Ecology

Molecular Phylogeny of Paramecium bursaria and Identification of its EndosymbiontsThe SSU and ITS rDNA of the nuclear ribosomal operon were sequenced to infer the genetic variability of the investigated strains. The SSU and ITS rDNA sequences were aligned according to their secondary structure (examples are presented for the strain SAG 27.96; Fig. 1 and Supplementary Fig. 1). Additional sequences acquired from GenBank were incorporated into a dataset, which included all syngens also from references known for P. bursaria. The phylogenetic analyses revealed five highly supported lineages among the P. bursaria strains, which corresponded to their syngen assignment. As demonstrated in Fig. 2, all investigated strains belonging to the syngens R1, R2 and R5 originated from Europe, whereas the others of the syngens R3-R4 showed a worldwide distribution. The three known green algal endosymbionts, i.e., Chlorella variabilis (Cvar), Chlorella vulgaris (Cvul) and Micractinium conductrix (Mcon) showed no or only little affiliation to specific syngens.Figure 1ITS‐1 (A) and ITS-2 (B) secondary structures of Paramecium protobursaria, SAG 27.96 (syngen R1).Full size imageFigure 2Molecular phylogeny of the Paramecium bursaria species complex based on SSU and ITS rDNA sequence comparisons. The phylogenetic tree shown was inferred using the maximum likelihood method based on the datasets (2197 aligned positions of 19 taxa) using the computer program PAUP 4.0a169. For the analyses, the best model was calculated by PAUP 4.0a169. The setting of the best model was given as follows: TVM + I (base frequencies: A 0.2983, C 0.1840, G 0.2271, T 0.2906; rate matrix A–C 2.6501, A–G 8.6851, A–U 5.3270, C–G 0.91732, C–U 8.6851, G–U 1.0000) with the proportion of invariable sites (I = 0.9544). The branches in bold are highly supported in all bootstrap analyses (bootstrap values  > 50% calculated with PAUP using the maximum likelihood, neighbour—joining, and maximum parsimony). The clades are named after the syngens (color‐coded) proposed by Greczek‐Stachura et al.10 and Bomford9 in brackets. The accession numbers are given after the strain numbers. The endosymbiotic green algae identified are highlighted (Mcon—Micractinium conductrix, Cvar—Chlorella variabilis and Cvul—Chlorella vulgaris) after the origin of the P. bursaria strains. The reference strain of each syngen is marked with an asterisk. The strains used for morphological comparisons are marked with a green dot next to the strain number.Full size imageSynapomorphies of the Paramecium bursaria SyngensAs demonstrated in Fig. 2, the subdivision of the P. bursaria strains into syngens is supported by the phylogenetic analyses of the SSU and ITS rDNA sequences. To figure out if these splits were also supported by characteristic molecular signatures, we studied the secondary structures of both SSU and ITS of all available sequences. We discovered 30, respectively 23 variable positions among the SSU and ITS sequences (numbers of these positions in the respective alignments are given in Fig. 3). All syngens showed characteristic patterns among the SSU and ITS. Only the syngens R1 and R2 could not be distinguished using the SSU only, however, in combination with the ITS, each syngen is characterized by unique synapomorphies as highlighted in yellow (Fig. 3). In addition, few variable base positions within syngens (marked in blue in Fig. 3) have been recognized in the ITS regions. For comparison with literature data, we also analyzed all available sequences of the mitochondrial COI gene to find synapomorphies for the five syngens. Within this gene, only 18 variable positions at the amino acid level could be discovered of which 13 are diagnostic for the five syngens (Fig. 3).Figure 3Variable base positions among the SSU, ITS rRNA, and COI sequences of the five syngens among the Paramecium bursaria species complex. The unique synapomorphies are highlighted in yellow, variable positions marked in blue.Full size imageThe synapomorphies discovered above were used to get insights into the geographical distribution of each P. bursaria syngen. Despite the complete SSU and ITS rDNA sequences included in the phylogeny presented in Fig. 2, records of the partial SSU or ITS rDNA sequences are available in GenBank (BLASTn search; 100% identity;13). Considering the metadata of our investigated strains and of the entries in GenBank (Supplementary Table 1), we constructed three haplotype networks using the Templeton-Crandall-Sing (TCS) approach. The SSU haplotype network (Fig. 4) containing 84 records showed that the syngens R1, R2 and R5 were only found in Europe, whereas the other three syngens have been discovered around the world. A similar distribution pattern occurred when using the ITS (101 entries in GenBank). Records of syngens R1 and R5 have only been found in Europe, whereas all other syngens were distributed around the world. The 132 COI records found in GenBank by the BLASTn search were used for the haplotype network, which