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Variation in ground-dwelling arthropod communities across differently managed infiltration basins

Published online by Cambridge University Press:  08 May 2024

Shayan Farhang ,
Dan Duffy  and
Brett Seymoure Open the ORCID record for Brett Seymoure [Opens in a new window]
Shayan Farhang
Affiliation:
Washington University, St. Louis, MO, USA
Dan Duffy
Affiliation:
City of Ellisville Council, Ellisville, MO, USA
Brett Seymoure*
Affiliation:
Washington University, St. Louis, MO, USA University of Texas, El Paso, TX, USA
*
Corresponding author: Brett Seymoure; Email: [email protected]
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Abstract

As urbanisation continues to increase, terrestrial arthropod diversity declines. Urban green spaces represent unique opportunities to preserve arthropod diversity in urban environments. We quantify how ground-dwelling arthropod communities vary both seasonally and across three differently maintained stormwater infiltration basins in Ellisville, Missouri, United States of America. One basin was routinely mowed, a second was mowed only seasonally, and a third was intentionally planted to attract pollinators and was not mowed during this study. We expected higher plant diversity to correlate with higher arthropod diversity. Therefore, we expected the unmowed basin to have the highest levels of arthropod diversity and abundance and the mowed basin to have the lowest. Four collection periods spanned spring, early summer, late summer, and fall. During each collection period, five pitfall traps were placed throughout each basin for 48 hours. In total, 5686 specimens were collected and identified, representing 59 families. Arthropod communities did not vary across basins or collection dates, largely contrasting with existing literature. The results of this study do not indicate that different mowing regiments in infiltration basins will affect the ground-dwelling arthropod communities at a family level, although the effect on species-level diversity remains to be investigated.

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Research Paper
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The Canadian Entomologist , Volume 156 , 2024 , e13
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This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of Entomological Society of Canada

Introduction

Terrestrial arthropod populations and biodiversity are declining worldwide (van der Sluijs Reference van der Sluijs2020). The extent of this decline is uncertain, largely due to a lack of global arthropod abundance monitoring, especially when compared with other, better-studied taxa (Wagner et al. Reference Wagner, Grames, Forister, Berenbaum and Stopak2021). Arthropod decline reporting is also geographically restricted, with most studies coming from western and northern Europe (Wagner Reference Wagner2020) and North America (Wagner et al. Reference Wagner, Grames, Forister, Berenbaum and Stopak2021). The scarcity of arthropod population data in other areas, especially tropical regions, is largely due to limited funding, hyperdiversity, and incipient taxonomy (Wagner et al. Reference Wagner, Grames, Forister, Berenbaum and Stopak2021). As such, estimates of the proportion of arthropods at risk for extinction vary widely. The Intergovernmental Science–Policy Platform on Biodiversity and Ecosystem Services (Bonn, Germany) cautiously estimates that 10% of insect species are at risk for extinction (Purvis et al. Reference Purvis, Molnár, Obura, Ichii, Willis and Chettri2019), but other estimates place this number over 40% (Sánchez-Bayo and Wyckhuys Reference Sánchez-Bayo and Wyckhuys2019). Whatever the exact number is, terrestrial arthropod population collapse could spell disaster for the global ecosystem functions they make possible (van der Sluijs Reference van der Sluijs2020).

Terrestrial arthropods serve many vital roles within their environments. They act as pollinators and decomposers (Weisser and Siemann Reference Weisser and Siemann2008) and are important prey for many predatory animals (Denno et al. Reference Denno, Gratton, Peterson, Langellotto, Finke and Huberty2002). Insect herbivores break down organic matter within soil, aiding in decomposition, plant productivity, and nutrient cycling (Hartley and Jones Reference Hartley and Jones2008). Food web interactions through arthropod competition and predation are essential for ecosystem processes and have a range of positive, neutral, and negative outcomes on the plants and other components of the ecosystem (Sabelis et al. Reference Sabelis, Janssen, Bruin, Bakker, Drukker, Scutareanu and van Rijn1999; Janssen and Sabelis Reference Janssen and Sabelis2008). Predatory spiders provide biological control, suppressing pest species within an ecosystem (Michalko and Pekár Reference Michalko and Pekár2017). Certain soil arthropods, such as ants, termites, isopods, and millipedes, are considered ecosystem engineers: they alter their environment through bioturbation, reworking the soil by incorporating plant litter and other organic matter (Gonçalves et al. Reference Gonçalves, Carlos, Crespo, Zina, Oliveira and Salvação2021). Loss of arthropod populations could have far-reaching cascading effects, leading to biodiversity loss at higher trophic levels while also impairing ecosystem resilience and stability (van der Sluijs Reference van der Sluijs2020).

Many arthropods also are indicator species due to their niche partitioning and ease of monitoring (Hunter and Jaros-Su Reference Hunter and Jaros-Su1997). For example, some aquatic ecosystems rely on aquatic insect species as indicators for ecological integrity (Rosenberg and Resh Reference Rosenberg and Resh1993). In other cases, various arthropods have been used to monitor environmental pollution due to their sensitivity to environmental change (Parikh et al. Reference Parikh, Rawtani and Khatri2020). Soil arthropods can act as bioindicators for soil quality and can be used for more sustainable management of agroecosystems (Gonçalves et al. Reference Gonçalves, Carlos, Crespo, Zina, Oliveira and Salvação2021). Losing these indicators would mean loss of important research tools for ecosystem health monitoring.

