidae, Dysderidae, Eresidae and Filistatidae.

Introduction

The IUCN Red List of Threatened Species is the most widely used information source on the extinction risk of species (Lamoreux et al. 2003, Rodrigues et al. 2006, Mace et al. 2008 but see Cardoso et al. 2011, Cardoso et al. 2012). It is based on a number of objective criteria, which are relatively easy to apply when adequate information is available (IUCN 2001). The Red List has been used to raise awareness about threatened species, guide conservation efforts and funding, set priorities for protection, measure site irreplaceability and vulnerability and influence environmental policies and legislation (Gardenfors et al. 2001, Rodrigues et al. 2006, Mace et al. 2008, Martín-López et al. 2009).

One of the uses of the Red List is to evaluate and monitor the state of biodiversity and a possible approach for this purpose is the Red List Index (RLI). The RLI helps to develop a better understanding of which taxa, regions or ecosystems are declining or improving their conservation status. It provides policy makers, stakeholders, conservation practitioners and the general public with sound knowledge of biodiversity status and change and tools with which to make informed decisions. The RLI uses weight scores based on the Red List status of each of the assessed species. These scores range from 0 (Least Concern) to 5 (Extinct/Extinct in the Wild). Summing these scores across all species, relating them to the worst-case scenario - all species extinct and comparing two or more points in time gives us an indication of how biodiversity is doing. At a global level, the RLI has been calculated for birds (Butchart et al. 2004, Hoffman et al. 2010), mammals (Hoffman et al. 2011), amphibians (Hoffman et al. 2010), corals (Butchart 2010) and cycads (United Nations 2015).

For many taxa, mainly hyperdiverse groups, it is not possible within available resources to assess all known species. In such cases, a random sample of species might be selected for assessment and the results derived from it extrapolated for the entire group - the Sampled Red List Index (SRLI, Baillie et al. 2008). The SRLI is now being developed for plants (Brummitt et al. 2015) and efforts towards a SRLI for butterflies (Lewis and Senior 2011) and are also in progress (Clausnitzer 2009).

Spiders currently comprise over 47000 species described at a global level (World Spider Catalog 2018). Of these, only 199 species (0.4%) have been assessed (www.redlist.org), of which the vast majority are from the Seychelles Islands or belong to the golden-orb weavers, (e.g. Kuntner et al. 2017). To these, a large number will be added in the near future, such as 55 species endemic to the Madeira and Selvagens archipelagos and 25 endemic to the Azores, all in Portugal (Cardoso et al. 2017, Borges et al. submitted). The vast majority of spiders assessed to date are therefore either regionally or taxonomically clustered and do not represent the group as a whole. With the current contribution and the three following papers, we intend to create the first point in time of a future spider SRLI encompassing 200 species distributed across the world.

Methods

A sample of 200 species of spiders were randomly selected from the World Spider Catalog (2018), an updated global database containing all recognised species names for the group. The 200 selected species were divided taxonomically at the family level and those familes were ordered alphabetically. In this publication, we present the conservation profiles of 46 species belonging to the families alphabetically arranged between and , which encompassed , , , , , , , , , , , , , and .

Species data were collected from all taxonomic bibliography available at the World Spider Catalog (2018), complemented by data in other publications found through Google Scholar and georeferrenced points made available through the Global Biodiversity Information Facility (www.gbif.org) and also other sources (https://www.biodiversitylibrary.org; https://login.webofknowledge.com; http://srs.britishspiders.org.uk; http://symbiota4.acis.ufl.edu/scan/portal; https://lepus.unine.ch; http://www.tuite.nl/iwg/Araneae/SpiBenelux/?species; https://atlas.arages.de; https://arachnology.cz/rad/araneae-1.html; http://www.ennor.org/iberia/). Whenever possible, with each species record, we also collected additional information, namely habitat type and spatial error of coordinates.

For all analyses, we used the R package red - IUCN redlisting tools (Cardoso 2017). This package performs a number of spatial analyses based on either observed occurrences or estimated ranges. Functions include calculating Extent of Occurrence (EOO), Area of Occupancy (AOO), mapping species ranges, species distribution modelling using climate and land cover information, calculating the Red List Index for groups of species, amongst others. In this work, the EOO and AOO were calculated in one of two ways:

- for range restricted species, for which we assumed knowledge of the full range, these values were classified as observed, the minimum convex polygon encompassing all observations used to calculate the EOO and the 2 km x 2 km cells known to be occupied and used to calculate the AOO. When the EOO was smaller than the AOO, it was made equal as per the IUCN guidelines (IUCN Standards and Petitions Subcommittee 2017).

- for widespread species or those for which we did not have confidence to know the full range, we performed species distribution modelling (SDM). This was done based on both climatic (Fick and Hijmans 2017) and landcover (Tuanmu and Jetz 2014) datasets, at an approximately 1x1 km resolution. Before modelling, the world layers were cropped to the region of interest to each species and reduced to four layers through a PCA to avoid overfitting. In addition, latitude and longitude were used as two extra layers to avoid the models predicting presences much beyond the known region following the precautionary principle. We then used the Maxent method (Phillips et al. 2006) implemented in the R package red. Isolated patches outside the original distribution polygon were excluded from maps to avoid overestimation of EOO and AOO values. All final maps and values were checked and validated by our own expert opinion. KMLs derived from these maps were also produced using the red package. The cells (2x2 km) predicted to be occupied were used to calculate the AOO. When the EOO was smaller than the AOO, it was made equal as per the IUCN guidelines (IUCN Standards and Petitions Subcommittee 2017).

To infer on possible changes in range and/or abundance and for forest species only, we have also consulted the Global Forest Watch portal (Global Forest Watch 2014), looking for changes in forest cover during the last 10 years that could have affected the species.

Distribution of Shimojana, 1989

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Distribution of (Chamberlin & Ivie, 1942)

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Distribution of (Marples, 1959)

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Distribution of Leech, 1972

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Distribution of Leech, 1972

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Distribution of Brescovit, 1993

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Distribution of (L. Koch, 1866)

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Distribution of Chickering, 1937

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Distribution of (O. P.-Cambridge, 1898)

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Distribution of (Keyserling, 1879)

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Distribution of (Keyserling, 1865)

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Distribution of (Simon, 1889)

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Distribution of (O. P.-Cambridge, 1885)

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Distribution of Yin et al, 1990

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Distribution of Levi, 1999

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Distribution of Yin & Zhao, 1994

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Distribution of L. Koch, 1843

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Distribution of Marusik, 1987

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Distribution of Schenkel, 1953

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Distribution of Levi, 1995

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Distribution of Levi, 1995

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Distribution of Chamberlin and Ivie, 1942

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Distribution of (Benoit, 1963)

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Distribution of Levi, 1995

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Distribution of (Simon, 1908)

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Distribution of Levi, 1995

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Distribution of Levi, 1991

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Distribution of Rix & Harvey, 2011

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Distribution of Rix & Harvey, 2012

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Distribution of Raven, 1994

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Raven & Churchill, 1994

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Distribution of Raven, 1994

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Distribution of Kritscher, 1966

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Distribution of Wunderlich & Schuett, 1995

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Distribution of Schenkel, 1936

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Distribution of (Thorell, 1895)

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Distribution of (Caporiacco, 1955)

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Distribution of Thorell, 1890

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Distribution of (F. O. P.-Cambridge, 1897)

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Dsitribution of Strand, 1907

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Distribution of Tucker, 1917

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Distribution of Griswold, 1987

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Distribution of (Banks, 1898)

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Distribution of Beladjal & Bosmans, 1996

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Distribution of Rossi, 1846

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Distribution of Li, 1994

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