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All statistical analyses were performed through R version 4.1.050. Besides the explicitly mentioned packages, the R packages cowplot51, data.table52, dplyr53, ggplot254, itsadug55, purrr56, raster57, sf58, sfheaders59, tibble60 and tidyr61 were key for data handling, data analysis, and plotting. Posterior distributions were summarised through means and credible intervals (CIs). CIs are the highest density intervals, calculated through the package bayestestR62. To summarise multiple posterior distributions, 5000 Monte Carlo simulations were used.Study regionThe study included data from the whole of Switzerland. As an observation unit for records, we chose 1 × 1 km squares (henceforth squares). Switzerland covers 41,285 km2, spanning a large gradient in elevation, climate and land use. It can be divided into five coarse biogeographic regions based on floristic and faunistic distributions and on institutional borders of municipalities63 (Fig. 1b). The Jura is a mountainous but agricultural landscape in the northwest (~4200 km2, 300–1600 m asl; annual mean temperature: ~9.4 °C, annual precipitation: ~1100 mm (gridded climate data here and in the following from MeteoSwiss (https://www.meteoswiss.admin.ch), average 1980–2020, at sites ~500 m asl.)). The Jura is separated from the Alps by the Plateau, which is the lowland region spanning from the southwest to the northeast (~11,300 km2, 250–1400 m asl, mostly below 1000 m asl; ~9.5 °C, ~1100 mm). It is the most densely populated region with most intensive agricultural use. For the Alps, three regions can be distinguished. The Northern Alps (~10,700 km2, 350–4000 m asl; ~9.2 °C, ~1400 mm), which entail the area from the lower Prealps, which are rather densely populated and largely used agriculturally, up to the northern alpine mountain range. The Central Alps (~11,300 km2, 450–4600 m asl; ~9.5 °C, ~800 mm) comprise of the highest mountain ranges in Switzerland and the inner alpine valleys characterised by more continental climate (i.e., lower precipitation). Intensive agricultural land use is concentrated in the lower elevations and agriculture in higher elevations is mostly restricted to grassland areas used for summer grazing. The Southern Alps (~3800 km2, 200–3800 m asl; ~10.4 °C, 1700 mm) range from the southern alpine mountain range down to the lowest elevations of Switzerland and are clearly distinguished from the other regions climatically, as they are influenced by Mediterranean climate, resulting in, e.g., milder winters. Besides differences between biogeographic regions, climate, land use and changes therein vary greatly between different elevations (Supplementary Fig. S9). To account for these differences, we split the regions in two elevation classes at the level of squares. All squares with a mean elevation of less than 1000 m asl were assigned to the low elevation, whereas squares above 1000 m asl were assigned to the high elevation (no squares in the Plateau fell in the high elevation). This resulted in nine bioclimatic zones (Fig. 1b), for which separate species trends were estimated in the subsequent analyses. The threshold of 1000 m asl enabled a meaningful distinction based on the studied drivers (climate and land-use change) and was also determined by the availability of records data (high coverage in all nine bioclimatic zones).Species detection dataWe extracted records of butterflies (refers here to Papilionoidea as well as Zygaenidae moths), grasshoppers (refers here to all Orthoptera) and dragonflies (refers here to all Odonata) from the database curated by info fauna (The Swiss Faunistic Records Centre; metadata available from the GBIF database at https://doi.org/10.15468/atyl1j, https://doi.org/10.15468/bcthst, https://doi.org/10.15468/fcxtjg). This database unites faunistic records made in Switzerland from various sources including both records by private persons and from projects such as research projects, Red-List inventories or checks of revitalisation measures. Only records with a sufficient precision, both temporally (day of recording) and spatially (place of recording known to the precision of 1 km2 or less), were used for analyses. Besides temporal and spatial information, information on the observer and the project (if any) was obtained for each record. All records made by a person/project on a day in a square were attributed to one visit, which was later used as replication unit to model the observation process (see below).We included records from the focal time range 1980–2020. Additionally, we included records from 1970–1979 for butterflies in occupancy-detection models to increase the robustness of mean occupancy estimates. We excluded the mean occupancy estimates for these additional years from further analyses to cover the same period for all groups. Prior to