also showed the similar pattern (Fig. 4).Figure 4TCS haplotype networks of the five syngens inferred from SSU, ITS rRNA, and COI sequences of the Paramecium bursaria species complex. This network was inferred using the algorithm described by Clement et al.40,41. Sequence nodes corresponding to samples collected from different geographical regions.Full size imageCiliate TaxonomyConsidering all our findings, P. bursaria is morphologically highly variable, and obviously represents a cryptic species complex (Figs. 5, 6; Supplementary Table 2). The known five syngens most likely represent biological species according to Mayr14 and can be attributed to the cryptic species described by Greczek-Stachura et al.11. As mentioned above, the assignments of these cryptic species by Greczek-Stachura et al.11 have not been validly described according to the ICZN. In addition, the naming using a mixture of Latin prefix and Greek suffix is also not appropriate (the epithet bursa derived from the Greek word byrsa). Therefore, we describe the five syngens as new species as follows. The general morphological features of these species are summarized in Table 1.Figure 5Ventral views of Paramecium bursaria morphotypes in vivo: P. protobursaria (syngen R1), i.e., strains SAG 2645 (A) and PB-25 (B); P. deuterobursaria (syngen R2), i.e., strains CCAP 1660/36 (C) and CCAP 1660/34 (D); P. tritobursaria (syngen R3), i.e., strains CCAP 1660/28 (E), CCAP 1660/26 (F) and CCAP 1660/31 (G); P. tetratobursaria (syngen R4), i.e., strains CCAP 1660/25 (H) and CCAP 1660/33 (I); P. pentobursaria (syngen R5), i.e., strain CCAP 1660/30 (J). Scale bar 20 µm.Full size imageFigure 6Morphological details of the Paramecium bursaria species complex from specimens of strains PB-25 (A), CCAP 1660/30 (B), SAG 2645 (C, F, G, I, L–N), CCAP 1660/36 (D), CCAP 1660/26 (E, H), CCAP 1660/30 (J, O), CCAP 1660/16 (K) in vivo (A–F, H–O) and after silver nitrate staining (G). Adoral membranelles (A, B), endosymbiotic algae Micractinium conductrix (C), caudal and somatic cilia (D), arrows denote excretory pores of the contractile vacuoles: extruded extrusomes are shown and caudal cilia (E), ventral views showing the preoral suture and the oral opening (F), the ciliary pattern (G), arrows denote excretory pores of the contractile vacuoles (H), trichocysts and symbiotic algae underneath the pellicula (I, J), cell size variations (K), radial collecting channels (white arrows) and excretory pores (black arrows) of contractile vacuoles (L), macro- and micronucleus (M), cytopyge and characteristic rectangular pellicular pattern (N), pattern of the pellicula (O). AS anterior suture, CC caudal cilia, CP cytopyge (cell after), CV contractile vacuole, EP excretory pore of a contractile vacuole, EX extrusomes, M1–M3 membranelles 1–3, MA macronucleus, MI micronucleus, OO oral opening, S symbiotic algae, SC somatic cilia, SK somatic kineties, UM undulating membrane. Scale bars 10 µm (A, I), 20 µm (B, D–H, J, L–O), 50 µm (K).Full size imageTable 1 Main morphometric and morphological characteristics of the Paramecium bursaria syngens (min and max values).Full size table
Paramecium protobursaria sp. nov.Synonym: Paramecium primabursaria nom. inval.Description: The strains SAG 27.96 and PB-25 belong to syngen R1 according to Greczek-Stachura et al.10,11 and differ from other syngens by their SSU and ITS rDNA sequences (MT231333). From morphology, the cells are ellipsoidal to broadly ellipsoidal and dorso-ventrally flattened in vivo. The cells measure 70–164 × 44–65 µm; the single macronucleus is located around mid-cell and measures 25–38 × 11–22 µm; the adjacent single compact micronucleus measures 11–20 × 5–8 µm; the usually two (rarely one) contractile vacuoles, one in the anterior and one in the posterior cell portion have radial collecting channels and 1–3 excretory pores each; the number of ciliary rows/20 µm is 14–22; the length of the caudal cilia is 9–19 µm; the numerous trichocysts located in the cell cortex are 4–6 µm in length. The symbiotic algae belong to M. conductrix; the larger algae measure 4–7 × 4–7 µm; the smaller algal cells measure 2–5 × 2–5 µm.Geographic distribution: The investigated strains of syngen R1 were found in Europe: Göttingen, Germany; Lake Mondsee, Austria. In addition, this species has been reported from different places in Europe, Asia and North America (see details in Supplementary Table 1).Reference material: Strain SAG 27.96 and the clonal strain SAG 2645 derived from SAG 27.96 are available at the Culture Collection of Algae (SAG), University of Göttingen, Germany.Holotype: Two slides (one holotype, one paratype) with protargol-impregnated specimens from the clonal culture SAG 2645, which derived from the reference material SAG 27.96, isolated from the pond of the Old Botanical Garden of the University of Göttingen (Germany), have been deposited in the Oberösterreichisches Landesmuseum at Linz (LI, Austria).Zoobank Registration LSID: AFD967ED-BC2A-43FD-847E-5DF588BB025C.
