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Distribution of Stentor pyriformis in Japan and its optimal culture conditions
S. pyriformis was described by Johnson in 18936. This algae-bearing Stentor has separated spherical macronuclei without pigmentation, which certainly differentiates it from other Stentor species (see Table S1, Fig. 5B). While the most common algae-bearing Stentor, S. polymorphus assumes a slender trumpet shape (often shortened), S. pyriformis never resembles such a slender trumpet, but assumes a pear or short conical shape, even when it is swimming6. Presence or absence of colored pigmentation is also a prominent characteristic for separating Stentor species. Among algae-bearing Stentor spp., S. polymorphus and S. pyriformis only are considered colorless species, whereas colored species are S. amethystinus, S. fuliginosus, S. araucanus, and S. tartari8 (Table S1). Therefore, S. pyriformis is a clearly discernible species; however, it remains underexplored. Indeed, we could only find one paper on the new habitats of S. pyriformis7, with the exception of the paper of species consolidation of this genus8. We confirmed the presence of S. pyriformis at 23 locations (Fig. 1A). This indicates that S. pyriformis is by no means a rare organism. We assume one of the reasons why S. pyriformis has been poorly studied is the difficulty of cultivation. In fact, Johnson6 noted that he could not keep them more than a month and never observed any cells in fission. In addition, after five years of failure, it was finally possible to culture S. pyriformis for more than several months. Because of objectively unfounded data that we could not include in the distribution data (Fig. 1A), we noticed the wetlands where we found S. pyriformis were limited to small ponds or bogs locating near the mountain peak or along the ridge (Fig. 1B). That is, the ponds depending on rainfall without inflowing rivers. Because there is no nutrient flowing in, waters in these ponds showed noticeable oligotrophic tendency, i.e., extremely low electric conductivity (Fig. 1A), which gave us some clues on culture.
The most important point of culture for S. pyriformis was keeping the medium lower electric conductivity. We use the KCM medium diluted by 2% with Milli-Q water, and changed medium once a week. A non-photosynthetic cryptophyte, Chilomonas paramecium was selected for food. We selected the food so that it would not itself grow in the culture medium. Growing organisms, like photosynthetic algae, seemed to cause damage to S. pyriformis. Using this culture method, S. pyriformis can be maintained for more than four years (see Table 1). For the organisms not easy to grow in culture, Professor Michael Melkonian mentioned no protist is ‘uncultivable’, there is just human failure30. Here, it just became possible to culture S. pyriformis 120 years after its discovery; however, this method does not always work. S. pyriformis appears to be extremely fragile and disintegrates when any variables are unintentionally altered, that is, the culture is still unstable. When its condition deteriorates, the cells divide unevenly in such a way that a part of the cell is broken. When this happens, the cells become spherical, and the drug drops to the bottom of the dish. It retains this shape for more than a month, but eventually disappears. The doubling time of S. pyriformis remains 3 to 4 weeks, even under favorable conditions (data not shown). We occasionally encountered the blooming of S. pyriformis all over the bottom of the ponds (Fig. 1C). S. pyriformis, therefore, does not seem to be a particularly slow growing species, but our culture method appears to be far from the optimal culture conditions for them. Three S. pyriformis strains used in this study are available from the authors upon request.
Ultrastructure
In this study, we compared the conventional chemical fixation method with the rapid-freezing fixation method for electron microscopic observation. As a result, large vacuoles were observed in the cytoplasm when chemical fixation was used, but not by rapid freezing. Instead, many multi-vesicular bodies were observed in the cytoplasm. The quick-freezing and freeze-substitution method is considered superior in that it can prevent deformation of the intracellular structure compared to chemical fixation31. Therefore, it is possible that the originally existing multi-vesicular bodies were artificially disintegrated by chemical fixation, and the constituent biological membranes fused together, eventually forming large vacuoles. To the authors’ knowledge, no intracellular structure similar to the multi-vesicular body in S. pyriformis has been reported in protists. As multi-vesicular bodies of S. pyriformis could only be observed using the freeze-substitution method, similar granules may also be found in other protists if the same technique is used for electron microscopy. In animals, on the other hand, aggregates of secretory vesicles resembling the multi-vesicular bodies of S. pyriformis are present in cardiac telocytes32. The extracellular vesicles form multi-vesicular structures of about 1 μm in diameter and contain materials for intercellular communication that are involved in cardiac physiology and regeneration. Because S. pyriformis cells often form aggregates at the bottom of the pond, some chemicals may be released from the multi-vesicular body, attracting nearby cells and forming aggregates.