Along with pollution, diseases and parasites, and climate change, the main driver of these global declines is habitat change caused by human activities, including agriculture, industrialisation, and urbanisation (Sánchez-Bayo and Wyckhuys Reference Sánchez-Bayo and Wyckhuys2019). Urbanisation has directly impacted terrestrial arthropod abundance and diversity by way of pollution, habitat loss and fragmentation, and land conversion (Shuisong et al. Reference Shuisong, Yan and Kai2013; Piano et al. Reference Piano, Giuliano and Isaia2020). Urban land cover since 2000 is projected to triple by 2030 (Seto et al. Reference Seto, Güneralp and Hutyra2012). As urbanisation increases, these arthropod communities are at risk of further declines, extirpation, and possible extinction (Shuisong et al. Reference Shuisong, Yan and Kai2013).

Although urbanisation has caused overall declines in biodiversity, urban green spaces have proven to be essential tools for maintaining high levels of biodiversity within urban areas (Mata et al. Reference Mata, Threlfall, Williams, Hahs, Malipatil, Stork and Livesley2017). Also referred to as “green infrastructure,” urban green spaces constitute any area of vegetation within an urban landscape. They include parks, community gardens, lawns, golf courses, cemeteries, green roofs, and sporting fields (Gairola and Noresah Reference Gairola and Noresah2010; Wolch et al. Reference Wolch, Byrne and Newell2014).

Green spaces can maintain diverse communities of insects and other arthropods, and these communities can differ significantly from those found in the surrounding nonurban areas (Burkman and Gardiner Reference Burkman and Gardiner2014). In one study in the Swiss Plateau (Switzerland), urban areas were shown to support species that otherwise either did not appear or were scarce within the study region, with 13.3% of species being recorded only in urban areas (Sattler et al. Reference Sattler, Obrist, Duelli and Moretti2011). Unique abiotic factors in urban areas contribute to these differences (Dale and Frank Reference Dale and Frank2018). For example, cities tend to be hotter than surrounding rural areas, due to the urban heat island effect (Yang et al. Reference Yang, Qian, Song and Zheng2016). Arthropods respond to this differently, depending on their latitude, with arthropods in higher-latitude areas generally increasing in abundance (Youngsteadt et al. Reference Youngsteadt, Ernst, Dunn and Frank2016). As climate change continues to alter global temperatures, some ant species have been reported to migrate to urban areas from lower altitudes because of their higher temperatures and drier climates (Menke et al. Reference Menke, Guénard, Sexton, Weiser, Dunn and Silverman2011). Generalist arthropods like some ants and spiders are often more resistant to the effects of urbanisation, further changing arthropod community composition in these areas (Thompson and McLachlan Reference Thompson and McLachlan2007; Lowe et al. Reference Lowe, Wilder and Hochuli2017). As such, urban green spaces not only represent opportunities to sustain arthropod communities comparable to those in surrounding areas but are often distinct ecosystems with their own unique arthropod communities and arthropod-driven ecosystem services.

Ground-dwelling arthropod communities have been shown to vary across differently maintained urban green spaces (Mata et al. Reference Mata, Threlfall, Williams, Hahs, Malipatil, Stork and Livesley2017). Increased mowing frequency generally corresponds with lower plant and arthropod diversity (Watson et al. Reference Watson, Carignan-Guillemette, Turcotte, Maire and Proulx2019; Proske et al. Reference Proske, Lokatis and Rolff2022). Conversely, reduced mowing frequency in urban green spaces has been shown to increase plant diversity (Chollet et al. Reference Chollet, Brabant, Tessier and Jung2018; Sehrt et al. Reference Sehrt, Bossdorf, Freitag and Bucharova2020). Green spaces with higher plant diversity and richness generally have more diverse arthropod communities (Haddad et al. Reference Haddad, Tilman, Haarstad, Ritchie and Knops2001).

Ground-dwelling arthropod community composition within a site also changes throughout the year. Arthropod seasonality differs between species even within the same site, as different species respond variably to changes in temperature, day length, and humidity (Wolda Reference Wolda1988). Many arthropod life cycles are largely temperature-driven, with the timing of different milestones such as oviposition, egg hatching, and emergence from pupation depending on outside temperature (Powell and Logan Reference Powell and Logan2005). This changing thermoperiod, combined with changing photoperiods as day length changes during the year, is a primary driver of terrestrial arthropod presence and activity (Beck Reference Beck1983). In one study concerning temporary pools within a temperate urban green space in Buenos Aires City, Argentina, seasonality was shown to be a primary driver of changing arthropod community structure (Fontanarrosa et al. Reference Fontanarrosa, Collantes and Bachmann2009).

In this study, we examined how higher plant diversity in three differently managed stormwater infiltration basins corresponds with ground-dwelling arthropod diversity. Infiltration basins are tools used to manage storm runoff by infiltration of water through the soil into the groundwater aquifer. They are distinct from retention basins, which permanently hold water, and detention basins, which manage runoff through discharge to a surface water body. The basins can be planted with various kinds of foliage to aid the infiltration of water through the soil, allowing for more effective removal of pollutants from the runoff (Pekarek et al. Reference Pekarek, Shelton, Feehan and Holm2011).

The three study sites were chosen based on their different maintenance regiments. We expected the basins with higher plant diversity and richness to contain higher levels of arthropod diversity. One basin, the “mowed basin,” had been planted with a small variety of short grasses and was routinely mowed: we expected it to have the lowest plant and ground-dwelling arthropod diversity. Another basin, the “reduced mowing basin,” was maintained seasonally, being mowed only once or twice per season. We expected its plant and ground-dwelling arthropod diversity to be higher than the mowed basin but lower than the third basin, the “unmowed basin,” which had been planted intentionally to attract pollinators and was not mowed during the study period.