analyses, following the approach in ref. 26, we excluded observations of non-adult stages and observations from squares that only were visited in 1 year of the studied period, because these would not contain any information on change between years64. This resulted in 18,018 squares (15,248 for butterflies, 9870 for grasshoppers, 5188 for dragonflies) and 1,448,134 records (879,207 butterflies, 272,863 grasshoppers, 296,064 dragonflies) that we included in the analyses (Supplementary Fig. S2). The three datasets for the different groups were treated separately for occupancy-detection modelling, following the same procedures for all three groups. To determine detections and non-detections for each species and visit, which could then be used for occupancy-detection modelling, we only included visits that (a) did not originate from a project, which had a restricted taxonomic focus not including the focal species, (b) were not below the 5% quantile or above the 95% quantile of the day of the year at which the focal species has been recorded26 and (c) were from a bioclimatic zone, from which the focal species was recorded at least once.Occupancy-detection modelsWe used occupancy-detection models65,66 to estimate annual mean occupancy of squares for the whole of Switzerland and for the nine bioclimatic zones for each species (i.e., mean number of squares occupied by a species), mostly following the approach in ref. 26. We fitted a separate model for each species, based on different datasets for the three groups. We included only species that were recorded in any square in at least 25% of all analysed years. Occupancy-detection models are hierarchical models in which two interconnected processes are modelled jointly, one of which describes occurrence probability (ecological process; used to infer mean occupancy), whereas the other describes detection probability (observation process)65. The two processes are modelled through logistic regression models. The occupancy model estimates occurrence probability for all square and year combinations, whereas the observation model estimates the probability that a species has been detected by an observer during a visit. More formally, each square i in the year t has the latent occupancy status zi,t, which may be either 1 (present) or 0 (absent). zi,t depends on the occurrence probability ψi,t as follows$${z}_{i,t}sim {{{mbox{Bern}}}}left({psi }_{i,t}right)$$
(1)
The occupancy status is linked to the detection/non-detection data yi,t,j at square i in year t at visit j as$${y}_{i,t,, j}{{|}}{z}_{i,t}sim {mathrm {Bern}}({z}_{i,t}{p}_{i,t,j})$$
(2)
where pi,t,j is the detection probability.The regression model for occurrence probability (occupancy model) looked as follows$${{mbox{logit}}}({psi }_{i,t})={mu }_{o}+{beta }_{o1}{{{{{rm{elevatio}}}}}}{{{{{{rm{n}}}}}}}_{i}+{beta }_{o2}{{{{{rm{elevatio}}}}}}{{{{{{rm{n}}}}}}}_{i}^{2}+{alpha }_{o1,i}+{alpha }_{o2,i}+{gamma }_{r(i),t}$$
(3)
with μo being the global intercept, elevationi being the scaled elevation above sea level and αo1,i, αo2,i and γr(i),t being the random effects for fine biogeographic region (12 levels, Supplementary Fig. S10; these were again defined based on floristic and faunistic distributions and followed institutional borders63), square and year. The random effects for fine biogeographic region and square were modelled as follows:$${alpha }_{o1}sim {{{{{rm{Normal}}}}}}left(0,{sigma }_{o1}right)$$
(4)
and$${alpha }_{o2}sim {{{{{rm{Normal}}}}}}left(0,{sigma }_{o2}right)$$
(5)
The random effect of the year was implemented with separate random walks per zone following ref. 67, which allowed the effect to vary between the nine bioclimatic zones, while accounting for dependencies among consecutive years. Conceptually, in random walks, the effect of 1 year is dependent on the previous year’s effect, resulting in trajectories with less sudden changes between consecutive years. This was implemented as follows:$${gamma }_{r,t}sim left{begin{array}{c}{{{{{rm{Normal}}}}}}left(0,{1.5}^{2}right){{{{rm{for}}}}},t=1\ {{{{{rm{Normal}}}}}}left({gamma }_{r,t-1},{sigma }_{gamma r}^{2}right){{{{rm{for}}}}},t , > ,1end{array}right.$$
(6)
with$${sigma }_{gamma r}sim {{mbox{Cauchy}}}left(0,1right)$$
(7)
The regression model for detection probability (observation model) looked as follows$${{{{rm{logit}}}}}({p}_{i,t,j}) =, {mu }_{d}+{beta }_{d1}{{{{{rm{yda}}}}}}{{{{{{rm{y}}}}}}}_{j}+{beta }_{d2}{{{{{rm{yda}}}}}}{{{{{{rm{y}}}}}}}_{j}^{2}+{beta }_{d3}{{{{{rm{shortlis}}}}}}{{{{{{rm{t}}}}}}}_{j}+{beta }_{d4}{{{{{rm{longlis}}}}}}{{{{{{rm{t}}}}}}}_{j} \ quad+ {beta }_{d5}{{{{{rm{exper}}}}}}{{{{{{rm{t}}}}}}}_{j}+{beta }_{d6}{{{{{rm{projec}}}}}}{{{{{{rm{t}}}}}}}_{j}+{beta }_{d7}{{{{{rm{targeted}}}}}}_{{{{{rm{projec}}}}}}{{{{{{rm{t}}}}}}}_{j} \ quad+ {beta }_{d8}{{{{{rm{redlis}}}}}}{{{{{{rm{t}}}}}}}_{j}+{alpha }_{d1,t}$$
(8)