Observation by the freeze-substitution method revealed that the symbiosome membrane was in close contact with the symbiotic chlorella. Furthermore, fluffy projections were observed on the cell wall of the symbiotic chlorella. These characteristics were consistent with those of C. variabilis, which is symbiotic in the cells of P. bursaria9. The only difference was that in S. pyriformis, the symbiotic chlorella cells were scattered in the cytoplasm, whereas the symbiotic Chlorella in P. bursaria were anchored directly below the cell surface.
Storage granules
The iodine in Lugol’s solution selectively binds to α-1, 4-linked glucose found in polysaccharides, such as starch33 and glycogen34. The color stained with Lugol’s solution reflects the type of glucose polymer. Starches with high amylose content stain blue-violet (cf. Fig. 4B), high amylopectin stains red–purple, and glycogen stains reddish brown (Table 2). The granules in the cytoplasm of S. pyriformis stained reddish brown with Lugol’s solution (Fig. 4A), suggesting that these granules are composed of α-1,4-linked glucans with high number of α-1,6-linked branch points, either amylopectin-rich starch or glycogen. The pyrenoid of Chlorella spp. is surrounded by a starch sheath of two large plates35. As shown in Fig. 4F,G, the image contrast formed by electron staining of the starch granule in the chloroplast (arrow) was lost by treatment with Lugol’s solution. Although the detailed mechanism is unknown, this observation suggests that electron-stained heavy metals (osmium, lead, and lanthanoid ions) bound to the granules may have been eliminated by iodine in Lugol’s solution. The cytoplasmic granules of S. pyriformis showed the same staining properties as the starch granules in the chloroplasts of symbiotic chlorella, suggesting that both types of granules share chemical characteristics as polysaccharides.
Alveolates make up one of the most diverse and largest groups of protists. They include three major taxa: dinoflagellates, ciliates, and apicomplexan protozoa. All three alveolate lineages store glucose in an α-1,4-linked glucose chain with α-1, 6 branches. Ciliates are known to synthesize glycogen granules. For example, Tetrahymena has glycogen granules between 35 and 40 nm in diameter, each granule being a collection of small γ-granules of 2–3 nm in size36. Dinoflagellates and apicomplexans typically produce more complex and larger spherical starch particles, usually greater than 1 μm in size37,38. Amylopectin-rich starch and glycogen are very similar polysaccharides, but they differ in granule size and birefringence (Table 2). Starch granules are large, birefringent, and have a high refractive index, but glycogen does not exhibit birefringence, and its granules generally have a size of 300 nm or less. When observed with a polarizing microscope, the starch granules show a Maltese cross pattern. This pattern is derived from the radial arrangement of amylose and amylopectin molecules in granules and is one of the criteria for starch identification. Since the cytoplasmic granules of S. pyriformis are large in size (1–3 μm) and show a typical Maltese cross pattern as shown in Fig. 4E, these granules are likely to be starch granules rich in amylopectin.
Phylogeny of S. pyriformis and its morphology
Relationships of Stentor species were not clearly resolved. BI and ML analyses indicated basal diverging of the S. pyriformis + S. amethystinus clade from others, but NJ analysis did not indicate so (Fig. 5). Recent phylogenetic analyses inclusive of Stentor species also indicated basal diverging of S. amethystinus from the others; however, the monophyly of the others is not highly supported21,22. Therefore, the one thing that can be said is that S. pyriformis is closely related to S. amethystinus.
For the identification of Stentor species, the shape of macronucleus, presence or absence of cortical pigmentation, and symbiotic algae are very important and iconic characteristics8,19. S. pyriformis and S. amethystinus share beaded macronuclei and the presence of symbiotic chlorella (Table S1, Fig. 5B). Pigmentation is present in S. amethystinus, but not in S. pyriformis. Pigmentation is a noticeable characteristic, which tinctures the whole body of Stentor cells. The pigment is thought to function as a defense against predators39. However, the kind of pigment compound depends on the species40, and the relationship between pigment possession and phylogeny is poor (Fig. 5). Of note, colorless vesicles exist in S. pyriformis (Fig. 2D). The short and fat shape is also a common characteristic for S. pyriformis and S. amethystinus, in this genus with many elongated trumpet shape species6,8.