Arthropods were collected from the three basins across four different collection periods: spring, early summer, late summer, and fall. We identified the collected arthropods to family level, as family-level diversity can be used as a proxy for species-level diversity, albeit with trade-offs between identification costs and more comprehensive data (Roy et al. Reference Roy, Jablonski and Valentine1996; Zou et al. Reference Zou, van der Werf, Liu and Axmacher2020). We expected arthropod community composition across all basins to vary seasonally due to climatic variation, as outlined by previous studies (Wolda Reference Wolda1988; Thomsen et al. Reference Thomsen, Jørgensen, Bruun, Pedersen, Riis-Nielsen and Jonko2015)

Methods

Study sites

Three infiltration basins in Ellisville, Missouri, United States of America were selected because of their differing maintenance regiments (Fig. 1). The mowed basin (38.585331, –90.585043) is approximately 250 m2 and had been planted with short grasses, mainly Festuca spp., that were routinely mowed. It was initially constructed as an inlet to keep water off of a nearby trail but was rebuilt as an infiltration basin in 2008. The reduced mowing basin (38.586388, –90.585844) was built in 2008 and is approximately 593 m². It usually was overgrown with tall grasses and weeds and underwent maintenance only seasonally. Plants present at this basin included Lonicera maackii (Ruprecht) (Caprifoliaceae) and Eupatorium Linnaeus (Asteraceae). The unmowed basin (38.601222, –90.592673) is approximately 75 m² and had been intentionally planted with plants that attract pollinators, including Sonchus asper (Linnaeus) (Asteraceae) and Asclepias incarnata Linnaeus (Apocynaceae). It was constructed in 2020 and was not mowed during this study. The mowed and reduced mowing basins are approximately 170 m apart, and the unmowed basin is located approximately 2.4 km from them.

Figure 1. Map showing location of basins (A, mowed basin; B, reduced mowing basin; and C, unmowed basin) in Ellisville, Missouri, with bottom-right inset showing location of Ellisville (red star) within the United States of America.

Collection methods

To compare ground-dwelling arthropod diversity across basins, pitfall traps were set at each basin for four 48-hour periods across 2021: 25–27 April (spring), 22–24 June (early summer), 1–3 September (late summer), and 30 October–1 November (fall). We restricted sampling to 48-hour periods that were forecasted to have no precipitation to ensure traps would not be flooded. Five pitfall traps were placed in an approximate “X” pattern at each basin, with one trap set at each point (the end of each arm) of the “X” and a fifth set at the centre. The traps were spread evenly across each basin, with each point of an “X” being approximately 1–2 m from that basin’s perimeter. Each trap consisted of one plastic cup (5.7 cm bottom diameter, 9.2 cm top diameter, 11.7 cm height) with a funnel secured in the top to allow arthropod entry but prevent escape. The bottom of each trap was filled with approximately 100 mL of 70% ethanol. The traps were installed flush to the ground and were intended to collect primarily ground-dwelling arthropods, such as beetles, spiders, ants, and crickets.

After 48 hours, the contents of each trap were emptied into Ziploc plastic bags and labelled accordingly. All specimens were then driven to the home lab setting, where they were identified to family level. Identification was completed using a Solomark Portable Stereo Microscope (https://www.solo-mark.com). Specimens were identified using the key in Marshall (Reference Marshall2006) and supplementary identification materials, including Bradley (Reference Bradley2012) and online resources such as iNaturalist (https://www.inaturalist.org) and BugGuide.net (https://bugguide.net/node/view/3/bgpage). Taxon concepts and taxonomic classification were derived from Marshall (Reference Marshall2006) and Bradley (Reference Bradley2012).

To determine differences between basins, plant diversity and richness for each basin were quantified. For each pitfall trap, all plants within a 1-m radius were identified. To properly quantify the plant diversity, both generic flora richness and abundance were assessed. Plants were identified to genus level by primarily using online resources such as iNaturalist.

Statistical methods

Data analysis was completed using R, version 4.1.2 (R Core Team 2021). We calculated Shannon diversity and total individual counts of arthropods at each basin and collection date using the vegan package, version 2.5.7 (Oksanen et al. Reference Oksanen, Blanchet, Friendly, Kindt, Legendre and McGlinn2020). Shannon diversity indices were also calculated for the plants at each basin. Number of families at each basin and collection date were calculated using the rich R package, version 1.0.1 (Rossi Reference Rossi2011). To test for differences in Shannon diversity and number of families, we ran two-way analyses of variance, with basin and date as independent variables. Shannon diversity and the number of families met the assumptions of parametric tests, whereas abundance had an extreme outlier, so we used Kruskal–Wallis tests for total counts for basin and collection date. To determine if community composition varied across basins and dates, permutational multivariate analyses of variance were completed using the vegan package, version 2.5.7 (Oksanen et al. Reference Oksanen, Blanchet, Friendly, Kindt, Legendre and McGlinn2020) and data were plotted with nonmetric multidimensional scaling plots using ggplot2, version 3.3.5 (Wickham Reference Wickham2016) and ggrepel, version 0.9.1 (Slowikowski Reference Slowikowski2021). Bray–Curtis dissimilarity distance was used for both the nonmetric multidimensional scaling plots and the permutational multivariate analyses of variance.

Results

In total, 5686 arthropod specimens were collected and identified across the three basins, representing 59 families (Supplementary material, Table S1). Although abundance of specimens did not differ significantly between basins (H (2) = 1.4231, P = 0.49) or collection date (H (3) = 6.0769, P = 0.11), 3365 specimens were collected at the mowed basin, whereas 1700 specimens were collected at the unmowed basin, and 621 specimens were collected at the reduced mowing basin (Fig. 2A). The collection period yielding the highest arthropod abundance was the late summer period, whereas the spring period yielded the lowest arthropod abundance (Fig. 2B). Of the 3365 specimens collected from the mowed basin, it should be noted that 2837 were collected during one collection date, 97% of which were ants. Removing this sampling does not change the diversity relationship between the basins or collection dates, nor does it significantly impact the arthropod community composition across basins or dates. However, with this date removed, the unmowed basin would be the site with the most abundant collection.

