Fragment edges benefit a common predator of pollinators via bottom-up effects

Fragment edges benefit a common predator of pollinators via bottom-up effects | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 4 September 2025 V1 Latest version Share on Fragment edges benefit a common predator of pollinators via bottom-up effects Authors : Wenlong Zhou 0009-0008-8102-0076 , Peng Ren 0000-0001-6033-6188 , Marcel Holyoak 0000-0001-9727-3627 , Donghao Wu 0000-0003-3568-0782 , Chen Zhu , Wenjie Zhou , Ping Ding , and Mingjian Yu 0000-0001-8060-8427 [email protected] Authors Info & Affiliations https://doi.org/10.22541/au.175697695.53818338/v1 223 views 162 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Defaunation following habitat fragmentation typically threatens predators at higher trophic levels, which may further alter prey and plants via top-down effects. However, there are few studies that have tested if fragmented habitats (e.g. forest edges) support higher trophic levels through bottom-up effects. Herein we tested the effects of habitat fragmentation on multi-trophic interactions involving flowering plants, pollinators, and a common predatory spider, Atypus heterothecus (Atypidae). We conducted the study on 19 islands in the Thousand Island Lake (TIL), eastern China, including four large islands (> 9 ha) and 15 small islands (< 3 ha) over a 2-year period. Spider population biomass was higher at edges than the interior of large islands. Unexpectedly, island area and isolation had no significant effects on spider biomass. High-throughput-sequencing showed that pollinators made up over 50% of prey resources of the spider. Furthermore, prey composition significantly differed between edges and interiors, with edges having higher prey richness, and richness and abundance of flowering plants and pollinators. Piecewise structural equation models showed that edges had higher spider biomass due to bottom-up effects, and that top-down effects were also substantial though clearly not strong enough to suppress prey biomass. In contrast to most studies, our study shows that edge effects induced by habitat fragmentation produced strong positive bottom-up effects and benefitted spider predators, thereby relieving the negative effects of habitat fragmentation on higher trophic levels and cross-trophic interactions. Introduction As one of the primary drivers of biodiversity loss worldwide (Fahrig 2003, Chase et al. 2020), habitat fragmentation threatens species diversity through decreasing habitat area, increasing isolation between habitats, and creating edge habitats (Haddad et al. 2015, Betts et al. 2019). Higher trophic levels, e.g. predators, are especially prone to local extinction in fragment habitats due to diet specialization and low population density (Estes et al. 2011, Gibson et al. 2013). Specifically, predators in small and isolated habitats have higher rates of mortality and lower rates of re-colonization than large and continuous habitats (Crooks et al. 2017, Kuipers et al. 2021, Wang et al. 2024), namely the equilibrium theory of island biogeography (Brown and Kodric-Brown 1977, Laurance 2008, Yu et al. 2012). However, edge habitats may increase environmental heterogeneity during habitat fragmentation with different species responding contrastingly to edge habitats (Fahrig 2017, Fletcher Jr et al. 2018), and not entirely preforming negative responses to edge habitats (Pfeifer et al. 2017, Moreno and Teixido 2025). The effects of habitat fragmentation on specific trophic guild can pass on to other trophic levels. For instance, predators are often more sensitive to habitat fragmentation than their prey, and consequently fragmentation may release intermediate trophic levels from predator control and strengthen interactions between producers and primary consumers via top-down effects (Terborgh et al. 2001, Genua et al. 2017). Experiments in an old field system found that predator densities declined in small fragments whereas herbivorous prey densities increased and generated unequal impacts on two plant species through top-down effects, depending on the herbivore’s feeding preference (Genua et al. 2017). Species at lower trophic levels may also affect higher trophic levels by bottom-up effects (Haddad et al. 2009, Morante-Filho et al. 2016). In a fragmented central European landscape, increasing numbers of prey augmented the abundance of predators at habitat edges (Šálek et al. 2010). The relative importance of top-down vs. bottom-up effects depends on