Symbiotic algae in S. pyriformis
Algae-targeted PCR products from whole cells of S. pyriformis were sequenced directly, and clear peaks were obtained for each. This shows that all or nearly all of the algal symbionts in each Stentor cell are unified, regardless of samples under long-term culture or nature. In addition, all symbionts were closely related to C. variabilis (Fig. S3), which has been known as a representative symbiont of P. bursaria (Oligohymenophorea), the model organism of multi-algae retaining protists (MARP41) style symbioses. For the chlorellacean species, the diversity of ITS2 sequence comparisons has often been adopted. For two organisms to compare, ITS2 sequence differences (gaps are counted as a fifth character) usually fall either less than 2% for single species or more than 10% for different species42,43. This characteristic simply encourages a species concept. The ITS2 sequences of S. pyriformis algae differ only by one nucleotide site out of 248 sites from those of P. bursaria algae (Fig. 6A), which strongly suggests the symbiotic chlorella of S. pyriformis are also C. variabilis. Several Stentor species retain coccoid green algae8 (Table S1), but only three algal sequences have been published. Two algal sequences from S. polymorphus belonged to different clades from Chlorellaceae44,45. As for the other algal sequence of S. amethystinus, the symbiont may belong to Chlorellaceae46. This sequence (EF589816) is short (991 bp) and only covers a part of SSU rDNA; therefore, it was not included in our phylogenetic analyses (Fig. S3). The sequence differs from C. variabilis with 10 base changes and 3 indels, indicating that it is not C. variabilis.
Figure 6

Sequence differences of SSU, ITS1, 5.8S and ITS2 rRNA gene (without group I introns) among Chlorella variabilis. “PbS-gt” indicates Paramecium bursaria symbiont genotypes. Genotype 1 includes SAG 211-6, ATCC 50258 (NC64A), NIES-2541, and some other US and Japanese strains. Genotype 2 is the alga of Chinese P. bursaria strain Cs2, and genotype 3 is the alga of Australian P. bursaria strain MRBG1. For further information, see Hoshina et al.53. “SpS” indicates the algal sequence of Stentor pyriformis strains collected from Japan. (A). Different positions. Numerals represent the nucleotide number in aligned sequences (2462 aligned sites). (B). Distance tree of above four types of sequences. (C). E23_2 helix of SSU rRNA structure that includes hemi-CBC at the alignment position 656. (D). Deformation of ITS1 Helix 1 associated with the mutations including several nucleotide insertions.

Full size image

In the case of P. bursaria-C. variabilis symbiosis, C. variabilis has been shown to be vastly different from other free-living species. C. variabilis demands organic nitrogen compounds47 and leaks nearly half of the photosynthate to outside algal cells48,49. Furthermore, they are sensitive to the C. variabilis virus (CvV; so-called ‘NC64A virus’), which is abundant in natural freshwater50,51,52. Therefore, C. variabilis should be considered an already evolved species that is unable to survive without the protection of the host cell53.
Four C. variabilis rDNA sequences obtained from S. pyriformis were identical, with the exception of a nucleotide position in the S1512 intron. Here, the regions without group I introns, i.e., SSU, ITS1, 5.8S, and ITS2 rDNA, are compared among C. variabilis sequences of S. pyriformis and of P. bursaria. Several published sequences cover the above SSU-ITS region, of which varieties are shown as P. bursaria symbiont genotype (PbS-gt) 1 to 3 (Fig. 6A). Due to the small number of sequences, it is still unknown whether these genotypes depend on (or are related to) their living regions. Genotype 1 was from USA and Japan, genotype 2 was from China, and genotype 3 was from Australia. All available sequences for S. pyriformis symbionts were obtained in this study, and they were all from Japan. As a result, all sequences of S. pyriformis symbionts were aggregated into a single genotype SpS, which was distantly related to all P. bursaria symbionts, including those from Japan (Fig. 6B). Five variable sites are found in SSU rDNA among C. variabilis genotypes, of which four are concentrated to that of the symbionts of S. pyriformis (SpS) (Fig. 6A). C/T substitution at alignment position 656 will be a hemi-compensatory base change (hemi-CBC) at the E23_2 helix of SSU rRNA structure (Fig. 6C), whereas the other four sites are at single strand regions (data not shown). Mutations (1821–1828) including comparatively large indels were seen in ITS1 region (Fig. 6A). It was found that all these mutations are assembled in helix 1 (for chlorellacean ITS1 structure, see Bock et al.54,55). Thermodynamic analysis via Mfold56,57 predicted that PbS sequences form linear helix 1 similar to the other chlorellacean species, but SpS sequences including the additional nucleotides may form a dichotomous branching of helix 1 (Fig. 6D).