Figure 2. Arthropod abundance at each A, basin and B, collection date. There are no significant differences in abundance across basin types or collection dates.

The unmowed basin had the highest mean Shannon diversity index (1.612), whereas the mowed basin had the lowest mean Shannon diversity index (1; Fig. 3A), although no significant differences in Shannon diversity were observed between basins (F 2,6 = 0.83, P = 0.48) or collection dates (F 3,6 = 0.42, P = 0.745; Fig. 3B). In addition, no difference in the number of arthropod families was found between each basin (F 2,6 = 0.50, P = 0.632; Fig. 3C) or collection date (F 3,6 = 2.67, P = 0.142; Fig. 3D). Furthermore, the permutational multivariate analyses of variance revealed no significant differences in arthropod community assemblage for basin (F 2,11 = 0.81, P = 0.61; Fig. 4A) or collection date (F 2,11 = 1.35, P = 0.23; Fig. 4B).

Figure 3. Shannon diversity index for each A, basin and B, collection date; number of families at each C, basin and D, collection date. There are no significant differences in diversity or number of families across basin types or collection dates.

Figure 4. A, Nonmetric multidimensional scaling plot generated for arthropod communities across basins, showing significant overlap between communities; B, nonmetric multidimensional scaling plot generated for arthropod communities across collection dates, showing minimal overlap between fall and spring collection dates, with significant overlap between both summer collection dates. Abbreviations: anth, Anthocoridae; aphi, Aphididae; aran, Araneidae; arma, Armadillidiidae; beth, Bethylidae; brac, Braconidae; bupr, Buprestidae; call, Calliphoridae; cara, Carabidae; ceci, Cecidomyiidae; chei, Cheiracanthiidae; chir, Chironomidae; chlo, Chloropidae; chry, Chrysomelidae; cica, Cicadellidae; curc, Curculionidae; cydn, Cydnidae; delp, Delphacidae; diap, Diapriidae; dros, Drosophilidae; dysd, Dysderidae, elat, Elateridae; ento, Entomobryomorpha; fann, Fanniidae; form, Formicidae; gryl, Gryllidae; hesp, Hesperiidae; latr, Latridiidae; lino, Linotaeniidae; liny, Linyphiidae; luca, Lucanidae; lyco, Lycosidae; lyga, Lygaeidae; miri, Miridae; myce, Mycetophilidae; myma, Mymaridae; nabi, Nabidae; niti, Nitidulidae; orib, Oribatida; pano, Panorpidae; phor, Phoridae; plat, Platygastridae; podu, Poduromorpha; porc, Porcellionidae; pter, Pteromalidae; pyra, Pyralidae; scar, Scarabaeidae; scio, Sciomyzidae; scut, Scutigeridae; spha, Sphaeroceridae; stap, Staphylinidae; sylv, Silvanidae; symp, Symphypleona; tach, Tachinidae; ther, Theridiidae; thri, Thripidae; trac, Trachelidae; tric, Trichoceridae; vesp, Vespidae.

Plant genera richness was highest at the reduced mowing basin and lowest at the mowed basin. The mowed basin had the lowest diversity index (approximately 0.78). Flora at this basin was primarily spread across three grass genera, Festuca Tournefort (Poaceae), Digitaria Haller (Poaceae), and Sorghum Moench (Poaceae). The reduced mowing and unmowed basins’ Shannon diversity indices were more than double that of the mowed basin, with values of 1.91 and 1.94, respectively.

Discussion

This study did not find variation in arthropod diversity at the family level across basin types. This observation contrasts with existing literature, as the unmowed and reduced mowing basins both had higher plant diversity and generic richness than the mowed basin did, and those characteristics were expected to lead to significantly higher arthropod diversity in these two basins (Haddad et al. Reference Haddad, Crutsinger, Gross, Haarstad, Knops and Tilman2009).

Certain families accounted for a large proportion of all arthropods collected and appeared in all three basins. These included Lycosidae, Formicidae, Carabidae, and Gryllidae. Some of these families, such as Lycosidae, have relatively high proportions of generalist species (Bedford and Usher Reference Bedford and Usher1994; Major et al. Reference Major, Gowing, Christie, Gray and Colgan2006). Generalist species are often more resistant to disturbance (Niemelä and Kotze Reference Niemelä and Kotze2009; Lowe et al. Reference Lowe, Wilder and Hochuli2017), which may partially explain why some of these families appeared at all three sites, leading to a lack of variation. Families that appeared only in one basin, such as Curculionidae (mowed basin), Scarabaeidae and Trachelidae (reduced mowing basin), and Lucanidae (unmowed basin), were collected infrequently and subsequently accounted for a small proportion of all arthropods collected. Identification of arthropods to species level could reveal more significant differences between the communities, showing more clearly how adaptive radiation within families could lead to specialisation. Higher-taxon surrogacy was used due to time and resource constraints, but correlations with species composition at a local scale have been shown to decrease at the family level as compared to the genus level (Mandelik et al. Reference Mandelik, Dayan, Chikatunov and Kravchenko2007).

