Biodiversity Data Journal : Data Paper (Biosciences)
PDF
Data Paper (Biosciences)
Assessing the effects of climate change on arthropod abundance in Azorean pastures: PASTURCLIM project's baseline monitoring data
expand article infoSophie Wallon, Catarina Melo‡,§, Noelline Tsafack‡,|, Rui B. Elias, Paulo A. V. Borges‡,
‡ Centre for Ecology, Evolution and Environmental Changes (cE3c)/Azorean Biodiversity Group, CHANGE – Global Change and Sustainability Institute, Faculty of Agricultural Sciences and Environment, University of the Azores, Rua Capitão João d´Ávila, Pico da Urze, 9700-042, Angra do Heroísmo, Azores, Portugal
§ CFE – Centre for Functional Ecology, 3001-401 Coimbra, Portugal
| Regional Secretariat of Environment and Climate Change, Project LIFE BEETLES (LIFE 18NAT/PT/000864), Rua do Galo n118, 9700-040, Angra do Heroísmo, Azores, Portugal
¶ IUCN SSC Mid-Atlantic Islands Invertebrate Specialist Group, Angra do Heroísmo, Azores, Portugal
Open Access

Abstract

Background

The data we present are part of the project PASTURCLIM (Impact of climate change on pasture’s productivity and nutritional composition in the Azores). The project aims to assess the consequences of climate change (e.g. temperature increase) on the grass production and its quality for forage, as well as to assess changes in the arthropod communities associated with the Azorean intensive pastures. An in situ experiment was set up using Open Top Chambers (OTCs), in order to simulate an increasing of temperature (average of +1.2ºC) on pastures. In this contribution, we present the data relative to the arthropod sampling.

New information

We provide an inventory of all arthropods recorded inside OTCs and in control plots in three intensively managed pastures dominated by grasses in Terceira Island (Azores): two of them dominated by ryegrass, Lolium multiflorum Lam. (Poaceae), located respectively at 186 m and 301 m above sea level; and one field dominated by common velvetgrass, Holcus lanatus L. (Poaceae), located at an altitude of 385 m.

A total of 41351 specimens were collected. Organisms collected belong to four classes, 15 orders, 60 families and 171 species/morphospecies (including 34 taxa identified only at order, family or genus level). Therefore, for only 137 taxa, we have a scientific name associated (n = 38918). A total of 75% of the species (n = 129 species) are considered introduced (including all the species with indeterminate colonisation status that are possibly also exotic species (n = 7622)), representing 71% of the total abundance (n = 29664 specimens). A total of 19% of the species (n = 33 species) are considered native non-endemic representing 28% of the total abundance (n = 11608 specimens). Only one endemic species was sampled, the wolf spider Pardosa acorensis Simon, 1883 (1% of the species), representing 0.2% of the total abundance (n = 79 specimens). Spiders (5056 specimens) and beetles (18310 specimens) were the dominant taxa representing, respectively, 20 and 78 morphospecies.

Since the main aim of this study was to have a better knowledge on arthropod communities present in Azorean pastures under a simulated temperature increase, the principal novelty of this paper is the contribution with distribution and abundance data to a baseline knowledge on the future consequences of climate changes on arthropod communities in Azorean pastures.

Keywords

arthropods, climate change, grasses, Open Top Chamber, pasture, pitfall traps.

Introduction

Climatic changes occurring on Earth imply mainly changes in temperature (Arnell et al. 2019, Pörtner et al. 2022) and in rainfall patterns (Ohba and Sugimoto 2019, Papalexiou and Montanari 2019), which affect ecosystems as well as their biodiversity (Sharma and Dhillon 2018, Habibullah et al. 2022). Grasslands used as forage crops are affected at different levels by the increase of temperature: i) Increased growth rate, in which higher temperatures can stimulate the growth rate of forage crops. As a result, grasslands can produce more forage, which can be beneficial for livestock. However, changes in seasonal precipitation would reduce these benefits, particularly in areas with low summer rainfall (Hopkins and Del Prado 2007); ii) Drought stress, in which higher temperatures comes with the higher risk of drought, which can be detrimental to the growth of forage crops. Drought stress can reduce the yield of grasslands and result in poor-quality forage; iii) Changes in plant composition (Feeley et al. 2020), in which some species may become less abundant, while others may thrive, which can alter the nutritional value of the forage, decreasing protein and mineral nutrient concentrations, as well as altering lipid composition (DaMatta et al. 2010); iv) Changes in plant phenology, in which some grasses are affected as well as their functional traits and chemical composition (Lee et al. 2013, Piao et al. 2019, Ekholm et al. 2020, Melo et al. 2022). All these factors can lead to cascading effects on biodiversity and on ecosystem services (Selvaraj et al. 2013, Banerjee et al. 2018, Garcia et al. 2018, Mirás-Avalos and Baveye 2018, Moss and Evans 2022).