The group I introns inserted in SSU rDNA of S. pyriformis symbionts are identical to those of P. bursaria symbionts28,58 in terms of numbers (three introns) and insertion sites (S943, S1367 and S1512). The sequences of S943 and S1512 introns are matched more than 99%. However, with respect to the S1367 intron, a large length gap was found (168 nucleotides) at the tip of P8 (Fig. S4). This section has been indicated as a homing endonuclease gene remnant28, and those of S. pyriformis symbionts are presumed to be a more degenerated form than those of P. bursaria symbionts.
At any rate, the symbiotic algae of S. pyriformis were found to be C. variabilis. Because S. pyriformis never lost the symbiotic algae in four years of culture, and all four algae had nearly identical genetic characteristics, the symbiotic relationships between S. pyriformis and C. variabilis can be regarded as stable, or permanent. Although S. pyriformis and P. bursaria share C. variabilis as their endosymbionts, considering the genetic differences depending on their host species, the sharing event has not happened recently. Symbiont sharing among various host species has also been known for some ciliates41,59 (Carolibrandtia ciliaticola in Fig. S3), and a script to spread a particular algal symbiont has been suggested41. Given the physiological characters of C. variabilis (mentioned above), this algal species might be an ideal algal symbiont, and it will be no surprise if the other protists also retained C. variabilis as their algal partners. Research on the symbiotic algae that other Stentor spp. have and on host and regional dependencies are awaited.
Adaptation of S. pyriformis to oligotrophic environment in highland marsh
In Japan, S. pyriformis lives only in alpine ponds (Fig. 1), where the winter is cold, and the surface of the pond is always covered with ice. The water in these ponds has low electrical conductivity (~ 10 μS/cm), and there are few living organisms except S. pyriformis, meaning that only little food is available in wintertime. The reason this ciliate is rich in stored carbohydrate granules may be due to its need for nutrients to survive such harsh winter environments.
Preliminary studies suggest that many protists, especially ciliates, may make starch. Large amounts of cytoplasmic granules that show a Maltese cross were observed in chlorella-bearing ciliates such as P. bursaria, while only a small amount of such granules was observed in Euplotes aediculatus, Paramecium caudatum, Blepharisma japonicum, and Tetrahymena pyriformis. Protists with symbiotic algae seem to produce particularly large amounts of stored carbohydrate granules in the cytoplasm, but the mechanism of starch synthesis may be widely shared by ciliates.
P. bursaria has been shown to be more resistant to starvation conditions than the aposymbiotic strain of the same species13. Under food-deprived conditions, P. bursaria was interpreted to have survived by digesting symbiotic algae. Resting cyst formation and cannibalism are known as other strategies for protozoans to survive starvation conditions60. This study suggests that the use of carbohydrate granules stored in cells may be another possible strategy for ciliates to survive harsh environments such as highland oligotrophic bogs. More

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All experimental procedures were approved by the University of Toronto animal care committee (Animal Use Protocol number 20012112) and conformed to guidelines prescribed by the Canadian Council on Animal Care.