Although no significant differences were observed in the arthropod communities across collection dates, possibly due to lack of replication and small sample size, there are indications that these data follow similar phenological patterns to those shown in other similar studies. The early and late summer dates contained the highest overlap, whereas the arthropod communities collected in the spring and fall overlapped less with each other and with either of the summer dates. Arthropod communities have been found to experience significant turnover throughout the year (Thomsen et al. Reference Thomsen, Jørgensen, Bruun, Pedersen, Riis-Nielsen and Jonko2015; Seifert et al. Reference Seifert, Jorge, Volf, Wagner, Lamarre and Miller2021): it therefore makes sense that the more temporally distant collection dates yielded less overlap than the temporally closer ones did. This annual turnover can partially be attributed to bottom-up processes driven by temporal (Ekholm et al. Reference Ekholm, Tack, Pulkkinen and Roslin2019; Shinohara and Yoshida Reference Shinohara and Yoshida2021) and spatial (Sobek et al. Reference Sobek, Steffan-Dewenter, Scherber and Tscharntke2009) turnover of plant species. In one study, Auchenorrhyncha species abundance changed significantly across the year and related directly to the number of grass structures present at the site, which peaked in late summer (Stinson and Brown Reference Stinson and Brown1983). Those results align with the current study’s most abundant collection period, the late summer period, although it was not more significantly abundant than the other collection dates. Analysis of seasonal variation in plant diversity, richness, spatiality, and architecture would help to determine the factors underlying these seasonal changes in arthropod community composition.

Due to time, resource, and spatial constraints, the replication level and sample size of this study were limited and may have contributed to the lack of variation. A larger sample size could be accomplished by placing more traps and by incorporating multiple types of traps. Increasing trap abundance and diversity would also allow for a greater variety of arthropods to be sampled. The highly species-specific nature of arthropod response to changing vegetation could mean that the inclusion of more flying arthropods, in addition to ground-dwelling arthropods, in studies may reveal more noticeable differences between the communities. The addition of traps specialising in capturing flying insects, such as malaise traps, yellow pan traps, and light traps, could accomplish this (Devigne and de Biseau Reference Devigne and de Biseau2014).

The location and size of the basins also may have contributed to the homogeneity of the collected arthropod community because the infiltration basins selected were all located relatively close to each other, especially the mowed and reduced mowing basins. The unmowed basin was significantly smaller and newer than the other basins, which may have contributed to its lower plant richness and abundance. Due to the even placement of traps across each study site, the traps in the unmowed basin were placed more closely together than those in the mowed or reduced mowing basins were, and this may have contributed to the variation in the collected arthropod abundance between sites. Because many traps were placed close to the basins’ edges, edge effects may have also skewed the results. Arthropod community composition can change significantly at habitat edges through species-specific responses that depend on resource requirements (Wimp and Murphy Reference Wimp and Murphy2021). Because all of the basins were relatively small, their edge densities were relatively large, with a significant portion of each basin’s total area being taken up by edge habitat. Edge density can negatively affect overall arthropod diversity while favouring generalist species (Peng et al. Reference Peng, Hung, Liu and Neoh2020). This relationship may have contributed to the overall homogeneity between the basins. A future study producing results with higher statistical power could aid city councils and urban planners in building infiltration basins, as well as urban green spaces in general, that are more conducive to ground-dwelling arthropod diversity. It is essential that urban planning considers arthropod diversity to mitigate the detrimental effects of urbanisation on overall biodiversity.

Supplementary material

To view supplementary material for this article, please visit https://doi.org/10.4039/tce.2024.8.

Acknowledgements

The authors thank Dr. Jonathan Losos and the Department of Biology at Washington University at St. Louis for supporting and mentoring S.F. during their undergraduate thesis. The authors are also grateful for the support of the Living Earth Collaborative and Ellisville City Council: the Living Earth Collaborative funded the work, and Ellisville City Council enabled access to the infiltration basins.

Competing interests

The authors declare that they have no competing interests.