Paramecium deuterobursaria sp. nov.Synonym: Paramecium bibursaria nom. inval.Description: The strains CCAP 1660/34 and CCAP 1660/36 belong to syngen R2 according to Greczek-Stachura et al.10,11 and differ from other syngens by their SSU and ITS rDNA sequences (OK318487). From morphology, the cells are ellipsoidal to broadly ellipsoidal and dorso-ventrally flattened in vivo. The cells measure 81–167 × 35–83 µm; the single macronucleus is located around mid-cell and measures 24–46 × 10–32 µm; the adjacent single compact micronucleus measures 10–18 × 5–9 µm, no micronucleus seen in live cells of strain CCAP 1660/34; the usually two (rarely one or three) contractile vacuoles, one in the anterior and one in the posterior cell portion have radial collecting channels and 1–3 excretory pores each; the number of ciliary rows/20 µm is 13–22; the length of the caudal cilia is 11–20 µm; the numerous trichocysts located in the cell cortex are 4–6 µm in length. The symbiotic algae belong to M. conductrix; the larger algae measure 5–7 × 4–7 µm; the smaller algal cells measure 3–5 × 2–5 µm.Geographic distribution: The investigated strains of syngen R2 were found in Europe: Zurich, Switzerland; Lake Piburg, Austria. In addition, this species has been reported from different places in Europe, Asia and Australia (see details in Supplementary Table 1).Reference material: Strain CCAP 1660/36 is available at the Culture Collection of Algae and Protozoa (CCAP) at the Scottish Association for Marine Science, Oban, Scotland.Holotype: Two slides (one holotype, one paratype) with protargol-impregnated specimens from the reference material CCAP 1660/36, isolated from Lake Piburg (Tyrol, Austria), have been deposited in the Oberösterreichisches Landesmuseum at Linz (LI, Austria).Zoobank Registration LSID: D1C20BE6-9A15-4A3D-A7E5-DFC31FF04679.
Paramecium tritobursaria sp. nov.Synonym: Paramecium tribursaria nom. inval.Description: The strains CCAP 1660/26, CCAP 1660/28 and CCAP 1660/31 belong to syngen R3 according to Greczek-Stachura et al.10,11 and differ from other syngens by their SSU and ITS rDNA sequences (MT231339). From morphology, the cells are ellipsoidal to broadly ellipsoidal and dorso-ventrally flattened in vivo. The cells measure 80–153 × 49–73 µm; the single macronucleus is located around mid-cell and measures 21–53 × 12–31 µm; the adjacent single compact micronucleus measures 9–17 × 3–6 µm; no micronucleus seen in live cells of strain CCAP 1660/28; the usually two (rarely one or three) contractile vacuoles, one in the anterior and one in the posterior cell portion have radial collecting channels and 1–3 excretory pores each; the number of ciliary rows/20 µm is 12–20; the length of the caudal cilia is 8–19 µm; the numerous trichocysts located in the cell cortex are 4–6 µm in length. The symbiotic algae belong to C. variabilis; the larger algae measure 4–7 × 3–6 µm; the smaller algal cells measure 3–5 × 2–4 µm.Geographic distribution: The investigated strains of syngen R3 were found in Europe and Asia: Lake Piburg, Austria; Tokyo, Japan; Khabarovsk region, Amur River, Russia. In addition, this species has been reported from different places in Europe, Asia, North and South America as well as in Australia (see details in Supplementary Table 1).Reference material: Strain CCAP 1660/26 is available at the Culture Collection of Algae and Protozoa (CCAP) at the Scottish Association for Marine Science, Oban, Scotland.Holotype: Two slides (one holotype, one paratype) with protargol-impregnated specimens from the reference material CCAP 1660/26, isolated from Japan, have been deposited in the Oberösterreichisches Landesmuseum at Linz (LI, Austria).Zoobank Registration LSID: CC0FBA7E-9E3A-4C37-B424-C9BFF2018EC0.