Animal capture and husbandry
Wild male ruby-throated hummingbirds (Archilochus colubris; (n = 23); mass range during experimental period: 2.59 g to 4.52 g), were caught on the University of Toronto Scarborough Campus (({43.7838}^{circ }hbox {N}), ({79.1875}^{circ }hbox {W})) or the University of Western Ontario campus (({43.0096}^{circ }hbox {N}), ({81.2737}^{circ }hbox {W})) using box traps modified with hook-and-loop fastener tape on a drop door containing hummingbird feeders. Birds were trapped between 06:00 h and 12:00 h during the months of May through September of 2017, 2018, and 2019. Pilot trials were conducted in 03/2018. Birds in the pilot study were on wintering/migratory seasonality with a 12 h daylight schedule. Subsequent trials were conducted between 04/2019 and 01/2020. In 04/2019, birds were under breeding seasonality (14 h daylight) and in 01/2020, birds were under wintering/migratory seasonality (12 h daylight) during experimental trials. The daylight schedule approximated the photoperiod encountered as part of annual migrations to Central America and back. Upon capture, hummingbirds were quickly transported to metal EuroCages (({50.8 times 91.5 times 53.7},hbox {cm}) ((hbox {L}times hbox {W}times hbox {H}))) at the animal care facility where they were housed individually and acclimated to feed from syringe feeders. Birds were provided an 18 % (w/v) Nektar Plus (Guenter Enderle, Tarpon Springs, FL, USA) solution (henceforth referred to as maintenance diet), which was consumed ad libitum, and syringes were replaced daily (range of average consumption of daily maintenance diet during study period was 5.4 mL13.2 mL).
Experimental design
Birds drank solutions of imidacloprid (IMI; Sigma-Aldrich Cat. No. 37894) dissolved in a 20% w/v sucrose solution and were randomly assigned to either control (({0.0},upmu hbox {g g}^{-1}cdot)BW), low (({1.0}upmu hbox {g g}^{-1})), middle (({2.0}upmu hbox {g g}^{-1})), or high dose (({2.5}upmu hbox {g g}^{-1})) groups (n = 7, 4, 8, 4, respectively). Stock solution concentrations were analytically confirmed (low: ({0.32},hbox {gL}^{-1}), middle: ({0.59},hbox {gL}^{-1}), high: ({0.78},hbox {gL}^{-1})) such that a 3 g bird dosed with ({10},upmu hbox {L}) of solution would receive the dosage rate corresponding to either the low, middle or high dose. The volume of imidacloprid stock solution used for dosage was adjusted on a body weight (BW) basis, pipetting from the stock solution into a new nectar syringe and drawing up to a final volume of ({50},upmu hbox {L}) with 20% w/v sucrose solution, ensuring that birds received the same dosage rate throughout the trial. Birds were deprived of their regular nectar solution for 10 min to 15 min consumed the entire small-volume dosing solution within 10 min of being offered the solution. The dose was considered to be delivered when there was no visible solution remaining in the transparent syringe.
Doses were established within a range spanning expected exposure in a bird drinking ({10},hbox {mLd}^{-1}) from contaminated flowers10 up to 10 % of the LD50 in canaries61 (Serinus canaria, LD50: ({25},upmu hbox {g g}^{-1}) to 50 (upmu hbox {g g}^{-1})), similarly small birds with fast metabolic rates to target a sub-lethal concentration expected to produce toxic effects32. When energy demands are high, hummingbirds may consume over three times their body weight in nectar63, therefore ({10},hbox {mLd}^{-1}) is a probable figure for contaminated nectar consumption. Pooled blueberry flower samples collected about 1 year after treatment with imidacloprid contained the neonicotinoids at a concentration of ({5.16},hbox {ng g}^{-1})10. We extrapolated our very low and low dose concentrations based on these data. We stipulate that given the flower sample is a pooled sample, it was collected from flowers long after treatment, and there are different regulations on pesticide use within the ruby-throated hummingbird’s range, these doses were environmentally relevant.
We tested multiple intermediate doses which allowed us to explore dose-response relationships in observed effects64. Pilot experiment data with control, very low (({0.2},upmu hbox {g g}^{-1})), or high dose (({2.5},upmu hbox {g g}^{-1})) (n = 3 per group) are included for cholinesterase activity and toxicokinetic elimination analyses. Other metrics including behaviour and energy expenditure were not included from the pilot study due to differences in data collection protocols and are not strictly comparable. Behavioural data collection, cloacal fluid (CF) collection, and respirometry occurred over 6 days, where pre-dose data were collected for each animal on days 1 through 3, and dosing occurred once per day at 11:00 on days 4 through 6. Body weight measurements were taken daily at 10:00. The body weights of birds on the first day of experimentation ranged from 2.70 g to 4.52 g. For simplicity, 11:00 on days 1-6 is referred to as Dose Time (DT). Terminal sampling and tissue collection occurred 24 h after the third dose was administered. Birds were sacrificed by decapitation following isoflurane overdose, and whole blood, flight muscle, liver, brain, and heart tissues were rapidly excised, flash frozen in liquid nitrogen, and stored at ({-80},^{circ }hbox {C}) until downstream analysis, except in the case of blood which was immediately used for blood smear preparation.