Footnotes

Subject editor: Joel Kits

References

Beck, S.D. 1983. Insect thermoperiodism. Annual Review of Entomology, 28: 91–108. https://doi.org/10.1146/annurev.en.28.010183.000515.CrossRefGoogle Scholar
Bedford, S.E. and Usher, M.B. 1994. Distribution of arthropod species across the margins of farm woodlands. Agriculture, Ecosystems & Environment, 48: 295–305. https://doi.org/10.1016/0167-8809(94)90111-2.CrossRefGoogle Scholar
Bradley, R.A. 2012. Common spiders of North America. University of California Press, Berkeley, California, United States of America.Google Scholar
Burkman, C.E. and Gardiner, M.M. 2014. Urban greenspace composition and landscape context influence natural enemy community composition and function. Biological Control, 75: 58–67. https://doi.org/10.1016/j.biocontrol.2014.02.015.CrossRefGoogle Scholar
Chollet, S., Brabant, C., Tessier, S., and Jung, V. 2018. From urban lawns to urban meadows: reduction of mowing frequency increases plant taxonomic, functional and phylogenetic diversity. Landscape and Urban Planning, 180: 121–124. https://doi.org/10.1016/j.landurbplan.2018.08.009.CrossRefGoogle Scholar
Dale, A.G. and Frank, S.D. 2018. Urban plants and climate drive unique arthropod interactions with unpredictable consequences. Current Opinion in Insect Science, 29: 27–33. https://doi.org/10.1016/j.cois.2018.06.001.CrossRefGoogle ScholarPubMed
Denno, R.F., Gratton, C., Peterson, M.A., Langellotto, G.A., Finke, D.L., and Huberty, A.F. 2002. Bottom–up forces mediate natural-enemy impact in a phytophagous insect community. Ecology, 83: 1443–1458. https://doi.org/10.2307/3071956.CrossRefGoogle Scholar
Devigne, C. and de Biseau, J.-C. 2014. Urban ecology: comparison of the effectiveness of five traps commonly used to study the biodiversity of flying insects. Biodiversity Journal, 5: 165–174.Google Scholar
Ekholm, A., Tack, A.J.M., Pulkkinen, P., and Roslin, T. 2019. Host plant phenology, insect outbreaks and herbivore communities: the importance of timing. Journal of Animal Ecology, 89: 829–841. https://doi.org/10.1111/1365-2656.13151.CrossRefGoogle ScholarPubMed
Fontanarrosa, M.S., Collantes, M.B., and Bachmann, A.O. 2009. Seasonal patterns of the insect community structure in urban rain pools of temperate Argentina. Journal of Insect Science, 9: 1–17. https://doi.org/10.1673/031.009.1001.CrossRefGoogle ScholarPubMed
Gairola, S. and Noresah, M.S. 2010. Emerging trend of urban green space research and implications for safe guarding biodiversity: a viewpoint. Nature and Science of Sleep, 8: 43–49.Google Scholar
Gonçalves, F., Carlos, C., Crespo, L., Zina, V., Oliveira, A., Salvação, J., et al. 2021. Soil arthropods in the Douro demarcated region vineyards: general characteristics and ecosystem services provided. Sustainability, 13: 7837. https://doi.org/10.3390/su13147837.CrossRefGoogle Scholar
Haddad, N.M., Crutsinger, G.M., Gross, K., Haarstad, J., Knops, J.M.H., and Tilman, D. 2009. Plant species loss decreases arthropod diversity and shifts trophic structure. Ecology Letters, 12: 1029–1039. https://doi.org/10.1111/j.1461-0248.2009.01356.x.CrossRefGoogle ScholarPubMed
Haddad, N.M., Tilman, D., Haarstad, J., Ritchie, M., and Knops, J.M.H. 2001. Contrasting effects of plant richness and composition on insect communities: a field experiment. The American Naturalist, 158: 17–35.Google Scholar
Hartley, S.E. and Jones, T.H. 2008. Insect herbivores, nutrient cycling and plant productivity. In Insects and ecosystem function. Edited by W.W. Weisser and E. Siemann. Springer, Berlin/Heidelberg, Germany. Pp. 27–52.Google Scholar
Hunter, M.L. and Jaros-Su, J.C. 1997. Insects, entomologists, and the conservation of biodiversity. Northeastern Naturalist, 4: 153–158. https://doi.org/10.2307/3858710.CrossRefGoogle Scholar
Janssen, A. and Sabelis, M.W. 2008. Food web interactions and ecosystem processes. In Insects and ecosystem function. Edited by W.W. Weisser and E. Siemann. Springer, Berlin/Heidelberg, Germany. Pp. 175–191CrossRefGoogle Scholar
Lowe, E.C., Wilder, S.M., and Hochuli, D.F. 2017. Life history of an urban-tolerant spider shows resilience to anthropogenic habitat disturbance. Journal of Urban Ecology, 3: jux004. https://doi.org/10.1093/jue/jux004.CrossRefGoogle Scholar
Major, R.E., Gowing, G., Christie, F.J., Gray, M., and Colgan, D. 2006. Variation in wolf spider (Araneae: Lycosidae) distribution and abundance in response to the size and shape of woodland fragments. Biological Conservation, 132: 98–108. https://doi.org/10.1016/j.biocon.2006.03.017.CrossRefGoogle Scholar
Mandelik, Y., Dayan, T., Chikatunov, V., and Kravchenko, V. 2007. Reliability of a higher-taxon approach to richness, rarity, and composition assessments at the local scale. Conservation Biology, 21: 1506–1515. https://doi.org/10.1111/j.1523-1739.2007.00823.x.CrossRefGoogle ScholarPubMed
Marshall, S.A. 2006. Insects: their natural history and diversity, with a photographic guide to insects of eastern North America. Firefly Books, Richmond Hill, Ontario, Canada.Google Scholar
Mata, L., Threlfall, C.G., Williams, N.S., Hahs, A.K., Malipatil, M., Stork, N.E., and Livesley, S.J. 2017. Conserving herbivorous and predatory insects in urban green spaces. Scientific Reports, 7: 40970. https://doi.org/10.1038/srep40970.CrossRefGoogle ScholarPubMed
Menke, S.B., Guénard, B., Sexton, J.O., Weiser, M.D., Dunn, R.R., and Silverman, J. 2011. Urban areas may serve as habitat and corridors for dry-adapted, heat tolerant species: an example from ants. Urban Ecosystems, 14: 135–163. https://doi.org/10.1007/s11252-010-0150-7.CrossRefGoogle Scholar
Michalko, R. and Pekár, S. 2017. The behavioral type of a top predator drives the short-term dynamic of intraguild predation. The American Naturalist, 189: 690501. https://doi.org/10.1086/690501.CrossRefGoogle ScholarPubMed
Niemelä, J. and Kotze, D.J. 2009. Carabid beetle assemblages along urban to rural gradients: a review. Landscape and Urban Planning, 92: 65–71. https://doi.org/10.1016/j.landurbplan.2009.05.016.CrossRefGoogle Scholar
Oksanen, J., Blanchet, F.G., Friendly, M., Kindt, R., Legendre, P., McGlinn, D., et al. 2020. vegan: community ecology package. R package, version 2.5-6.Google Scholar
Parikh, G., Rawtani, D., and Khatri, N. 2020. Insects as an indicator for environmental pollution. Environmental Claims Journal, 33: 161–181. https://doi.org/10.1080/10406026.2020.1780698.CrossRefGoogle Scholar
Pekarek, K.A., Shelton, D.P., Feehan, K., and Holm, B.A. 2011. Stormwater Management: Terminology. Papers in Natural Resources. University of Nebraska Extension Circular EC701. University of Nebraska–Lincoln Extension, Lincoln, Nebraska, United States of America.Google Scholar
Peng, M.H., Hung, Y.C., Liu, K.L., and Neoh, K.B. 2020. Landscape configuration and habitat complexity shape arthropod assemblage in urban parks. Scientific Reports, 10: 16043. https://doi.org/10.1038/s41598-020-73121-0.CrossRefGoogle ScholarPubMed
Piano, E., Giuliano, D., and Isaia, M. 2020. Islands in cities: urbanization and fragmentation drive taxonomic and functional variation in ground arthropods. Basic and Applied Ecology, 43: 86–98. https://doi.org/10.1016/j.baae.2020.02.001.CrossRefGoogle Scholar