Adaptation to climate change for agriculture will be definitively a crucial point to overpass in order to avoid an economic crisis in the coming years (Aguiar et al. 2018, Rivera et al. 2018, Vizinho et al. 2021). Regarding wildlife, there has been great concern for many years concerning the decline of arthropods (Wilson 1987, Brantley and Ford 2012, Seibold et al. 2019, Halsch et al. 2021). In anthropised ecosystems such as for crops or pastures, they are responsible for many ecosystem services (e.g. pollination, decomposition of organic matter, pest control and predation), but can also be responsible for ecosystem disservices (e.g. pest, parasitism, herbivory, seed predation, crop damage) (Cardenas et al. 2022, Ferrante et al. 2022). Climate changes may also affect this balance of services and disservices by inducing shifts in species composition (Harter et al. 2015). Climate changes may influence species presence/absence, fluctuation of abundances and can even favour the dominance of some species in the ecosystem with the threat of creating a boom of pest species (Buchholz et al. 2013, Sohlström et al. 2022). The risk is higher on island ecosystems because of the limited area available and the usually lower altitudinal range. Therefore, climate changes represent a real threat for island biodiversity (Harter et al. 2015, Borges et al. 2019, Veron et al. 2019, Pörtner et al. 2022).

Predictions for the Azores suggest a temperature increase between 1.6 and 2.72°C till the end of the century (respectively following the two scenarios from the PRAC: RCP4.5 and RCP 8.5). Changes in the rainfall pattern are also expected due to the increase in heavy rains and storms in the winter and prolonged droughts during the summer (Costa et al. 2017).

Nowadays, the main activity in the Azores is dairy and meat production. Thus, most of the land between the sea level and middle altitude (500 m) is used for agriculture (e.g. intensive pasture and forage crops) representing 56% of the territory (Costa et al. 2017). The impact of temperature increase on the arthropod communities of Azorean pastures is unknown.

Therefore, an in-situ experiment was established to collect baseline data in order to help understand how the increase of the temperature affects the arthropod communities associated with intensive pastures in the Azores.

General description

Purpose: 

To provide baseline data on arthropod species richness and abundance from intensively managed pasture in Terceira Island (Azores) under natural and modified climatic conditions (e.g. increase in temperature via Open Top Chambers - OTCs). These data will allow us to assess the effects of climate change on arthropod’s communities in Azorean pastures.

Additional information: 

Open Top Chambers (OTCs) are raised from the floor (around 5 cm) and allow free movement of all crawling arthropods around the pasture. Instead, for flying arthropods, OTCs represent an artificial barrier and data collected would present a bias due to this obstacle. Therefore, we focused on the collection of crawling arthropods using pitfall traps filled with ethylene glycol.

Project description

Title: 

PASTURCLIM - Impact of climate change on pasture’s productivity and nutritional composition in the Azores

Personnel: 

Project leaders: Rui B. Elias

Team members: Paulo A. V. Borges, Sophie Wallon, Catarina D. Melo.

External Consultants : Teresa M. Ferreira.

Parataxonomists: Sophie Wallon; Mauro Matos.

Taxonomist: Paulo A. V. Borges.

Darwin Core Database management: Paulo A. V. Borges, Sophie Wallon.

Fieldwork: Sophie Wallon, Catarina D. Melo, Rui B. Elias.

Study area description: 

The study was conducted on the Archipelago of the Azores (North Atlantic), on Terceira Island (decimal coordinates 38.712925, -27.234912) which is the third largest island of the Archipelago with 400.2 km2 and a maximum altitude above sea level of 1021 m. The Azores are from volcanic origin and have a temperate oceanic climate, relatively wet with mild temperature at low altitude, all year long.

Design description: 

The study areas were intensive pastures located at different elevations (Table 1). All pastures were dominated by grasses. The two fields at lower elevations (A and B) were covered by the annual ryegrass, Lolium multiflorum Lam. (Poaceae) and the field at higher elevation (C) was covered by the perennial common velvetgrass, Holcus lanatus L. (Poaceae).

Table 1.

Description of the locality, habitat, elevation and coordinates (in decimal degrees) of the three fields sampled in Terceira island, Azores.

Locality

Site Code

Habitat

Grass cover species

Elevation (m)

Longitude

Latitude

Santa Bárbara-Field_A

A

Pasture

Lolium multiflorum

186

-27.35381

38.70351

Santa Bárbara-Field_B

B

Pasture

Lolium multiflorum

301

-27.32578

38.70164

Granja da Universidade-Field_C

C

Pasture

Holcus lanatus

385

-27.17008

38.69777

Funding: 

Core funding was obtained from the Project PASTURCLIM (ACORES-01-0145-FEDER-000082) financed by FEDER at 85% and by Azorean Public funds at 15% through the Operational Programme Azores 2020.

Additional funding was secured from the projects FCT-UIDB/00329/2020-2024 (Thematic Line 1 – integrated ecological assessment of environmental change on biodiversity) and Azores DRCT Pluriannual Funding (M1.1.A/FUNC.UI&D/010/2021-2024).

SW is currently being funded by the Ph.D. Grant DRCT - M3.1.a/F/018/2020 (2021-2024).

Darwin-Core and GBIF management were funded by the project Portal da Biodiversidade dos Açores (2022-2023) - PO Azores Project - M1.1.A/INFRAEST CIENT/001/2022.