Figure 3

Daily experimental timeline for days 1 through 6 of trials where on days 1 through 3, a control solution (20% w/v sucrose solution) is given in all groups and on days 4 through 6, dosing solutions were administered. Times of data collection are shown relative to Dose Time (DT). Terminal tissue sampling occurred on day 7 at DT, 24 h after the final dose was administered.

Full size image

Respirometry
Oxygen consumption and carbon dioxide production rates were measured using open-flow chamber respirometry65. Airflow through three metabolic chambers and one empty reference chamber was maintained at a rate of ({300},hbox {mL min}^{-1}). Excurrent air from the chambers was sub-sampled at ({100},hbox {mL min}^{-1}) sequentially starting with the reference chamber at using a Turbofox-5 (Sable Systems International Las Vegas, NV, USA). Sub-sampled air was passed through a water vapour pressure analyzer, a drying column (Indicating Drierite, W.A. Hammond Drierite, Xenia, Ohio, USA), carbon dioxide meter, and finally an oxygen analyzer (Turbofox-5, Sable Systems International). The oxygen and carbon dioxide analyzers were calibrated according to manufacturer instructions using well-mixed ambient air for the oxygen analyzer, and zero and (0.25 ,%hbox {CO}_{2}) reference gases for the (hbox {CO}_2) analyzer. Respirometry data were recorded at a frequency of 1 Hz using Expedata software (v. 1.84, Sable Systems) for 5 min while sampling from the empty reference chamber, followed by three 7 min recording periods from each of the chambers holding a bird. After this 26 min period, sub-sampling was resumed from the reference chamber for another 5 min followed by another 7 min sub-sampling period from experimental chambers. A final 5 min sampling of the reference chamber concluded the respirometry data collection, and birds were returned to the cloacal fluid collection chambers approximately 60 min after initially being placed in respirometry chambers.
Behavioural data collection and processing
Video recordings of birds were collected for 2 h, starting 4 h after DT (15:00–17:00). At the start of the recording period, birds were returned to their home cages where they could feed ad libitum by hovering and tracking a syringe on a 10 cm arm oscillating through a ({90}^{circ }) range along a lateral arc at a speed of 15 RPM. Video recordings were analyzed for time spent in flight, subdivided into foraging and non-foraging flights. Foraging flights were defined as flights where the bird contacted the hover feeder with their bill. Total consumption of the maintenance diet over this 2 h period was recorded.
Heterophil/lymphocyte ratios
Approximately ({2},upmu hbox {L}) of blood was collected for blood smear preparation immediately following sacrifice. After smearing, slides were left to air dry for a minimum of 3 h before fixing with 100 % methanol and staining with Giemsa–Wright solution (Fisher Scientific Cat. No. 123869). Slides were stained by immersion in eosinophilic dye (5times 1,hbox {s}) followed by (5times {1},hbox {s}) in basophilic dye.
Cholinesterase activity assay
Brain and muscle tissues were homogenized using a sonic dismembrator ((hbox {Fisherbrand}^{mathrm{TM}}) Model 120 Sonic Dismembrator) 1:10 w:v with ice-cold 0.1 M potassium phosphate buffer (pH 7.2). Samples were centrifuged at 10,000 RPM in a Beckman Coulter microfuge 22R centrifuge held at ({4},^{circ }hbox {C}) for 5 min. Total protein concentrations in tissue homogenates were determined by the Bradford assay (Sigma-Aldrich Cat. No. B6916). Cholinesterase activity was measured by the Ellman method adapted for a microplate reader (BioTek Synergy HT)66. Optimal assay conditions were 0.1 M potassium phosphate buffer (pH 7.2), 0.48 mM acetylcholine, 0.64 mM DTNB (Sigma-Aldrich Cat. No. D8130), 1.1 mM sodium bicarbonate. Assays were initiated through the addition of acetylcholine (Sigma-Aldrich, Cat. No. 01480) in a total volume of ({300},upmu hbox {L}). Absorbance was read at 412 nm every 2.5 min for 10 min.