habitat fragment size, according to a study of tree seeds, rodents and their predators (Wang et al. 2020). Despite these findings, few studies have investigated how habitat fragmentation affects bottom trophic levels (i.e. plants), intermediate levels (e.g. herbivorous prey or pollinators), and top levels (e.g. predators) simultaneously through bottom-up or top-down effects (Anderson et al. 2019, Palmeirim et al. 2024). Moreover, the influence of edge habitats on multi-trophic interactions remains underexplored (Wimp et al. 2011), and this gap persists to the present. Spiders are important top predators of insects in terrestrial ecosystems (Nyffeler and Birkhofer 2017). Spiders can produce trophic control involving insects and plants, which occur through a mix of density- and trait-mediated (non-consumptive) effects (Schmitz 2008, Laws and Joern 2015). For instance, spider presence directly changed the flower-visiting behavior of pollinators and indirectly decreased the individual seed set and fruit biomass of plants (Gonçalves-Souza et al. 2008). The decrease of spider biomass also increased the abundance and richness of insects (Genua et al. 2017). Nevertheless, changes in producer groups can indirectly influence spider density and foraging behavior through their effects on prey diversity and composition (Hu et al. 2024). Another study involving plants, pollinators, and a predatory crab spider species also found that floral abundance strongly increased the crab spider abundance through enhancing pollinator visitation and prey (i.e. pollinator) availability (Hulting et al. 2024). Although forest edges have been shown to mitigate the negative effects of fragmentation on plant–pollinator interactions (Ren et al. 2023), our understanding of how trophic control shape multi-trophic interactions across fragments remains limited. Here we extend these studies to test how habitat fragmentation changes multi-trophic interactions involving flowering plants, pollinators, and the common species Atypus heterothecus ( Atypidae), a large-bodied species with limited dispersal capacity (Wu et al. 2017). We tested three hypotheses (Fig. 1): H1 Biomass of spiders will decrease with decreasing island area and increasing island isolation. H2 Considering the complex effects of edge heterogeneity, edge habitats will change (either increase or decrease) spider biomass compared with interior habitats. H3 Habitat-fragmentation-induced changes in spider biomass will change top-down and bottom-up effects on the richness and abundance of flowering plants and pollinators. To elucidate the mechanisms by which habitat fragmentation alters the multi-trophic interactions (‘plant-pollinator-spider’), we evaluated the fit of two different piecewise SEM models representing a pure bottom-up effect, that flowering plants affect spiders via affecting pollinators (Fig. S1a), or a pure top-down effect, that spiders affect flowering plants via affecting pollinators (Fig. S1b). We determined the prey composition of A. heterothecus via gut high-throughput sequencing, and we incorporated the prey composition of A. heterothecus into the piecewise SEM models. Materials and Methods Study area The study was carried out in the Thousand Island Lake (TIL) in Zhejiang Province, eastern China (29°22′–29°50′ N, 118°34′–119°15′ E) (Fig. 2a). The lake is a large artificial land-bridge island system (Hu et al. 2011, Yu et al. 2012). It was created in 1959 through the construction of Xin’an River Dam for hydroelectric production, forming a water area of approximately 540 km 2 (at the high-water level of 108 m) and 1078 islands (previously hilltops of continuous forest) with areas ranging from 0.25 to 1154 ha (Fig. 2b) (Hu et al. 2012, Wilson et al. 2016). The forests in TIL were clear-cut before the construction of the dam, and subsequently have undergone secondary succession without deliberate anthropogenic reforestation, and with legally protection from further human disturbance after 1980s (Wilson et al. 2016, Wang et al. 2024). Currently, about 90% of island area is covered by an unmanaged secondary forest dominated by a Masson pine, Pinus massoniana, in the canopy level and broad-leaved tree and shrub species in the subcanopy and understory (Liu et al. 2022, Wang et al. 2024). Understory shrubs and herbs are sparse in the island interior and dominated by Loropetalum chinense and Vaccinium carlesii , whereas understory shrubs and herbs are denser and more diverse in the island edge (Ren et al. 2023, Zheng et al. 2024). TIL