Sampling methods

Description: 

The study was conducted in three intensive pastures on Terceira Island (Azores) (Fig. 1). In each field, 20 plots (1 x 1 m) were set up in an area of 100m2 where cattle were not allowed. Amongst those 20 plots, 10 were randomly chosen to be surrounded by an OTCs (in order to simulate an increase of +1.2ºC average), while the other 10 were considered as control plots. OTCs were built including a 1 m2 plot and a margin of 25 cm all around. The aim of this margin was to allow the same set-up of the pitfall traps as in the control plots (e.g. with one pitfall trap at each corner); it also allows free space for scientists to enter inside the OTCs without stepping on the plot. Temperature and relative humidity were recorded through data loggers (Easy Log: EL-USB-2) in control plots and inside OTCs.

Figure 1.  

Picture and localisation of each field on the island of Terceira. Each experimental area is covered with 10 control plots and 10 plots surrounded by an OTC (Photo credits: Sebeyes Production).

Sampling description: 

The focus of the study were the arthropods associated with pasture for foraging production. As OTCs represent a physical barrier for flying insects, our focus was made on crawling arthropods. OTCs were raised about 5 cm above the ground and allowed arthropod movement around the experimental area. Pitfall traps were then used for the sampling.

Grasses inside each plot were seasonally and manually harvested to evaluate the biomass. Therefore, pitfall traps were set up and collected before harvesting grasses.

Pitfalls were set up for 14 days, in each field, in the winter of 2020. During the summer of 2020, in the fields A and C, pitfall traps were set up for 14 days, while they were set up for 13 days in Field B.

Pitfall traps consisted in a 330 ml plastic cups, about 12 cm deep and 8 cm of diameter at the top (Fig. 2). Traps were filled with ethylene glycol. We used car’s cooling liquid at 20% ethylene glycol and added few drops of soap to break the water tension. Specimens collected were then stored into ethanol (96%).

Figure 2.  

A pitfall trap. The trap was then covered with a plastic dish raised from the ground to avoid overflow of the trap due to eventual rainfall (Photo credit: Sophie Wallon).

For each season (winter and summer), four pitfall traps were set up on each corner of each plot resulting in four traps per plot (Fig. 3). All traps were were active for 14 days, except during the summer, in field B, where the traps were active for 13 days.

Figure 3.  

Set-up of an OTC plot (a) and a control plot (b) (Photo credits: Sophie Wallon)

In the winter (March 2020) and before sorting arthropods, the four traps of each plot were merged into one sample corresponding to the plot. For this reason, for the winter 2020 period, only the pitfall number 1 (PTF_1) appears in the column “eventID” that corresponds to four pitfall traps merged into one single sample. Then in the summer (September 2020), each pitfall trap was kept separately before sorting, resulting in four pitfalls for each plot (PTF_1; PTF_2; PTF_3; PTF_4).

In the Event table, the location ID name includes the following information:

Code Site (A, B or C), Control (C) or Treatment with OTCs (T), Plot Number (1 to 10) _ Year of collection - Month of collection_ Pitfall trap (PTF)_ Pitfall number (1 to 4).

For example, the location ID “AC7_2020-09_PTF_3” corresponds to the “Field A Control Plot number 7_ collected in September 2020_ Pitfall trap _ Number 3”

Quality control: 

After collection, specimens were stored in ethanol (96%) before sorting. Specimens, adults and juveniles, were identified in the laboratory by a trained parataxonomist (Sophie Wallon) and organised following a system of morphospecies (Oliver and Beattie 1996). Final identification was done by the senior author (Paulo A. V. Borges).

For each species identified, a colonisation status (Endemic, Native (non-endemic), Introduced, Indeterminate) named as “establishmentMeans” in the Occurrence table, was attributed following Borges et al. (2022).

Step description: 

Specimens were identified, based on the Azorean arthropods collection “Dalberto Teixeira Pombo Insect Collection (DTP), University of Azores” created and maintained by Professor Paulo A. V. Borges. A new collection reference was created, in the framework of the project PASTURCLIM, referencing each species occurring in the present dataset. If the specimen observed did not correspond to species/morphospecies recorded in any specimen already recorded in the Azorean arthropods collection or if its identification was not possible, then a new morphospecies number was attributed to that specimen (identificationRemarks in Occurrence table).

Geographic coverage

Description: 

Terceira Island, Azores, Portugal.

Coordinates: 

-27.394 and -27.0150 Latitude; 38.814 and 38.638 Longitude.

Taxonomic coverage

Description: 

The following classes and orders of arthropods are covered:

Arachnida: Araneae, Opiliones, Pseudoscorpiones; Chilopoda: Lithobiomorpha, Scutigeromorpha; Diplopoda: Julida, Polydesmida; and Insecta: Coleoptera, Dermaptera, Hemiptera, Hymenoptera, Lepidoptera, Neuroptera, Orthoptera, Psocoptera.