Cloacal fluid
Collection
Cloacal fluid was collected for 1 h at 3 time points each day according to one of two schedules: starting (1) 1 h, 6 h, and 23 h, or (2) 2.5 h, 6.5 h, and 23 h after DT. Cloacal fluid was collected according to schedule (1) in pilot experiments, and (2) in the subsequent trials. A watch glass was placed beneath birds perching in 10 cm W (times) 12 cm H glass cylinder enclosures stopped with 19-gauge galvanized 1 cm hardware mesh openings in order to obtain cloacal fluid. To encourage greater cloacal fluid production, and to simulate the regular feeding behaviour of wild birds, individuals fed ad libitum from a syringe containing a 20% (w/v) sucrose solutions every 5 min to 10 min for the duration of cloacal fluid collection, which took place over 1 h as described under Sect. 4.2. After the collection period, cloacal fluid samples were stored at ({-20},^{circ }hbox {C}) until pooling and refreezing prior to chemical analysis.
Chemical analyses
Cloacal fluid samples and dosing solutions were analyzed for IMI by HPLC-ESI-MS/MS by Laboratory Services, NWRC (National Wildlife Research Centre, Ottawa, ON, Canada). Cloacal fluid samples were pooled by time point across dosing days by individual to reach the necessary minimum volume of ({100},upmu hbox {L}).
Cloacal fluid sample pools from 2018 trials were thawed at room temperature. Each pool was diluted 4 (times) with DI water (({25},upmu hbox {L}) cloacal fluid + ({75},upmu hbox {L}) DI water). The resulting ({100},upmu hbox {L}) diluted samples were then spiked with ({100},upmu hbox {L}) of internal standard (IS) solution. Spiked samples were filtered directly into ({300},upmu hbox {L}) glass inserts using 4 mm PVDF ({0.45},upmu text {m}) Millex filters and ({50},upmu hbox {L}) aliquots were injected. For the 2018 analyses, the minimum detection limit (MDL) and minimum reporting limit (MRL) were ({0.204},hbox {ng}hbox { mL}^{-1}) and ({0.616},hbox {ng}hbox { mL}^{-1}) respectively.
Cloacal fluid sample pools from 2019 trials were thawed at room temperature and ({50},upmu hbox {L}) of IS solution was added to (200,upmu text {L}) of pooled cloacal fluid. In cases where the sample volume was too small, volumes were adjusted: ({100},upmu hbox {L}) cloacal fluid + ({25},upmu hbox {L}) IS or ({80},upmu hbox {L}) cloacal fluid + ({20},upmu hbox {L}) IS as required. In these cases, duplicate injections of ({50},upmu hbox {L}) were not possible. All samples were filtered with 4 mm PVDF ({0.45},upmu text {m}) Millex filters prior to injection. For the 2019 analysis, the MDL and MRL were ({0.051},hbox {ng}hbox { mL}^{-1}) and ({0.154},hbox {ng}hbox { mL}^{-1}) respectively.
Cloacal fluid sample pools and dosing solutions were analyzed according to modifications to the methods of Main et al.9. Briefly, IMI in a cloacal fluid or DI water matrix was quantified by the internal standard method using the API5000 Triple Quadropole Mass Spectrometer (AB Sciex) and the TurboSpray ion source in positive polarity. The calibration curve was constructed from 8 concentrations ranging from ({0.1},hbox {ng}hbox { mL}^{-1}) to ({20},hbox {ng}hbox { mL}^{-1}) yielding an R greater than 0.995 (linear regression, no weighting). Injection cross-contamination was monitored by injecting solvent blanks (water:acetonitrile 80:20) before and after each set of samples. Contamination was also monitored by using a DI water sample blank spiked at ({20},hbox {ng}hbox { mL}^{-1}) IMI. In all cases, no IMI above MDLs was detected. Method precision was evaluated by duplicate injections and/or duplicate dilutions: the RPDs (relative percent differences) were all less than 15 %, demonstrating good method precision. Method accuracy was evaluated by analyzing a ({20},hbox {ng}hbox { mL}^{-1}) QC spike per set: the recoveries ranged between 96 % and 106 %, demonstrating good method accuracy.