where μd is the global intercept, ydayj is the scaled day of the year of visit j, shortlistj and longlistj are dummies of a three-level factor denoting the number of species recorded during the visit (1; 2–3; >3), and expertj, projectj, targeted_projectj and redlistj are dummies of a five-level factor denoting the source of the data. The source might either be a common naturalist observation (reference level), an observation by an expert naturalist, an observation made during a not further specified project, an observation made in a project targeted at the focal species or an observation made during a Red-List inventory. An expert naturalist was defined as an observer that contributed a significant number of records, which was defined as the upper 2.5% quantile of all observers arranged by their total number of records, and that made at least one visit with an exceptionally long species list, which was defined as a visit in the upper 2.5% quantile of all visits arranged by the number of records. The proportions of records originating from these different sources changed across years, but change was not unidirectional and differed among the investigated groups (Supplementary Fig. S11), such that accounting for data source in the model should suffice to yield reliable estimates of occupancy trends. αd1,t is a random effect for year, which was modelled as$${alpha }_{d1}sim {{{{{rm{Normal}}}}}}left(0,{sigma }_{d1}right)$$
(9)
The occupancy and observation models were fitted jointly in Stan through the interface CmdStanR68. Four Markov chain Monte Carlo chains with 2000 iterations each, including 1000 warm-up iterations, were used. Priors of the model parameters are specified in Supplementary Table S5. For the prior distribution of global intercepts, a standard deviation of 1.5 was chosen to not overweight the extreme values on the probability scale. To ensure that chains mixed well, Rhat statistics for annual mean occupancy estimates were calculated through the package rstan69. For Switzerland-wide annual estimates (n = 18,140), 98.0% of values met the standard threshold of 1.1 (99.9% of values More

According to the information that exists so far regarding reproduction in echinoderms, this is the first work in which the occurrence of trioecy in sea urchins is reported. This is also the first report of trioecy among members of the phylum Echinodermata, one of the most widespread taxa, both latitudinally and bathymetrically. Our results show that trioecy in this population of T. roseus is temporally stable, since the three sexes were observed together throughout the year in each month of sampling. Hermaphroditic individuals also presented the same gametogenic developmental pattern as females and males. Finally, during the spawning period of the population they contributed to the reproductive process by releasing mature gametes, which evidenced their full functionality within the studied population.We were unable to obtain evidence of self-fertilization in the studied hermaphrodites; but self- fertilization in the gonads and gonadal ducts of a hermaphrodite individual of Echinocardium cordatum was recorded in 193543. However, the embryos produced did not complete development successfully, probably due to the premature fertilization within the gonad43. Also, the cases of fully functional hermaphrodites of Arbacia punctulata have been reported44,45. The gametes of the hermaphrodites were fertilized as soon as they were released into seawater and the development of self-fertilized eggs was absolutely normal in time and morphology. After nine days, typical pluteus larvae were obtained and both the eggs and sperm of the hermaphrodites functioned ordinarily with gametes from other males and females.Therefore, we consider that there are no reasons to think that in the case of Toxopneustes roseus hermaphrodites cannot carry out self-fertilization. According to the analysis of the gonad developmental stages, their gametes were released into seawater. Theoretically, those gametes would be able to follow the normal course of fertilization, interacting among them and with gametes of females and males.The trioecic condition has been recorded so far only in some animals, such as a few nematode species and a hydra9,10,14,46,47,48. In marine invertebrates, it has been reported in one anemone under laboratory conditions and in one bivalve mollusk15,16. The coexistence of males, females and hermaphrodites has been considered an evolutionarily transitory state; for example, androdioecy (male / hermaphrodite) in nematodes such as Caenorhabditis elegans is believed to have evolved from dioecy (male / female) through a trioic intermediate. Consequently, it is very difficult to find the ecological or evolutionary causes that lead a species or population to present three sexes simultaneously49.In the species in which trioecy has been studied and monitored, it