Taxa included:
Rank Scientific Name Common Name
class Arachnida Arachnids
order Araneae Spiders
order Opiliones Harvestmen
order Pseudoscorpiones Pseudoscorpions
class Chilopoda Centipedes
order Lithobiomorpha Centipedes
order Scutigeromorpha Centipedes
class Diplopoda Millipedes
order Julida Millipedes
order Polydesmida Millipedes
class Insecta Insects
order Coleoptera Beetles
order Dermaptera Earwigs
order Hemiptera Bugs
order Hymenoptera Ants
order Lepidoptera Moths
order Neuroptera Lacewings
order Orthoptera Crickets, Grasshoppers
order Psocodea Psocids, Barklice, Booklice

Temporal coverage

Notes: 

Winter 2020 (03-2020):

Field A: 20 February 2020 till 5 March 2020 (14 days)

Field B: 26 February 2020 till 11 March 2020 (14 days)

Field C: 24 February 2020 till 9 March 2020 (14 days)

Summer 2020 (09-2020):

Field A: 24 August 2020 till 7 September 2020 (14 days)

Field B: 25 August 2020 till 7 September 2020 (13 days)

Field C: 27 August 2020 till 10 September 2020 (14 days)

Collection data

Collection name: 
Entomoteca Dalberto Teixeira Pombo at University of Azores
Collection identifier: 
DTP
Specimen preservation method: 
All specimens were preserved in 96% ethanol.
Curatorial unit: 
Dalberto Teixeira Pombo insect collection at the University of the Azores (Curator: Paulo A. V. Borges)

Usage licence

Usage licence: 
Creative Commons Public Domain Waiver (CC-Zero)

Data resources

Data package title: 
Monitoring grassland’s arthropods in an in situ climate change experimentation (Terceira, Azores, Portugal)
Number of data sets: 
2
Data set name: 
Event Table
Character set: 
UTF-8
Data format: 
Darwin Core Archive
Data format version: 
Version 1.4
Description: 

The dataset is available on the Global Biodiversity Information Facility platform, GBIF (Wallon et al. 2023). The event table dataset is organied following the Darwin Core Archive (DwCA) format and contains 297 records (eventID).

Column label Column description
eventID An identifier for every single event and specific to the dataset.
samplingProtocol The methods or protocols used during an Event.
sampleSizeValue A numeric value for a measurement of the size (time duration, length, area or volume) of a sample in a sampling event.
sampleSizeUnit The unit of measurement of the size (time duration, length, area or volume) of a sample in a sampling event.
samplingEffort The amount of effort expended during an Event.
eventDate Date or date range the record was collected.
year Year of the event.
month Month of the event.
verbatimEventDate The verbatim original representation of the date and time information.
habitat Description of the habitat in which the Event occurred.
fieldNotes Note to facilitate the characterisation of the plot treatment: Control plot or plot surrounded by an Open Top Chamber.
locationID An identifier for the set of location information (specific to the dataset).
islandGroup Name of the archipelago of the sampling site.
island Name of the island of the sampling site (Terceira Island).
country Name of the country of the sampling site.
countryCode The standard code for the country in which the Location occurs.
stateProvince An identifier for every single event and specific to the dataset.
municipality Municipality of the sampling site.
locality Name of the locality.
minimumElevationInMetres The lower limit of the range of elevation (altitude, usually above sea level), in metres.
maximumElevationInMetres The highest limit of the range of elevation (altitude, usually above sea level), in metres.
decimalLatitude Geographic coordinate (Decimal degrees): sampling location Latitude.
decimalLongitude Geographic coordinate (Decimal degrees): sampling location Longitude.
geodeticDatum Spatial reference system (SRS) upon which the geographic coordinates given in decimalLatitude and decimalLongitude are based.
coordinateUncertaintyInMetres Coordinates' uncertainty in metres to the site of the true sampling area.
coordinatePrecision A decimal representation of the precision of the coordinates given in the decimalLatitude and decimalLongitude.
georeferenceSources A map, gazetteer or other resource used to georeference the Location.
Data set name: 
Occurrences table
Character set: 
UTF-8
Data format: 
Darwin Core Archive
Data format version: 
version 1.4
Description: 

The dataset is available on the Global Biodiversity Information Facility platform, GBIF (Wallon et al. 2023). The occurrence table dataset is organised following the Darwin Core Archive (DwCA) format and contains 6051 records (occurrenceID).