Paramecium tetratobursaria sp. nov.Synonym: Paramecium tetrabursaria nom. inval.Description: The strains CCAP 1660/25 and CCAP 1660/33 belong to syngen R4 according to Greczek-Stachura et al.10,11 and differ from other syngens by their SSU and ITS rDNA sequences (MT231347). From morphology, the cells are ellipsoidal to broadly ellipsoidal and dorso-ventrally flattened in vivo. The cells measure 65–179 × 37–79 µm; the single macronucleus is located around mid-cell and measures 18–53 × 10–29 µm; the adjacent single compact micronucleus measures 8–18 × 4–10 µm; the usually two (rarely one or three) contractile vacuoles, one in the anterior and one in the posterior cell portion have radial collecting channels and 1–3 excretory pores each; the number of ciliary rows/20 µm is 14–19; the length of the caudal cilia is 12–20 µm; the numerous trichocysts located in the cell cortex are 4–7 µm in length. The symbiotic algae belong to C. variabilis (CCAP 1660/25) and M. conductrix (CCAP 1660/33); the larger algae measure 3–6 × 3–6 µm; the smaller algal cells measure 2–5 × 1–4 µm.Geographic distribution: The investigated strains of syngen R4 are found in North- and South America: Burlington, North Carolina, USA; San Pedro de la Paz, Laguna Grande, Chile. In addition, this species has been reported from Europe (see details in Supplementary Table 1).Reference material: Strain CCAP 1660/25 is available at the Culture Collection of Algae and Protozoa (CCAP) at the Scottish Association for Marine Science, Oban, Scotland.Holotype: Two slides (one holotype, one paratype) with protargol-impregnated specimens from the reference material CCAP 1660/25, isolated from a pond in Burlington (North Carolina, USA), have been deposited in the Oberösterreichisches Landesmuseum at Linz (LI, Austria).Zoobank Registration LSID: 78BA9923-07A9-4918-AD7C-9E5E15CC9CDB.
Paramecium pentobursaria sp. nov.Synonym: Paramecium pentabursaria nom. inval.Description: The strain CCAP 1660/30 belongs to syngen R5 according to Greczek-Stachura et al.10,11 and differs from other syngens by their SSU and ITS rDNA sequences (MT231348). From morphology, the cells are ellipsoidal to broadly ellipsoidal and dorso-ventrally flattened in vivo. The cells measure 161–194 × 76–99 µm; the single macronucleus is located around mid-cell and measures 24–47 × 19–31 µm; the adjacent single compact micronucleus measures 13–20 × 4–9 µm; the usually two (rarely one or three) contractile vacuoles, one in the anterior and one in the posterior cell portion have radial collecting channels and 1–4 excretory pores each; the number of ciliary rows/20 µm is 13–19; the length of the caudal cilia is 14–25 µm; the numerous trichocysts located in the cell cortex are 5–7 µm in length. The symbiotic algae belong to C. variabilis; the larger algae measure 5–6 × 5–6 µm; the smaller algal cells measure 4–5 × 3–4 µm.Geographic distribution: The investigated strain of Syngen R5 was found in Europe: Astrakhan Nature Reserve, Russia.Reference material: Strain CCAP 1660/30 is available at the Culture Collection of Algae and Protozoa (CCAP) at the Scottish Association for Marine Science, Oban, Scotland.Holotype: Two slides (one holotype, one paratype) with protargol-impregnated specimens from the reference material CCAP 1660/30, isolated from Astrakhan Nature Reserve (Russia), have been deposited in the Oberösterreichisches Landesmuseum at Linz (LI, Austria).Zoobank Registration LSID: 6629FA71-E00F-48C6-83AB-61C0CA4823B6.Syngen Affiliation related to Ciliate Morphology, Endosymbionts and Geographic DistributionPearson-correlations of morphometric, syngen-specific and endosymbiont datasets of the P. bursaria strains revealed four significant positive correlations (p  r  > 0.75) between ciliate cell length (BLEN) and width (BWID), BWID and macronucleus width (MACWID), as well as length and width of large symbiotic algae (LSALEN and LSAWID; Fig. 7).Figure 7Pearson-correlations of morphometric, symbiont and syngen data of Paramecium strains under study. Colored dots indicate the strength of correlation, and the size of dots represent p-values. Bold squares highlight significant correlations, with − 0.75  > r  > 0.75 and p  1, accounting for 73.1% variation in total (Supplementary Table 3). Principal component axis 1 (PC1) appears to be most negatively weighted by syngen (SYN) and width of the macronucleus (MACWID), separating CCAP 1660/30 and CCAP 1660/33 from the other strains. Principal component axis 2 (PC2) is primarily positively influenced by symbiotic algae characteristics (LSALEN, LSAWID, small symbiotic algal length (SSALEN) and width (SSAWID)) and, ciliate cell length (BLEN) and width (BWID; Supplementary Table 4), partitioning strain PB-25, CCAP 1660/26 and CCAP 1660/36 from CCAP 1660/31 and SAG 27.96 (Fig. 8).Figure 8PCA of morphometric data of Paramecium bursaria strains. Only the top eight contributing variables are shown.Full size imageThe redundancy analysis (RDA; Fig. 9) revealed a large difference between morphometric features and the tested set of explanatory variables (i.e., algal species (ALSPEC), LSAWID, SSALEN, SYN and GEO) as only 26.9% of the total variation could be explained.Figure 9Ordination diagram for redundancy analysis (RDA) of morphometric data and shown syngen (SYN), geographic region (GEO), and algal features (ALSPEC, LSAWID and SSALEN) as explanatory features.Full size image More