Statistical analyses
All statistical analyses were conducted in R version 3.5.267. Birds exhibiting weight loss outside the lower bound of the 95 % confidence interval (CI) of 20 % over the study period ((n=3)) were omitted and data were reanalyzed. Birds exhibiting extreme weight loss across the pre-dose and post-dose conditions were in the control group ((n=2)) and the low dose group ((n=1)) suggesting a adverse response to the experimental period rather than the treatment itself. Data are presented as mean ± standard error. Significance ((p More

Focal species
The Lesser Prairie-Chicken is a medium-sized grouse endemic to, broadly, the shortgrass prairie ecosystem of the south-central United States, where it is found only in southwestern Colorado, western Kansas, northwestern Oklahoma, the Texas panhandle, and eastern New Mexico. As with almost all open-country grouse of temperate environments, the Lesser Prairie-Chicken forms leks at which a cluster of males (in this species, usually 5–12 individuals) display vigorously and female visit to assess males with an intent to secure sperm to fertilize her eggs, which she will lay and raise without male help. Outside of male lekking (mid-March to mid-May) and female nesting (late April to early July), birds congregate is small flocks to forage, at times on grain remains in farmed fields but typically, as through the rest of the life cycle, restricting themselves to native prairie. Accordingly, this species has three distinct aspects of habitat selection: general occurrence, lek placement, and nest placement.
Data
Lesser Prairie-Chicken were tracked at two study sites, one in Roosevelt County in east-central New Mexico, U.S.A., the other in Beaver, Harper, and Ellis Counties in northwestern Oklahoma, U.S.A. Birds tagged with VHF transmitters were tracked from April 1999–March 2006 in New Mexico and from March 1999–July 2013 in Oklahoma11,12,13,14. Study periods differed chiefly because of funding, which for New Mexico was insufficient after 2006. The study sites differ markedly in land tenure history. Parcel size in New Mexico averages 1300 ha versus 180 ha in Oklahoma11. The difference largely stems from settlement patterns over the past two centuries. New Mexico was part of the Spanish land grant system, which tended to yield huge parcels. In our study area, parcels approach 8 km2 ( > 1900 acres). By contrast, during the “land rush” era of the late 19th Century most of northwestern Oklahoma was parceled into 65-ha (160-acre) plots as part of the United States’ Homestead Act. Smaller parcels translate to a higher density of roads, fences, buildings, and powerlines11.
Radiotracking typically yielded a triplet of coordinate readings, from which we had to triangulate a grouse’s location. We estimated latitude and longitude using a maximum likelihood estimator (MLE), although it some cases the MLE algorithm failed to converge. If it failed, we instead used the Andrew and Huber methods15. R code for the estimation procedure can be found at https://github.com/henry-dang/triangulation/blob/master/lenth_triang.R.
From these data we used kernel density methods (R package ks16) to estimate annual home ranges (235 in New Mexico, 263 in Oklahoma). Tracking data included lek (12 in New Mexico, 23 in Oklahoma) and nest (122 in New Mexico, 128 Oklahoma) locations. For home range centroids, the outer contour of home ranges, leks, and nests, we estimated distance to seven anthropogenic features: roads (highways, primary, and secondary roads only; small farm roads or one-lane gravel roads were excluded), powerlines (overhead only, with buried or trunk lines excluded; https://hifld-geoplatform.opendata.arcgis.com/datasets/electric-power-transmission-lines), oil wells, gas wells (for both types of wells, http://www.occeweb.com and http://www.emnrd.state.nm.us/ocd), outbuildings (barns, grain silos, poultry houses, and similar large structures; chiefly the TIGER database), and fences (Bureau of Land Management) in both states, plus private houses in New Mexico and railroad tracks in Oklahoma. We placed 2000 random points on each study area to estimate distances to each of these same anthropogenic features, which provided an estimate of feature density on the landscape.
Analyses
The initial step was to estimate the probability of a grouse occurring a certain distance from a feature. We treated New Mexico and Oklahoma data separately, giving us a replicate assessment because these populations have been isolated from each other for  > 100 years17 and, as noted above, land tenure history differs strikingly between the states11. We estimated probabilities of grouse occurrence, πi, via a Bayesian model with binomial likelihood and flat prior (i.e., no assumption of the central tendency of occurrence probability at a given distance from a feature):
yi ~ binomial (πi, n) with yi the cumulative count of grouse at distance i (i.e., the data) and n the total number of home ranges, leks, or nests. Distances, i, were binned to the smallest extent possible, from 10 to 100 m, to allow the Markov chain Monte Carlo (MCMC) algorithm to converge in a reasonable number of iterations (e.g.,  More

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