Powell, J.A. and Logan, J.A. 2005. Insect seasonality: circle map analysis of temperature-driven life cycles. Theoretical Population Biology, 67: 161–179. https://doi.org/10.1016/j.tpb.2004.10.001.CrossRefGoogle ScholarPubMed
Proske, A., Lokatis, S., and Rolff, J. 2022. Impact of mowing frequency on arthropod abundance and diversity in urban habitats: a meta-analysis. Urban Forestry & Urban Greening, 76: 127714. https://doi.org/10.1016/j.ufug.2022.127714.CrossRefGoogle Scholar
Purvis, A., Molnár, Z., Obura, D., Ichii, K., Willis, K., Chettri, N., et al. 2019. Status and trends – nature. In Global assessment report on biodiversity and ecosystem services. Edited by E.S. Brondízio, J. Settele, S. Díaz, and H.T. Ngo. Intergovernmental Science–Policy Platform on Biodiversity and Ecosystem Services (IBPES) Secretariat, Bonn, Germany. Pp. 206–308.Google Scholar
R Core Team. 2021. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Available from https://www.R-project.org/ [accessed 28 August 2023].Google Scholar
Rosenberg, D.M. and Resh, V.H. 1993. Freshwater biomonitoring and benthic macroinvertebrates. Kluwer Academic Publishers, Dordrecht, The Netherlands.Google Scholar
Rossi, J.-P. 2011. rich: an R package to analyse species richness. Diversity, 3: 112–120. https://doi.org/10.3390/d3010112.CrossRefGoogle Scholar
Roy, K., Jablonski, D., and Valentine, J.W. 1996. Higher taxa in biodiversity studies: patterns from eastern Pacific marine molluscs. Philosophical Transactions of the Royal Society B: Biological Sciences, 351: 1605–1613. https://doi.org/10.1098/rstb.1996.0144.Google Scholar
Sabelis, M.W., Janssen, A., Bruin, J., Bakker, F., Drukker, B., Scutareanu, P., and van Rijn, P.C.J. 1999. Interactions between arthropod predators and plants: a conspiracy against herbivorous arthropods? In Ecology and evolution of the Acari. Edited by J. Bruin, L.P.S. van der Geest, and M.W. Sabelis. Springer, Dordrecht, Germany. Pp. 207–229.Google Scholar
Sánchez-Bayo, F. and Wyckhuys, K.A.G. 2019. Worldwide decline of the entomofauna: a review of its drivers. Biological Conservation, 232: 8–27. https://doi.org/10.1016/j.biocon.2019.01.020.CrossRefGoogle Scholar
Sattler, T., Obrist, M.K., Duelli, P., and Moretti, M. 2011. Urban arthropod communities: added value or just a blend of surrounding biodiversity? Landscape and Urban Planning, 103: 347–361. https://doi.org/10.1016/j.landurbplan.2011.08.008.CrossRefGoogle Scholar
Sehrt, M., Bossdorf, O., Freitag, M., and Bucharova, A. 2020. Less is more! Rapid increase in plant species richness after reduced mowing in urban grasslands. Basic and Applied Ecology, 42: 47–53. https://doi.org/10.1016/j.baae.2019.10.008.CrossRefGoogle Scholar
Seifert, C.L., Jorge, L.R., Volf, M., Wagner, D.L., Lamarre, G.P.A., Miller, S.E., et al. 2021. Seasonality affects specialisation of a temperate forest herbivore community. Oikos, 130: 1450–1461. https://doi.org/10.1111/oik.08265.CrossRefGoogle Scholar
Seto, K.C., Güneralp, B., and Hutyra, L.R. 2012. Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools. Proceedings of the National Academy of Sciences, 109: 16083–16088. https://doi.org/10.1073/pnas.1211658109.CrossRefGoogle ScholarPubMed
Shinohara, N. and Yoshida, T. 2021. Temporal changes of local and regional processes in the assembly of herbivorous insect communities. Oikos, 130: 1626–1635. https://doi.org/10.1111/oik.08350.CrossRefGoogle Scholar
Shuisong, Y., Yan, F., and Kai, L. 2013. Impacts of urbanization process on insect diversity. Biodiversity Science, 21: 260–268.CrossRefGoogle Scholar
Slowikowski, K. 2021. ggrepel: automatically position non-overlapping text labels with ‘ggplot2’. R package, version 0.9.1. Available from https://CRAN.R-project.org/package=ggrepel [accessed 28 August, 2023].Google Scholar
Sobek, S., Steffan-Dewenter, I., Scherber, C., and Tscharntke, T. 2009. Spatiotemporal changes of beetle communities across a tree diversity gradient. Diversity and Distributions, 15: 660–670. https://doi.org/10.1111/j.1472-4642.2009.00570.x.CrossRefGoogle Scholar
Stinson, C.S. and Brown, V.K. 1983. Seasonal changes in the architecture of natural plant communities and its relevance to insect herbivores. Oecologia, 56: 67–69. https://doi.org/10.1007/BF00378218.CrossRefGoogle ScholarPubMed
Thompson, B. and McLachlan, S. 2007. The effects of urbanization on ant communities and myrmecochory in Manitoba, Canada. Urban Ecosystems, 10: 43–52. https://doi.org/10.1007/s11252-006-0013-4.CrossRefGoogle Scholar
Thomsen, P.F., Jørgensen, P.S., Bruun, H.H., Pedersen, J., Riis-Nielsen, T., Jonko, K., et al. 2015. Resource specialists lead local insect community turnover associated with temperature: analysis of an 18-year full-seasonal record of moths and beetles. Journal of Animal Ecology, 85: 251–261. https://doi.org/10.1111/1365-2656.12452.CrossRefGoogle ScholarPubMed
van der Sluijs, J.P. 2020. Insect decline, an emerging global environmental risk. Current Opinion in Environmental Sustainability, 46: 39–42. https://doi.org/10.1016/j.cosust.2020.08.012.CrossRefGoogle Scholar
Wagner, D.L. 2020. Insect declines in the Anthropocene. Annual Review of Entomology, 65: 457–480. https://doi.org/10.1146/annurev-ento-011019-025151.CrossRefGoogle ScholarPubMed
Wagner, D.L., Grames, E.M., Forister, M.L., Berenbaum, M.R., and Stopak, D. 2021. Insect decline in the Anthropocene: death by a thousand cuts. Proceedings of the National Academy of Sciences, 118: e2023989118. https://doi.org/10.1073/pnas.2023989118.CrossRefGoogle ScholarPubMed
Watson, C.J., Carignan-Guillemette, L., Turcotte, C., Maire, V., and Proulx, R. 2019. Ecological and economic benefits of low-intensity urban lawn management. Journal of Applied Ecology, 57: 436–446. https://doi.org/10.1111/1365-2664.13542.CrossRefGoogle Scholar
Weisser, W.W. and Siemann, E. 2008. Insects and ecosystem function. Springer, Berlin/Heidelberg, Germany.CrossRefGoogle Scholar
Wickham, H. 2016. ggplot2: elegant graphics for data analysis. Second edition. Springer, Cham, Switzerland.CrossRefGoogle Scholar
Wimp, G.M. and Murphy, S.M. 2021. Habitat edges alter arthropod community composition. Landscape Ecology, 36: 2849–2861. https://doi.org/10.1007/s10980-021-01288-6.CrossRefGoogle Scholar
Wolch, J.R., Byrne, J., and Newell, J.P. 2014. Urban green space, public health, and environmental justice: the challenge of making cities ‘just green enough’. Landscape and Urban Planning, 125: 234–244. https://doi.org/10.1016/j.landurbplan.2014.01.017.CrossRefGoogle Scholar
Wolda, H. 1988. Insect seasonality: why? Annual Review of Ecology and Systematics, 19: 1–18. https://doi.org/10.1146/annurev.es.19.110188.000245.CrossRefGoogle Scholar
Yang, L., Qian, F., Song, D., and Zheng, K. 2016. Research on urban heat-island effect. Procedia Engineering, 169: 11–18. https://doi.org/10.1016/j.proeng.2016.10.002.CrossRefGoogle Scholar
Youngsteadt, E., Ernst, A.F., Dunn, R.R., and Frank, S.D. 2016. Responses of arthropod populations to warming depend on latitude: evidence from urban heat islands. Global Change Biology, 23: 1436–1447. https://doi.org/10.1111/gcb.13550.CrossRefGoogle ScholarPubMed
Zou, Y., van der Werf, W., Liu, Y., and Axmacher, J.C. 2020. Predictability of species diversity by family diversity across global terrestrial animal taxa. Global Ecology and Biogeography, 29: 629–644. https://doi.org/10.1111/geb.13043.CrossRefGoogle Scholar
Figure 0