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Project 1: mesocosm field experimentsMesocosm experiments took place at Lockwood Farm located in Hamden, Connecticut. Individual mesocosms were composed of black 20 L cylindrical plastic containers filled with 12 L tap water and seeded with 10 mg of a 3:2 ratio liver powder/brewer’s yeast mixture and 1 g of grass hay. Drain-holes were drilled into the sides of each container 5 mm from the 12 L surface to allow flooding for Aedes spp. egg emergence and to allow overflow beyond this level due to precipitation. Four experimental mesocosm clusters were dispersed throughout the Lockwood Farm in microhabitats previously sampled in Eastwood et al.22. Clusters contained 4 mesocosms spaced 3 m apart in a 2 × 2 grid. We utilized four L. sphaericus treatment levels in each cluster: no L. sphaericus, the LC50 (0.053 ITU/ml) and LC95 (1.0 ITU/ml) for Culex pipiens derived from Burtis et al.3, and the label rate of L. sphaericus (~ 1.2 ITU/ml). All treatments were derived from VectoLex WDG. Prior to insecticide application, we prepared 1 L of a 1000 ITU/ml stock solution. To inoculate each mesocosm, we measured the depth of the container’s water column, calculated water volume, and applied the appropriate amount of stock to achieve the target LC value. Replicate insecticide treatments were randomized within each cluster, and insecticides were applied 30-days post mesocosm seeding with nutrients. All mesocosms in each cluster were rotated within the 2 × 2 grid each week. Two clusters were then randomly chosen for a second application of L. sphaericus 30-days post initial insecticide application.To sample the larval habitat of each mesocosm, we performed a figure-8 sweep with an aquarium fish net (4 × 3-in. opening, Penn-Plax) each Monday and Thursday of the week for each week of the experiment. Sweep contents were washed from the net into a white photo development pan, and pupae were removed for in-lab identification after eclosion following a dichotomous key23. All larvae were then returned to the mesocosm. This sampling protocol minimized destruction of larval habitats and influence of interspecific interactions due to removal sampling.In addition to sampling containers for pupae, we collected water samples from each container for an in-lab bioassay to determine the realized mortality of the larval environment. Due to time constraints of the field crew, a 50% randomized sample of containers were sampled on Monday with the remaining 50% sampled on Thursday of each sampling week. Bioassay procedures followed McMillan et al.24 for Cx. pipiens with the addition of screening mortality in CAES’ Ae. albopictus colonies. We finally performed in-lab susceptibility trials to L. sphaericus with larvae from CAES’ Cx. pipiens and Ae. albopictus colonies to confirm each species’ colony varied in their sensitivity to the product. Briefly, 15 3rd to 4th instar larvae of each species per replicate dose were exposed to a wide range of L. sphaericus concentrations and mortality was recorded 24-h post-exposure. Lethal concentrations were then estimated from a generalized linear model with mortality (corrected for mortality in untreated control replicates) as the response term and the log10-dose as the predictor term.Primary endpoints from the field experiment included the number and species identity of pupae collected from each mesocosm. We compared total weekly pupal collections per mesocosm using a generalized linear mixed model (GLMM) framework with treatment level and cluster ID as fixed effects, species ID and week of collection as a random effect, and a Poisson-error distribution. We repeated this analysis excluding all collected Culex spp. to examine how the L. sphaericus treatments impacted the more tolerant Aedes spp. The primary endpoint for the mortality assays was the corrected larval mortality. We initially compared mortality using a species-specific GLMM with L. sphaericus treatment concentration and treatment period as fixed effects, week of collection as a random effect, and a binomial-error distribution. Preliminary analyses revealed negligible variance attributed to week of collection, so all subsequent models were a GLM. All analyses were performed in R V4.1.325 using the following packages: tidyverse26, gridExtra27, ggplot228, ggeffects29, and glmmTMB30.Project 2: laboratory competition assaysCompetition assays took place at CAES’ main facility in New Haven, CT. This facility contains an Ae. albopictus colony (founded circa 2014 from Stratford, CT) and a Cx. pipiens colony (founded circa 2018 from New Haven, CT;). Colony maintenance for each species was similar: larval rearing pans consisted of approx. 