Column label Column description
Event ID An identifier for every single event and specific to the dataset.
type The type of the related resource.
licence Information about rights held in and over the resource.
institutionID An identifier for the institution having custody of the object(s) or information referred to in the record.
collectionID An identifier for the collection or dataset from which the record was derived.
institutionCode The name in use by the institution having custody of the object(s) or information referred to in the record.
collectionCode The acronym identifying the collection or dataset from which the record was derived.
datasetName The name identifying the dataset from which the record was derived.
basisOfRecord The specific nature of the data record.
occurrenceID An identifier built as a "Globally Unique IDentifier".
recordedBy Names of people responsible for recording the original occurrence.
organismQuantity A number for the quantity of organisms.
organismQuantityType The type of quantification system used for the quantity of organisms.
sex The sex of the biological individual(s) represented in the occurrence.
lifeStage The age class or life stage of the Organism(s) at the time the Occurrence was recorded.
establishmentMeans The process of establishment of the species in the location, using a controlled vocabulary: 'native', 'introduced', 'indeterminate'.
occurrenceRemarks Comments or notes about the Occurrence mentioning the 'endemic' species.
identifiedBy Names of people who assigned the Taxon to the subject.
dateIdentified The date on which the subject was determined as representing the Taxon.
identificationRemarks Dalberto Teixeira Pombo (DTP) collection's morphospecies number attributed to specimens identified.
scientificName Full scientific name, with authorship and date information, if known. When identification to species level was not possible, then it is the name in the lowest level taxonomic rank that can be determined.
kingdom Scientific name of the kingdom in which the taxon is classified.
phylum Scientific name of the phylum in which the taxon is classified.
class Scientific name of the class in which the taxon is classified.
order Scientific name of the order in which the taxon is classified.
family Scientific name of the family in which the taxon is classified.
genus Scientific name of the genus in which the taxon is classified.
subgenus Scientific name of the sub genus in which the taxon is classified.
specificEpithet The species epithet of the scientific name.
infraspecificEpithet Name of the lowest or terminal infraspecific epithet of the scientific name.
taxonRank The taxonomic rank of the most specific name in the scientific name.
scientificNameAuthorship The authorship information related to the scientific name.

Additional information

We collected a total 41,351 specimens belonging to four classes, 15 orders, 60 families and 171 morphospecies (including 34 taxa identified only at order, family or genus level). Therefore, 137 taxa have a scientific name associated (n = 38918) (from now on “species”) Table 2.

Table 2.

Inventory of arthropods collected in three pastures (Fields A, B and C) in Terceira Island (Azores, Portugal) in control plots (C) and plots surrounded by an OTC (T).

AC - Field A control plot; AT - Field A plot OTC; BC - Field B control plot; BT - Field B plot OTC; CC - Field C control plot; CT - Field C plot OTC.

The list includes only the specimens identified at species-level. Class, order, family and scientific name follow alphabetical sequence. Colonisation statuses, based on Borges et al. (2022) and abundance per field and treatment, are provided. Colonisation status (Origin): END - Endemic; NAT - native non-endemic; INTR - introduced; IND - indeterminate.