is noticeable that their populations are subjected to strong environmental stress in situ or under laboratory manipulation50,51,52. For example, some nematodes of the genus Tokorhabditis are extremophilic species that live in the Californian Mono Lake, which is characterized by being hypersaline and exhibiting high levels of arsenic10,50. In the case of Auanema freiburgensis the flexible sex determination and mating system and, consequently, its trioecy can be critical for resilience at the population level in patchy, resource-limited environments49. These results thus demonstrate that life-history, ecology and environment can play defining roles in the development of sexual systems and determine the continued presence of trioecy in the nematode. In the case of Hydra viridissima, it unlike most European species, is a “warm crisis” hydra, since it usually reproduces asexually, but when the temperatures rise to, or are maintained at high levels (≥ 20 °C), it reproduces sexually14,53. In experimental conditions, the population studied essentially behaved as androdioecic and only at the end of the research period, when the temperature was the highest (~ 25 °C), a few females appeared and joined the other existing sexes, thus generating the condition of trioecy14. Trioecy has been identified in another non-described species (e.g., Rhabditis sp. JU1783) isolated from star fruit, although it is closely related to A. rhodensis and A. freiburgensis and likely to belong to the same genus11,12. Little is known about the ecology of Auanema, as A. rhodensis has been isolated from a tick and a beetle, and A. freiburgensis from dung and a rotting plant of the genus Petasites12,47,51.Regarding the sea anemone Aiptasia diaphana, it is mainly found in isolated fouling communities, and no hermaphrodites exist in natural populations that could reproduce asexually or sexually54. However, under laboratory conditions, a single founder individual (asexual clone) produced not only males and females, but also hermaphroditic individuals. In addition, A. diaphana can fertilize within and between cloning lines, producing larval-swimming planules, which could explain the success of the species as an invader of artificial marine substrates. The condition of trioecy was also identified in individuals of this anemone manipulated in the laboratory, to create age-homogeneous populations of asexual propagules (pedal lacerations) and ontogenetic patterns of sexual differentiation were documented15.In the case of the marine bivalve Semimytilus algosus, there was not an obvious explanation for the occurrence of its trioecy, despite the intense analyses of factors such as motility versus a sessile way of life or reproductive density within a population, which could have relevance for gamete interactions16. In many respects, S. algosus is a “typical” marine intertidal mussel, since it is sessile in adulthood, occurs at high densities in wild populations, and has a very large population. S. algosus also co-occurs with other species that are close relatives within the Mytilidae family and have evolved and conserved their dioecy16.Toxopneustes roseus is another typical species of sea urchin, which has a wide latitudinal distribution throughout the tropical eastern Pacific and co-inhabits with other species of sea urchins and echinoderms that have a similar distribution and in which hermaphroditism has not been reported40,55,56,57. Regarding its population density, T. roseus is not considered among the most abundant species in the study area and its densities are relatively low (between 0.04 and 1.2 ind.m2). However, it cannot be considered a rare species in terms of abundance58,59.All of the above makes it difficult to clearly explain the reasons for the occurrence of trioecy in this species; however, certain aspects of its early development are known that could indicate the factors behind the development of this reproductive mating system in the pink sea urchin. In recent experiments carried out with gametes, larvae, and embryos of a population of T. roseus from the same area as our study, it was found that the increase in temperature above the normal values of its habitat has a deleterious effect on the success of early development60. There exists experimental evidence that at an increase of temperature to 32 °C, which is 2 °C above the maximum values registered in the study area, fertilization occurred at a very low percentage. There was also a deleterious effect on embryos, resulting in abnormal development and the lowest percentage of larval survival also occurred at 32 °C60. The same kind of experiments has been performed on other species from the study area, such as the irregular sea urchin Ryncholampas pacificus and the intertidal Echinometra vanbrunti. The deleterious effects on these species were observed only at 34 °C, which was the