has a typical subtropical monsoon zone climate and is highly seasonal, with an average annual temperature of 17.0℃, ranging from -7.6℃ in January to 41.8℃ in July (Hu et al. 2011, Aiying Zhang et al. 2023). The average annual precipitation is 1430 mm and mainly concentrated in the rainy season between April and June (Liu et al. 2018, Ren et al. 2023). Transect line design We carried out this study on 19 islands in TIL, including 4 large islands (> 9 ha) and 15 small islands (< 3 ha) (Fig. 2a, Table S1). On large islands, we established paired transect lines of 100-m long and 4-m wide. Pairs consisted of one edge-habitat transect and one interior-habitat transect extending perpendicular from the edge into the forest interior at each site. On small islands, we established only one transect line on each island, reflecting that habitat was more uniform on small islands compared to large islands, lacking interior non-edge habitat. The number of transect lines and the area and distance to the mainland of islands are listed in Table S1. On islands with more than two transect lines, each pair of transect line was separated by ≥ 0.5 km. We conducted surveys and collected samples on these transect lines over 2 years (2023-2024). Spider sampling A. heterothecus is a burrowing spider with an average body length of females of 19 mm (Pekár et al. 2021). A. heterothecus lives in a long tubular nest made of silk, which extends from underground to aboveground and is attached to the base of plants (Fig. 2c). A. heterothecus forages actively aboveground and preys mainly on insects (personal observation, Fig. S2). From April to August, we counted the number of A. heterothecus along each transect line once per month and the maximum number was taken as the population density per transect. We also dug up and collected two unbroken adult females (identified based on their chelicerae) from nearby but outside each transect line (Fig. 2d), and stored them in 5-ml tubes at ‑20℃; based on our prior experience with the study system, collecting these spiders outside of transects is unlikely to have affected the transects. Half of the samples were used for measuring body mass, and others were used for obtaining diet information by utilizing high-throughput-sequencing of gut contents. Samples for measuring body mass were put into a drying oven dried for 72 h at 75℃ and then weighed (accurate to 0.1 mg). Gut content sequencing for diet Gut samples were placed into absolute ethyl alcohol at ‑20℃. With repeated sampling, a total 450 adult females were collected and used for genomic DNA extractions using QIA quick Gel Extraction Kits (Qiagen Ltd., Shanghai, China) following the manufacturer’s instructions. Five samples from the same transect line were pooled to perform a single DNA extraction. All spider individuals were washed three times with ddH 2 O. All extracted genomic DNA samples were stored at -80℃. A specialized arthropod primer pair designed from COI with barcode primers ZBJ-ArtF1c (5′-AGATATTGGAACWTTATATTTTATTTTTGG-3′) and ZBJ-ArtR2c (5′-WACTAATCAATTWCCAAATCCTCC-3′) was used for amplification of a short fragment (~157 bp) (Zeale et al. 2011). The wide range of invertebrates for getting the diet of spiders (van Schrojenstein Lantman et al. 2021). The PCR reaction mixture with a total volume of 25 μl contained 12.5 μl 2×Phanta Max Master Mix (Vazyme Biotech Co., Ltd., Nanjing, China), 0.25 μl of each primer (25 µM), 4 μl of DNA template and final adjusted with PCR Grade Water. The PCR thermal cycling conditions showed in Table S2. 2µl of each PCR product was detected by 2% agarose gel electrophoresis and the target fragment was detected. The remaining PCR product was purified using the QIA quick Gel Extraction Kit (Qiagen Ltd., Shanghai, China). The DNA library was examined for conformation to standards using a Qubit Fluorometer (Thermo Fisher Scientific, Shanghai, China) and Qseq100 DNA Analyzer (Bioptic Inc., New Taipei, Taiwan of China). A DNA library of successfully amplified samples was generated by quantifying the molar concentration of the DNA library with KAPA Library Quantification Kit (KAPA Biosystems) and subsequently sent for sequencing on Illumina Novaseq 6000 platform according to the manufacturer instruction at Hangzhou Kaitai Biotechnology Co., Ltd. (Hangzhou, China). We screened out useful operational taxonomic units (OTUs) according to the methods from a previous study (Saqib et al. 2021). OTU taxonomic classification was conducted with BLAST (blastn), requiring 