200 eggs (on papers, Ae. albopictus, or as egg rafts, Cx. pipiens) in ~ 2 L RO water and initiated with ~ 20 ml of a 1% 3:2 liver powder/brewer’s yeast slurry. Pans were held at 25.5 °C and 80% humidity and fed ~ 20 ml of the 1% slurry every other day. Pupae were removed to an eclosion chamber and adults were allowed access to 10% sucrose solution ad libitum. Aedes albopictus females were given access to defibrinated sheep’s blood (HemoStat©) through a Hemotek membrane feeder for 1 h every 2–3 weeks and moistened, fluted filter paper was provided to collect eggs. Culex pipiens females were given access to a live, restrained buttonquail overnight once per week and a small cup seeded with 5 ml 1% slurry and 15 RO ml water was provided to collect egg rafts. The use of buttonquail was reviewed and approved in accordance with CAES Institutional Animal Care and Use Committee.We performed two experiments. All experiments consisted of the following treatments: variable ratios of Ae:Cx larvae and two L. sphaericus treatments (no treatment and 0.01 ITU/ml). Larval density (40 per container) remained constant across all replicate treatments, but Ae:Cx ratios varied from 40/0, 30/10, 20/20, 10/30, and 0/40. Nutrients supplied were a low concentration (3 mg larva−1) of a 3:2 liver powder/brewer’s yeast mix applied at the beginning of the experiment. Temperature was held constant at the colony maintenance level. Assays took place in 300 ml disposable plastic cups filled with 100 ml of RO water. The first experiments consisted of the addition of the 40 larvae as newly hatched individuals (+/− 1 day between species’ hatch) at the appropriate ratios, the larval diet, and the 0.01 ITU/ml concentration (diluted from a lab stock of 1000 ITU/ml). Assays were monitored daily until all larvae were dead and/or all larvae pupated. Experiment 2 consisted of the addition of only the Cx. pipiens larvae and the larval diet. After all Cx. pipiens had pupated, containers were treated with L. sphaericus and then the Ae. Albopictus larvae were added.Primary endpoints included species-specific pupation success. Preliminary analyses in a GLMM framework revealed negligible variance attributed to a replicate ID random effect; replicate as a random term also interfered with model convergence. Preliminary analyses further revealed there was neither a significant interaction nor an improvement in the Akaike Information Criterion between the L. sphaericus treatment and initial starting condition terms. Thus, we adopted a GLM rather than a GLMM framework in all further analyses, and species-specific mortality was analyzed as a binomial response term with treatment and initial starting conditions included as fixed effects All analyses were performed in R V4.1.325 using the following packages: tidyverse26, gridExtra27, and ggplot228. More

UAVs indeed proved to be a practical, efficient, and accurate tool in sampling insects within four different habitats in Quebec. Furthermore, different drone settings of speed, height, and net diameter may yield different insect orders, which can be useful in studies that aim to target specific insects. Nonetheless, only height, and not speed, net diameter or drone type influenced insect abundance. Compared with Lindgren funnels, drones were not only able to catch more insects in less time, but also a wider array of the insect community diversity.Our study successfully shows the promise of using drones to collect forest and wetland canopy arthropods. More arthropods were collected flying at zero meters (grazing the canopy) than flying at one meter, while different speed, net size and drone type had less of an effect on insect yield (Fig. 2). The one-meter setting was expected to yield different arthropod diversity, such as fewer terrestrial families (ex. Araneae) and more aerial families (ex. Diptera) compared to the grazing zero-meter setting. However, the proportions of the top three orders (Diptera, Hemiptera, and Araneae) were similar among settings (Fig. 3). The capture of arachnids at one meter above the canopy can be explained by webs that are attached to taller foliage in proximity to the area, or spiders ‘ballooning’ in the airspace on silk threads25. Because canopy height was not always uniform, flying while grazing