Family Scientific Name Origin AC AT BC BT CC T Total
Arachnida Araneae
Dysderidae Dysdera crocata C. L. Koch, 1838 INTR 3 3 1 11 2 12 32
Gnaphosidae Marinarozelotes lyonneti (Audouin, 1826) INTR 1 1
Gnaphosidae Zelotes aeneus (Simon, 1878) INTR 2 2 4
Linyphiidae Agyneta fuscipalpa (C. L. Koch, 1836") INTR 98 58 1 1 1 159
Linyphiidae Erigone atra Blackwall, 1833 INTR 3 4 1 182 67 257
Linyphiidae Erigone autumnalis Emerton, 1882 INTR 148 88 79 67 54 9 445
Linyphiidae Erigone dentipalpis (Wider, 1834) INTR 109 52 87 95 569 248 1160
Linyphiidae Mermessus bryantae (Ivie & Barrows, 1935) INTR 10 8 4 5 25 42 94
Linyphiidae Mermessus fradeorum (Berland, 1932) INTR 5 8 20 24 99 102 258
Linyphiidae Neriene clathrata (Sundevall, 1830) INTR 1 1 2
Linyphiidae Oedothorax fuscus (Blackwall, 1834) INTR 170 151 72 65 975 473 1906
Linyphiidae Ostearius melanopygius (O. Pickard-Cambridge, 1880) INTR 23 43 12 44 3 125
Linyphiidae Prinerigone vagans (Audouin, 1826) INTR 13 9 2 5 13 4 46
Linyphiidae Tenuiphantes tenuis (Blackwall, 1852) INTR 43 69 30 80 41 71 334
Lycosidae Pardosa acorensis Simon, 1883 END 1 50 28 79
Mimetidae Ero furcata (Villers, 1789) INTR 1 1
Oecobiidae Oecobius navus Blackwall, 1859 INTR 1 1
Tetragnathidae Pachygnatha degeeri Sundevall, 1830 INTR 33 67 7 34 141
Theridiidae Cryptachaea blattea (Urquhart, 1886) INTR 3 3
Zodariidae Zodarion atlanticum Pekár & Cardoso, 2005 INTR 3 3 1 7
Arachnida Opiliones
Leiobunidae Leiobunum blackwalli Meade, 1861 NAT 2621 1313 3934
Sclerosomatidae Homalenotus coriaceus (Simon, 1879) NAT 1 5 73 283 71 68 501
Arachnida Pseudoscorpiones
Chthoniidae Chthonius ischnocheles (Hermann, 1804) INTR 1 1
Neobisiidae Neobisium maroccanum Beier, 1930 INTR 1 1 2
Chilopoda Lithobiomorpha
Lithobiidae Lithobius pilicornis pilicornis Newport, 1844 NAT 2 5 7 15 25 13 67
Chilopoda Scutigeromorpha
Scutigeridae Scutigera coleoptrata (Linnaeus, 1758) INTR 13 39 1 53
Diplopoda Julida
Blaniulidae Blaniulus guttulatus (Fabricius, 1798) INTR 1 5 6
Blaniulidae Nopoiulus kochii (Gervais, 1847) INTR 2 1 3
Blaniulidae Proteroiulus fuscus (Am Stein, 1857) INTR 2 4 4 10
Julidae Cylindroiulus propinquus (Porat, 1870) INTR 1 1 1 19 15 37
Julidae Ommatoiulus moreleti (Lucas, 1860) INTR 504 278 21 25 60 186 1074
Diplopoda Polydesmida
Paradoxosomatidae Oxidus gracilis (C.L. Koch, 1847) INTR 2 7 10 19
Polydesmidae Polydesmus coriaceus Porat, 1870 INTR 107 72 108 164 215 276 942
Insecta Coleoptera
Anthicidae Hirticollis quadriguttatus (Rossi, 1792) NAT 3 2 5
Aphodiidae Calamosternus granarius (Linnaeus, 1767) INTR 5 1 1 7
Apionidae Aspidapion radiolus (Marsham, 1802) NAT 1 13 1 6 11 32
Carabidae Agonum muelleri muelleri (Herbst) INTR 3 3
Carabidae Amara aenea (De Geer, 1774) INTR 6 1 7
Carabidae Anisodactylus binotatus (Fabricius, 1787) INTR 3 3 87 33 190 88 404
Carabidae Bembidion ambiguum Dejean, 1831 INTR 1 3 1 3 1 9
Carabidae Calosoma olivieri Dejean, 1831 NAT 2 2 16 30 1 1 52
Carabidae Harpalus distinguendus distinguendus (Duftschmidt, 1812) INTR 139 198 23 13 373
Carabidae Laemostenus complanatus (Dejean, 1828) INTR 1 5 6
Carabidae Notiophilus quadripunctatus Dejean, 1826 NAT 287 191 44 48 570
Carabidae Ophonus ardosiacus (Lutshnik, 1922) INTR 1 1
Carabidae Paranchus albipes (Fabricius, 1796) INTR 28 170 198
Carabidae Pseudoophonus rufipes (De Geer, 1774) INTR 247 127 3343 2480 285 466 6948
Carabidae Pterostichus vernalis (Panzer, 1796) INTR 3 19 6 567 709 1304
Carabidae Stenolophus teutonus (Schrank, 1781) NAT 1 30 5 36
Chrysomelidae Epitrix cucumeris (Harris, 1851) INTR 1 1
Chrysomelidae Epitrix hirtipennis (Melsheimer, 1847) INTR 1 1
Coccinellidae Rhyzobius lophanthae (Blaisdell, 1892) INTR 1 1
Coccinellidae Scymnus interruptus (Goeze, 1777) NAT 3 1 4
Coccinellidae Scymnus nubilus Mulsant, 1850 NAT 3 1 4
Corylophidae Sericoderus lateralis (Gyllenhal, 1827) INTR 6 18 2 1 1 28
Curculionidae Coccotrypes carpophagus (Hornung, 1842) INTR 1 1 4 6
Curculionidae Mecinus pascuorum (Gyllenhal, 1813) INTR 1 1
Curculionidae Orthochaetes insignis (Aubé, 1863) NAT 1 1
Curculionidae Sitona discoideus Gyllenhal, 1834 INTR 49 16 8 24 10 2 109
Curculionidae Tychius picirostris (Fabricius,1787) INTR 2 2
Dryophthoridae Sitophilus oryzae (Linnaeus, 1763) INTR 1 1
Dryophthoridae Sphenophorus abbreviatus (Fabricius, 1787) INTR 31 10 8 7 5 3 64
Dryopidae Dryops luridus (Erichson, 1847) NAT 1 14 11 26
Elateridae Aeolus melliculus moreleti Tarnier, 1860 INTR 52 12 12 5 5 86
Elateridae Melanotus dichrous (Erichson, 1841) INTR 3 1 16 13 33
Hydrophilidae Cercyon haemorrhoidalis (Fabricius, 1775) INTR 39 3 13 6 13 1 75
Hydrophilidae Sphaeridium bipustulatum Fabricius, 1781 INTR 1 1
Latridiidae Cartodere nodifer (Westwood, 1839) INTR 4 4