98% sequence identity for each representative sequence, and blasting the representative sequences against NCBI database (Sayers et al. 2024). An OTU table was further generated to calculate the abundance of each OTU in each sample and the taxonomy of these OTUs. OTUs containing less than 0.001% of total sequences across all samples were discarded. OTUs were identified to the lowest possible taxonomic level. This led to diet information for individual spiders. Finally, we determined the diet groups (pollinators and others) of prey by personal observation (see Table S3). Flowering plants and pollinators We conducted surveys of flowering plants and pollinators at each transect line on each island. The survey method was the same as Ren et al. (2023): Observations were carried out only in calm and sunny weather from 8:30 to 12:00 and from 13:00 to 17:00. We sampled all transect lines once every 2 weeks, with seven surveys conducted at each site from 22 nd March to 15 th July, 2023, and seven surveys at each site from 26 th March to 20 th July, 2024 (14 surveys in total at each transect line). We counted the abundance and richness of flowering plants and pollinators at each transect line on each island (methods see Supporting Information). Species of plants and pollinating insects were identified to the lowest possible taxonomic level. Statistical analyses Prior to conducting analyses, we tested the relationship between population density and body mass of A. heterothecus . We found a strong (r = 0.67) significant positive relationship (Table S4), and so we elected to use only spider biomass (population density multiply by average body mass) in subsequent analyses. Following Haddad et al. (2015), we considered the area (~ 3 ha) within 100 m as forest edges, so we considered three habitat types: large island edges, large island interiors and small islands (< 3 ha), with small islands lacked a distinct interior habitat type. For testing H1 , we used general linear models to assess the relationships of island area (log-transformed) and island isolation (distance to mainland) against the spider biomass. For testing H2 , we used a Kruskal-Wallis test to compare the differences of spider biomass among the three habitats (large island edge, large island interior and small island). To get the total diet information of A. heterothecus , we tested high-throughput-sequencing completeness with the ‘ specaccum ’ function in the R package ‘ vegan ’ (v.2.6-6.1) (Fig. S3) and visualized the spider-prey network with the ‘ plotweb ’ function in the R package ‘ bipartite ’ (Dormann et al. 2008) and then counted the proportion of diet groups (pollinators and others) among the three habitats (Oksanen et al. 2024). We also used a Kruskal-Wallis test to compare prey richness of A. heterothecus among the three habitats and compared the prey composition of A. heterothecus among the three habitats using non-metric multidimensional scaling (NMDS) based on Bray-Curtis dissimilarity (Oksanen et al. 2024). For testing H3 , we used Kruskal-Wallis tests to compare the differences of richness and abundance of flowering plants and pollinators among the three habitats. Subsequently, we used the R package ‘ piecewiseSEM ’ (v.2.3.1) to explore the mechanisms underlying the trophic control on multi-trophic interactions (Lefcheck 2016). We constructed two models to test the bottom-up effect and top-down effect (Fig. S1). These models were simple linear models (lm) using Z-score-transformed variables. Based on the Akaike information criterion (AIC), we selected the best-fit model by removing non-significant links and variables (Shipley 2013). We tested for the best-fit model using Shipley’s d-separation test via a Fisher’s C statistic and P -value. All analyses were performed using R version 4.4.1 (R Core Team 2024). Effects of habitat fragmentation on spider biomass In total, we collected 900 A. heterothecus samples across all transect lines on the 19 islands. Simple linear models showed that island area ( P = 0.34; Fig. 3a, Table S5 ) and island isolation ( P = 0.82; Fig. 3b, Table S5 ) did not have significant effects on spider biomass. Spider biomass showed a significant edge effect, with the largest values on large island edges, followed by small islands, and then large island interiors , with significant differences among all habitat categories ( P < 0.001; Fig. 3c , Table S6). The spider-prey network showed a total of 120 interactions of A. heterothecus among the three habitats and spiders preyed mainly