the canopy underneath the drone was at times lower than other parts of the canopy. Another explanation could be jumping spiders (ex. family Salticidae) which have been found to react to a disturbance or threat by leaping, possibly into the drone net26. Though the main three orders were in similar proportion, the one-meter setting caught five fewer orders in total than the zero-meter setting did. Flying at one meter was the only setting that captured no insects of order Coleoptera, Hymenoptera, or Orthoptera, suggesting that these orders spend time in and among the wetland canopy, and are seldom above the grassy canopy (Fig. 3). Most importantly, this setting only caught nine insects total over all flights, revealing itself to be an inefficient method of insect collection. This can be due to the number of insects available to be collected at each height. When flying at one meter, the net has access to only aerial insects in flight above the canopy (ex. flies). Flying while grazing the canopy, however, gives the researcher access to the same aerial insects in flight above the canopy, but also aerial insects in flight within the canopy (ex. bees), aerial insects at rest on the canopy (ex. leafhoppers), and terrestrial insects on the canopy (ex. ants). Thus, flying the drone while grazing the canopy opens the possibility of capturing three more insect groups compared to flying above the canopy. It is also possible that there are indeed many insects to be caught solely in the airspace, but that the ideal height for collecting insects strictly above the canopy is either less than or greater than one meter—which is the only height above the canopy that we tested.This sampling period caught three total insects from order Odonata, with two of the three being caught with the 18-inch diameter net setting (Fig. 3). As these dragonflies are typically fast flyers and of large body size, perhaps the extra diameter of the larger net was helpful in increasing the chances of catching Odonates, though we do not have enough data to make solid conclusions. This would be a valuable line of future research for studies focused on dragonflies, or other large and fast-flying insects.Flying the drone and hanging sweep net at 20 km/hr yielded the highest number and proportion of insects in the order Hemiptera, which are often found at rest within the canopy27. We speculate that the faster speed of the drone striking the grassy canopy more swiftly, thus giving the insects resting on the grasses less of an opportunity to evade the threat of the approaching net. Future studies targeting the collection of true bugs should utilize a faster drone speed in flight to optimize yield.With 84% of insects found within the second layer of our net, we conclude that our novel net design with two layers of tulle is satisfactory in retaining insects and preventing most from escaping when landing the drone. In addition to the insects counted, we never witnessed any insects flying out during landing stages. We believe that our methodology of flying the drone in quickly and covering the opening of the net with cardboard before landing the drone, in addition to the extra layer of netting, was successful at retaining the insects caught. Determining how to fly the drone and net over the two forest canopy habitats was a challenge. When flying, it was impossible for the drone camera to look both forward—to see obstacles coming up, and downwards—to see how close the net was hanging regarding the top of the canopy. For this reason, we used a second drone as a spotter for the first, the pilot of which could give instructions on moving up or down. Forest canopies were particularly difficult, as the height from one tree to the next was always different, the drone had to be constantly adjusted. We experienced many snags on branches, although they were not damaging to the net or drone. Once we became comfortable flying the drone low enough to graze the canopy, snagging became a common occurrence that was easily remedied. In fact, snagging the net probably helped in the collection of insects on those branches—a technique that could be honed and used in future studies using nets and drones over forest canopies.Over our 12 days of sampling habitat canopies with drones, we were able to determine that wetlands had the highest diversity and abundance of the four habitats examined, with lake habitats showing the lowest Shannon-Weiner Diversity index (H’), and the highest Pielou’s evenness index (J). It is unsurprising that lakes showed the most even distribution of families, as is often the case with habitats having low species richness, as there are less competitors that could dominate the habitat28. Habitat, humidity, and temperature were the most important variables affecting drone