Figure 1. Map showing location of basins (A, mowed basin; B, reduced mowing basin; and C, unmowed basin) in Ellisville, Missouri, with bottom-right inset showing location of Ellisville (red star) within the United States of America.

Figure 1

Figure 2. Arthropod abundance at each A, basin and B, collection date. There are no significant differences in abundance across basin types or collection dates.

Figure 2

Figure 3. Shannon diversity index for each A, basin and B, collection date; number of families at each C, basin and D, collection date. There are no significant differences in diversity or number of families across basin types or collection dates.

Figure 3

Figure 4. A, Nonmetric multidimensional scaling plot generated for arthropod communities across basins, showing significant overlap between communities; B, nonmetric multidimensional scaling plot generated for arthropod communities across collection dates, showing minimal overlap between fall and spring collection dates, with significant overlap between both summer collection dates. Abbreviations: anth, Anthocoridae; aphi, Aphididae; aran, Araneidae; arma, Armadillidiidae; beth, Bethylidae; brac, Braconidae; bupr, Buprestidae; call, Calliphoridae; cara, Carabidae; ceci, Cecidomyiidae; chei, Cheiracanthiidae; chir, Chironomidae; chlo, Chloropidae; chry, Chrysomelidae; cica, Cicadellidae; curc, Curculionidae; cydn, Cydnidae; delp, Delphacidae; diap, Diapriidae; dros, Drosophilidae; dysd, Dysderidae, elat, Elateridae; ento, Entomobryomorpha; fann, Fanniidae; form, Formicidae; gryl, Gryllidae; hesp, Hesperiidae; latr, Latridiidae; lino, Linotaeniidae; liny, Linyphiidae; luca, Lucanidae; lyco, Lycosidae; lyga, Lygaeidae; miri, Miridae; myce, Mycetophilidae; myma, Mymaridae; nabi, Nabidae; niti, Nitidulidae; orib, Oribatida; pano, Panorpidae; phor, Phoridae; plat, Platygastridae; podu, Poduromorpha; porc, Porcellionidae; pter, Pteromalidae; pyra, Pyralidae; scar, Scarabaeidae; scio, Sciomyzidae; scut, Scutigeridae; spha, Sphaeroceridae; stap, Staphylinidae; sylv, Silvanidae; symp, Symphypleona; tach, Tachinidae; ther, Theridiidae; thri, Thripidae; trac, Trachelidae; tric, Trichoceridae; vesp, Vespidae.

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