on pollinators (connectance = 0.57; Fig. 4a). A total of 70 species belonging to 10 orders were preyed on by A. heterothecus, representing Lepidoptera (23 species), Diptera (13 species), Coleoptera (10 species), Orthoptera (9 species), Hymenoptera (7 species), Hemiptera (4 species), Blattodea (2 species), Entomobryomorpha (1 species) and Scutigeromorpha (1 species) (Fig. 4a, Table S3). Counts showed that pollinators (49 species) made up a large proportion (over 50%) of A. heterothecus diet across the three habitats (Fig. 4b) . A Kruskal-Wallis test showed significant differences of prey richness of A. heterothecus among the three habitats with the largest values on large island edges, followed by small islands, and then large island interiors ( P < 0.001; Fig. 4c , Table S6). NMDS analysis based on Bray-Curtis distance also showed that diet composition of A. heterothecus in interiors was significantly different from that of edges (stress = 0.13, k =2; Fig. 4d). Flowering plants and pollinators In total, we counted 93 plant species and 273 pollinator species over 2 years. Flowering plants belonged to 39 families and 81 genera, and pollinators belonged to five orders (Hymenoptera, Diptera, Coleoptera, Lepidoptera and Hemiptera). The richness and abundance of flowering plants and pollinators significantly differed among the three habitats, with large island interiors having the lowest values, and no difference between large island edges and small islands (Fig. 5 , Table S6). Structural equation models In the final bottom-up effect model, five hypothesized paths were retained and final model included several significant effects: flowering plant richness had significant positive effects on the richness of pollinators and prey; pollinator richness had a significant positive effect on prey richness; and, the richness of pollinators and prey had significant positive effects on spider biomass (Fisher’s C = 1.39, P = 0.50, AIC = 594.02; Fig. 6a, Table S7 ). In the final top-down effect model, eight hypothesized paths were retained: spider biomass had significant positive effects on the richness of pollinators and prey; pollinator abundance, pollinator richness had a significant positive effect on prey richness; pollinator abundance had significant positive effects on the richness and abundance of flowering plants; prey richness had a significant positive effect on flowering plant richness; and pollinator richness had a significant negative effect on flowering plant richness (Fisher’s C = 10.15, P = 0.43, AIC = 1028.80; Fig. 6b, Table S7 ). Overall, we found substantial evidence of both bottom-up and top-down effects. Because the dependent variables are different in the top-down and bottom-up SEM’s the fit of the two kinds of models is not easily compared, but R 2 -values were substantial for dependent variables in both kinds of models. Discussion Habitat fragmentation has been shown to have positive effects on biodiversity and species interactions in some studies, yet the underlying mechanisms of the positive effects are frequently unexplored (Fahrig et al. 2019). Here, we determined how habitat fragmentation enhances predator biomass through edge effects and bottom-up effects that act across multiple trophic levels. Although top-down effects of spider predation were evident, they were insufficient to suppress prey biomass when predator biomass was high. We used high-throughput-sequencing to identify prey species (diet composition) and used piecewise SEM to identify the top-down and bottom-up effects. Our results highlight that multi-trophic interactions have a critical function to understand the mechanisms by which positive effects can counteract some of the negative effects of habitat fragmentation. Habitat fragmentation may increase extinction rates, especially for higher trophic level species (Davies et al. 2000, Liao et al. 2017, Wang et al. 2024). Specifically, populations of higher trophic levels (e.g. predators) tend to decline and may even go extinct in smaller and more isolated patches because of lower population density. For instance, a previous study in our study system found that abundance of herbivorous and predatory insects declined with decreasing island area (Wang et al. 2024). In our study, higher spider biomass resulted from both their higher population density and higher body mass (Table S4). Unexpectedly, our results showed no significant declines in spider biomass on smaller and more isolation islands (Fig. 3a, b). Instead, spider densities were higher