insect yield, with habitat being the common variable in all high scoring models. Wetlands had by the far the most insects collected, in addition to the highest diversity and species richness. This can be explained simply by the plant composition in wetlands compared to the other habitats. While coniferous and deciduous forests are dominated by a few species (and lakes have little to no vegetation over the water) wetlands can host a wide variety of plant species. Because insect diversity correlates with plant richness and abundance, wetlands can provide shelter and sustenance for many more groups of insects that the other habitats we studied29.Lindgren funnels disproportionately collected insects from order Coleoptera (Fig. 7). Although Lindgren funnels have been used in papers reporting results focused on insects of orders Hemiptera30,31,32,33 and Diptera34,35,36, it is unclear whether some were targeted studies or all simply bycatch of the funnel from other experiments. Instead, Lindgren funnels are overwhelmingly used in Coleoptera studies as the funnels resemble a tree and attracts various wood-boring beetles37,38,39,40,41. This attraction explains the large number and proportion of beetles caught in funnels in this study. However, diversity indices show that in three of four habitats, drones collect a higher diversity sample than the Lindgren funnels (Tables 1 and 2). Thus, though Lindgren funnels are undoubtedly effective at collecting beetles from the environment, our results indicate that the drone collection method is preferable when seeking an accurate representation of the insect diversity of the habitat. Studies focused on Coleoptera could also employ this method, which would be helpful in determining the status and proportion of beetles within the population and compared to other insect orders.In addition to the larger diversity collected by drones, the temporal advantage of this technique over the funnels can not be understated. During our study, it took three Lindgren funnel traps established for seven days to collect a total of 36 insects at the wetland sites (0.001 insect collected per minute). Comparatively, at the same height and placement, drones were able to collect 391 insects in only a combined 36 min (10.9 insects collected per minute) (Fig. 7). This large difference in both yield and time scale demonstrates that the drone collection method is vastly more efficient at arthropod sampling compared to the Lindgren funnels.While this study was successful at validating the usefulness of drones in canopy entomology studies and insect collection in general, it does have its limitations. Optimal drone settings were only examined at wetland grassy canopy sites, and it is possible that the drone might perform differently within different habitats. For example, grazing the canopy at 20 km/hr might result in high insect yield at wetlands, where the lack of obstacles made it relatively easy to fly quickly. But the same settings may be unrealistic and prone to net snagging when sampling over other habitats, such as the coniferous forest canopy. Furthermore, Lindgren funnels were an acceptable comparison to drone collection for yield and diversity at some habitats, however it was impossible to get the funnels up into the canopy where sampling took place at coniferous and deciduous sites. There is no doubt that the advantage of this method lies in its accessibility, speed, and safety—studies that need more precise and fine sampling might not benefit from drones.Overall, our research demonstrates that drones are an efficient and accurate tool in collecting a wide diversity of insects above the canopies of different habitats. Benefits included rapidly and safely sampling the airspace while drawbacks included battery life limiting the duration of sampling. If this new technique is integrated into the field of entomology, canopy studies can be done much more often, for less money, and more safely than they have been done using other techniques. In 2019, a review of the potential causes of decline of aerial insectivores concluded that insect declines and changes in high quality prey availability could be a large driver of insectivore declines9. However, there is a lack of research detailing insect trends over time. The drone collection method used in this study could provide the missing link between the need for more research of aerial canopy insects and the limitations of the current methodology in entomology. This technique can be used in conjunction with aerial insectivore surveys and diet studies to begin to determine the relationship between declining predators and prey. Future research may also use and add to our guidelines to customize drone and net settings for studies targeting specific insect orders or families. More