Mycetophagidae Litargus balteatus Le Conte, 1856 INTR 1 1
Mycetophagidae Typhaea stercorea (Linnaeus, 1758) INTR 15 11 3 29
Nitidulidae Carpophilus fumatus Boheman, 1851 INTR 2 1 3
Nitidulidae Epuraea biguttata (Thunberg, 1784) INTR 3 1 4
Nitidulidae Phenolia limbata tibialis (Boheman, 1851) INTR 1 1
Nitidulidae Stelidota geminata (Say, 1825) INTR 4 1 8 1 2 16
Phalacridae Stilbus testaceus (Panzer, 1797) NAT 1 1 2
Ptiliidae Ptenidium pusillum (Gyllenhal, 1808) INTR 2 1 3 3 1 1 11
Scarabaeidae Onthophagus taurus (Schreber, 1759) INTR 1 1 11 13 5 31
Scarabaeidae Onthophagus vacca (Linnaeus, 1767) INTR 2 1 1 4
Staphylinidae Aleochara bipustulata (Linnaeus, 1760) IND 8 2 2 31 3 46
Staphylinidae Aleochara verna Say, 1833 IND 1 1
Staphylinidae Aloconota sulcifrons (Stephens, 1832) IND 13 1 6 20
Staphylinidae Amischa analis (Gravenhorst, 1802) IND 36 21 39 68 408 110 682
Staphylinidae Amischa forcipata Mulsant & Rey, 1873 IND 3 24 4 31
Staphylinidae Anotylus nitidifrons (Wollaston, 1871) IND 1429 621 125 33 284 47 2539
Staphylinidae Anotylus nitidulus (Gravenhorst, 1802) IND 9 3 3 3 18
Staphylinidae Astenus lyonessius (Joy, 1908) IND 1 1
Staphylinidae Atheta aeneicollis (Sharp, 1869) IND 1 3 12 16
Staphylinidae Atheta fungi (Gravenhorst, 1806) IND 42 1 43
Staphylinidae Atheta palustris (Kiesenwetter, 1844) IND 2 2 5 9
Staphylinidae Atheta pasadenae Bernhauer, 1806 IND 3 5 3 11
Staphylinidae Carpelimus corticinus (Gravenhorst, 1806) IND 1 1
Staphylinidae Carpelimus zealandicus (Sharp, 1900) INTR 6 6
Staphylinidae Coproporus pulchellus (Erichson, 1839) IND 1 1
Staphylinidae Cordalia obscura (Gravenhorst, 1802) IND 265 61 80 50 152 75 683
Staphylinidae Gabrius nigritulus (Gravenhorst, 1802) IND 1 6 1 8
Staphylinidae Gyrohypnus fracticornis (Müller, 1776) IND 10 4 29 32 26 17 118
Staphylinidae Ocypus olens (Müller, 1764) IND 97 108 303 484 6 23 1021
Staphylinidae Oligota pumilio Kiesenwetter, 1858 IND 18 57 2 16 12 24 129
Staphylinidae Oligota pusillima (Gravenhorst, 1806) IND 2 5 4 11
Staphylinidae Philonthus longicornis Stephens, 1832 IND 3 3
Staphylinidae Philonthus quisquiliarius quisquiliarius (Gyllenhal, 1810) IND 1 1
Staphylinidae Pseudoplectus perplexus (Jacquelin du Val, 1854) IND 2 1 3
Staphylinidae Quedius simplicifrons Fairmaire, 1862 IND 2 13 14 29
Staphylinidae Rugilus orbiculatus (Paykull, 1789) IND 802 214 159 148 108 41 1472
Staphylinidae Sepedophilus lusitanicus Hammond, 1973 IND 4 3 1 8
Staphylinidae Stenomastax madeirae Assing, 2003 IND 12 1 54 11 78
Staphylinidae Sunius propinquus (Brisout de Barneville, 1867) IND 3 3
Staphylinidae Tachyporus chrysomelinus (Linnaeus, 1758) IND 3 2 5
Staphylinidae Tachyporus nitidulus (Fabricius, 1781) IND 13 38 8 26 6 7 98
Staphylinidae Xantholinus longiventris Heer, 1839 IND 1 1 3 18 9 6 38
Tenebrionidae Blaps lethifera Marsham, 1802 INTR 1 1
Insecta Dermaptera
Anisolabididae Euborellia annulipes (Lucas, 1847) INTR 1 5 20 185 2 20 233
Forficulidae Forficula auricularia Linnaeus, 1758 INTR 1802 1482 75 69 8 30 3466
Insecta Hemiptera
Anthocoridae Anthocoris nemoralis (Fabricius, 1794) NAT 2 1 3
Aphididae Rhopalosiphoninus latysiphon (Davidson, 1912) INTR 4 17 1 1 1 24
Cicadellidae Anoscopus albifrons (Linnaeus, 1758) NAT 24 15 16 45 22 6 128
Cicadellidae Euscelidius variegatus (Kirschbaum, 1858) NAT 1 3 4 2 10
Cydnidae Geotomus punctulatus (A. Costa, 1847) NAT 245 60 22 6 333
Delphacidae Kelisia ribauti Wagner, 1938 NAT 2 1 23 2 28
Delphacidae Megamelodes quadrimaculatus (Signoret, 1865) NAT 19 3 22
Lygaeidae Kleidocerys ericae (Horváth) NAT 1 1
Nabidae Nabis pseudoferus ibericus Remane, 1962 NAT 7 1 2 3 1 14
Rhyparochromidae Beosus maritimus (Scopoli, 1763) NAT 18 4 1 1 24
Rhyparochromidae Scolopostethus decoratus (Hahn, 1833) NAT 35 18 1 1 55
Saldidae Saldula palustris (Douglas) NAT 1 1
Insecta Hymenoptera
Apidae Bombus ruderatus (Fabricius, 1775) INTR 1 1
Formicidae Hypoponera eduardi (Forel, 1894) NAT 89 91 308 161 2 651
Formicidae Lasius grandis Forel, 1909 NAT 230 310 192 305 89 67 1193
Formicidae Linepithema humile (Mayr, 1868) INTR 2 36 25 1 2 66
Formicidae Monomorium carbonarium (F. Smith, 1858) NAT 3 10 13
Formicidae Tetramorium caespitum (Linnaeus, 1758) NAT 1470 1296 204 89 3059
Insecta Lepidoptera
Noctuidae Mythimna unipuncta (Haworth, 1809) NAT 5 1 6
Insecta Neuroptera
Chrysopidae Chrysoperla agilis Henry et al., 2003 NAT 1 1 7 9
Chrysopidae Chrysoperla lucasina (Lacroix, 1912) NAT 1 1 7 9
Insecta Orthoptera
Gryllidae Eumodicogryllus bordigalensis (Latreille, 1804) INTR 23 8 56 13 80 20 200
Gryllidae Gryllus bimaculatus De Geer, 1773 INTR 9 9 5 2 25
Insecta Psocodea
Ectopsocidae Ectopsocus briggsi McLachlan, 1899 INTR 1 1
TOTAL 8909 6039 5859 5412 7636 5063 38918