in edge habitats, with large island edges and small islands supporting greater spider biomass than large island interiors (Fig. 3c). Our results support the idea that positive edge effects relieved and even reversed the population decline process of spiders on small and isolated islands. This conclusion was evidenced in vertebrates with abundance of 46% species performing positive response to forest edges in earlier studies (Pfeifer et al. 2017), while invertebrate pollinators had a similar pattern in our study system (Ren et al. 2023). For most invertebrates, body size has been found to increase as a result of habitat fragmentation (König and Krauss 2019, de Cerqueira et al. 2023, Jia et al. 2024). Several mechanisms have been proposed to explain this change of body size, including reduced predation, relaxed competition and resource limitation in island environments (Benítez-López et al. 2021). In our study system, the perimeter-area ratio had a significant negative correlation with bird guild richness, with more edge habitats increasing the local extinction risk of birds (Ding et al. 2015). Hence, a decrease of bird predators could have led to the observed increase in spider biomass (Dunham 2008, Herrmann et al. 2012). Relaxed interspecific competition could also contribute to explaining the higher biomass of spiders since fragmentation changed the composition of spider communities in our study system (Wu et al. 2017). Nevertheless, we propose that increased prey resources may be one of the main mechanisms for edge habitats facilitating spider population density and body size. Our diet analyses showed that pollinators made up more than 50% of the prey resources of the spider species (Fig. 4a, b). Furthermore, prey richness and composition showed significant edge effects with similar trends to changes in spider biomass (Fig. 4c, d). Consistent with previous findings that changes in prey availability induced by habitat fragmentation can affect spider biomass (Bucher and Entling 2011), we found that richness and abundance of pollinators had similar responses to fragmentation as prey richness of spiders (Fig. 5c, d), with large island edges and small islands having higher prey richness than larger island interiors. High pollinator richness and abundance at edges was related to increased abundance and richness of flowering plants at edges, which are expected to result from high irradiance and warm conditions (Fig. 5a, b) (Mendes and Prevedello 2020, Ren et al. 2023). Hence, consistent with patterns reported in other studies, we conclude that better prey resources likely enhanced spider biomass at edges (Ryall and Fahrig 2006). Previous studies have shown both top-down and bottom-up responses to habitat loss and fragmentation (Ryall and Fahrig 2006, Šálek et al. 2010). Nevertheless, most have emphasized negative effects on predators and consequent top-down regulation (Terborgh et al. 2001, Genua et al. 2017). In contrast, our piecewise SEM results support bottom-up effects over top-down effects. Specifically, increased flowering plant richness indirectly enhanced the spider biomass through affecting pollinator abundance and richness (Fig. 6a). This pattern is consistent with insect and plant studies in our system where producer increases increased densities of primary consumers and predators (Wang et al. 2024). Interestingly, we also found that spider population density was positively correlated with body mass of the spider (Table S4), likely because abundant prey resources relieved intraspecific competition (Bucher and Entling 2011). Although our results provide substantial evidence for bottom-up effects on predatory spiders, this conclusion should be interpreted with caution because it contrasts with previous studies (Terborgh et al. 2001, Genua et al. 2017). Unfortunately, we did not include the top-down effects from predators of spiders, such as birds. We speculate that invertebrate and vertebrate predators may have different responses to habitat fragmentation due to differences in body size, thereby exerting distinct trophic control effects (Wang et al. 2020). While our study may not test this hypothesis, it highlights the need to consider predators of different body size in future studies on the relationship between trophic control and habitat fragmentation. Conclusion Overall, we found positive edge effects of fragmentation on predatory spiders with multiple lines of evidence supporting bottom-up effects as the primary driver. 