Regarding the colonisation status, introduced species (also those with an "indeterminate" colonisation status that are most probably exotic species (n = 7622)) represented 71% (n = 29664 specimens) of the total abundance and 75% (129 species) of the total richness; 28% (n = 11608 specimens) of the total abundance and 19% (33 species) of the total richness were represented by native non-endemic species; finally, endemic species represented 0.2% (n = 79 specimens) of the total abundance and 1% (one species) of the total richness.

Spiders (Arachnida, Araneae) and beetles (Insecta, Coleoptera) were the two most diversified and abundant groups.

Altogether, Pseudoophonus rufipes (De Geer, 1774) (Coleoptera, Carabidae), an omnivorous ground beetle, dominated the samples and represented 17% of the total arthropod abundance. This ground beetle dominated summer samples, while the predator rove beetle Ocypus olens (Müller, 1764) (Coleoptera, Staphylinidae) dominated winter samples.

The dominant spider was Oedothorax fuscus (Blackwall, 1834) (Araneae, Linyphiidae) representing 5% of overall arthropod abundance. It was also the most dominant spider species in summer samples, while winter samples were dominated by the spider Erigone dentipalpis (Wider, 1834) (Araneae, Linyphiidae).

Some species distributions varied with elevation and consequently with the type of field. The ground-beetle Notiophilus quadripunctatus Dejean, 1826 (Coleoptera, Carabidae) dominated winter samples (n = 464, 14%) at the low altitude field (field A) and the European earwig Forficula auricularia Linnaeus, 1758 (Dermaptera) was the most abundant arthropod in the summer samples (n = 3177, 24%) of the same field; at the intermediate altitude field (field B), the rove beetle Ocypus olens (Müller, 1764) (Coleoptera, Staphylinidae) (n = 579, 25%) dominated winter samples and the ground beetle Pseudoophonus rufipes (De Geer, 1774) (Coleoptera, Carabidae) (n = 5822, 61%) summer samples; finally, the rove beetle Amischa analis (Gravenhorst, 1802) (Coleoptera, Staphylinidae) was the most abundant species during the winter (n = 211, 14%) in the upper altitude field (field C), while the harvestman Leiobunum blackwalli (Arachnida, Opiliones) (n = 3882, 33%) was the dominant species in summer.

Our study is responding to the need to have baseline data to understand long-term insect decline patterns (Seibold et al. 2019). Setting monitoring programmes using arthropods is important for understanding and managing pest populations, detecting environmental changes, assessing the impact of management practices and identifying potential threats to biodiversity (Borges et al. 2019).

Acknowledgements

We gratefully acknowledge Virginia Pires for giving permission to use pastures A and B. We also thank the Bachelor student Mauro Matos, for his help with the fieldwork and sorting the samples prior to species assignment by an expert taxonomist (P.A.V.B) during his internship.

This work was funded by the project PASTURCLIM (ACORES-01-0145-FEDER-000082) financed by FEDER at 85% and by Azorean Public funds at 15% through the Operational Programme Azores 2020. All authors were also funded by FCT-UIDB/00329/2020-2024 (Thematic Line 1 – integrated ecological assessment of environmental change on biodiversity) and Azores DRCT Pluriannual Funding (M1.1.A/FUNC.UI&D/010/2021-2024). Darwin-Core and GBIF management were funded by the project Portal da Biodiversidade dos Açores (2022-2023) - PO Azores Project - M1.1.A/INFRAEST CIENT/001/2022.

SW is currently being funded by the Ph.D. Grant DRCT - M3.1.a/F/018/2020.

Author contributions

SW, PAVB and RBE contributed to study conceptualisation. SW, CDM and RBE performed the fieldwork. SW and PAVB performed the species sorting and identification. SW, NT and PAVB contributed to dataset preparation and data analysis. All authors contributed to manuscript writing.

References

login to comment