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Intraspecific leaf trait variation mediates edge effects on litter decomposition rate in fragmented forests. - Ecology 105: e4260. Figures Figure 1. Conceptual diagram illustrating the hypotheses regarding the effects of habitat fragmentation (area, isolation and edge effect) on spider biomass (population density multiply by body mass) and causing bottom-up or top-down effects on multi-trophic relationships between flowering plants, pollinators, and the spider A. heterothecus . H1 predicts that the spider biomass will decrease in smaller and more isolated patches. H2 predicts that the spider biomass will differ between island edges and interiors. H3 predicts that changes of the spider biomass will affect pollinators and flowering plants or be affected by them through top-down or bottom-up effects. Details of hypotheses are given in the Introduction. Figure 2. The study region photographs of landscape and the field photographs of A. heterothecus . (a) Study area is located at the Thousand Island Lake (TIL) in Zhejiang province, eastern China. The white areas in the main map represent water, the gray areas represent land, and the green areas and numbered or letter-coded islands represent the 19 islands studied. Island codes with red circle represent four large islands and others are small islands. (b) Landscape of TIL with various islands formed by dam construction and water storage. (c) The silk tube of A. heterothecus on aboveground attaches the base of a tree. (d) Collecting an A. heterothecus sample by digging. Credit: photograph (b) by Jincao Pan; photograph (c) and (d) by Wenlong Zhou. Figure 3. The effects of habitat fragmentation on spider biomass (g). (a) Area effect, (b) Isolation effect, and (c) Edge effect. Dotted lines represent a non-significant correlation ( P > 0.05). Bars with different letters had significant difference between them. LIE, large island edge; LII, large island interior; SI, small island. Figure 4. The effects of habitat fragmentation on spider-prey interactions. (a) Spider-prey interactions in three habitats. Prey were divided into pollinators and others (see Table S2). (b) Proportion of pollinators vs. other taxa based on richness in three habitats. (c) The differences of prey richness of A. heterothecus in three habitats. Bars with different letters were significantly different. (d) NMDS analysis based on Bray-Curtis distance of diets of A. heterothecus showing the difference between the three habitats. LIE, large island edge; LII, large island interior; SI, small island. Figure 5. The differences of (a) flowering plant richness, (b) flowering plant abundance, (c) pollinator richness, (d) pollinator abundance between the three habitats. LIE, large island edge; LII, large island interior; SI, small island. Figure 6. Piecewise structure equation models showing (a) the bottom-up effect, (b) the top-down effect on multi-trophic relationships. Black arrows represent significant positive relationships and red arrows represent significant negative relationships. Values along paths are standardized partial regression coefficients. The width of each arrow is scaled to the absolute value of the standardized path coefficient. The R 2 values within the squares show the explained proportion of variance in the response variables. * P <0.05; ** P < 0.01; *** P < 0.001. Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Information & Authors Information Version history V1 Version 1 04 September 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords bottom-up effects edge effects habitat fragmentation high-throughput-sequencing multi-trophic interactions spider Authors Affiliations Wenlong Zhou 0009-0008-8102-0076 Zhejiang University View all articles by this author Peng Ren 0000-0001-6033-6188 Zhejiang University View all articles by this author Marcel Holyoak 0000-0001-9727-3627 University of California Davis View all articles by this author Donghao Wu 0000-0003-3568-0782 Zhejiang University View all articles by this author Chen Zhu Zhejiang University View all articles by this author Wenjie Zhou Zhejiang University View all articles by this author Ping Ding Zhejiang University View all articles by this author Mingjian Yu 0000-0001-8060-8427 [email protected] Zhejiang University View all articles by this author Metrics & Citations Metrics Article Usage 223 views 162 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Wenlong Zhou, Peng Ren, Marcel Holyoak, et al. 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