highest temperature tested (unpublished data). At 32 °C, however, there was no evidence of negative effects in the case on E. vanbrunti, and there was just arrested development, but no abnormalities in the case of R. pacificus. These results indicate that T. roseus is much more sensitive to the rise in temperature than other cohabiting sea urchins, and probably lives near its upper thermal limit. In that context, the continuous ocean warming could threaten the permanence of the species in the study area, since the early stages of development constitute a bottleneck for successful recruitment and later population maintenance in populations that carry out reproduction by means of external fertilization.Within the phylum Echinodermata, when stressful conditions appear in the habitat or the environment becomes hostile, the species can generally resort to asexual reproduction by fission (ophiuroids) or fission and autotomy (holothuroids and asteroids) to increase the abundance of populations in a relatively short time or counteract a threat with numbers61. This does not apply to sea urchins since they are unable to reproduce asexually. The only way for sea urchins to reproduce asexually would be by cloning larvae, but this process would also require that sexual reproduction occurs first62. Therefore, any reproductive strategy that a sea urchin population could develop to respond to drastic changes in their area must involve sexual reproduction. In this regard, in an experimental evolution study with the nematode Caenorhabditis elegans, in which partial selfing, exclusive selfing, and predominant outcrossing were compared, it was evidenced that monoecious populations only have hermaphrodites and, therefore, reproduction is carried out exclusively by self-fertilization. However, in trioic populations that have males, females, and a small number of hermaphrodites, reproduction is predominantly carried out by external crossing49. Also populations that underwent some degree of interbreeding during the evolutionary experiments (trioic and androdioic populations), maintained more genetic diversity than expected solely under genetic drift or under genetic drift and directional selection49. In this sense, it is possible that high levels of interbreeding, such as that which occurs in trioic populations, develop with populations that have sufficient deleterious recessive alleles to avoid extinction, since selection is less efficient to purge them. Trioecy, therefore, becomes an efficient system to select characteristics of the genome that allows a population that only reproduces sexually to adequately cope with significant changes in the environment that could threaten the permanence of the species in that habitat. Interbreeding (gonochorism, self-incompatible hermaphroditism) also favors genetic diversity and offers greater potential to adapt to changing environments63. The costs and advantages of crossing over selfing depend on environmental factors and, therefore, selection may favor transitions between mating systems. Androdioecy, gynodioecy, and trioecy are evolutionarily unstable intermediate strategies, but they offer important systems for testing models of the causes and consequences of the mating system in the evolution of populations63.However, the question remains why T. roseus has developed trioecy, when in the same habitat there are other sea urchins with very similar life-histories that only maintain dioecy. In the case of the bivalve Semimytilus algosus; which presents the same situation as we have with T. roseus, it was proposed that the trioecy of the species may be related to the sex determination mechanism, considering what it is known about the nematodes of the genus Auanema10,16,46. In Auanema, the male versus non-male (hermaphrodite or female) decision is determined genetically (XO for males, and XX for females and hermaphrodites)9,64. The hermaphrodite versus female decision, however, is determined by the environment of the mother. For A. freiburgensis the maternal social environment is determinant, whereas for A. rhodensis it is the age of the mother9,12,51,65. Therefore, in Auanema, environmental sex determination and genetic sex determination interact to produce trioecy.Although there is apparently no clear cause of strong, stressful conditions in the habitat of T. roseus that could threaten the survival of this species, according to the United States Environmental Protection Agency (EPA, 2021), sea surface temperature increased during the twentieth century and continues to rise. From 1901 to 2020, the global temperature rose at an average rate of 0.004 °C per decade, resulting in a total increase of 0.5 °C to date. Additionally, regional studies based on continuous monitoring, which have not yet been published, have shown that between 2002 and 2020 there has been an increase of approximately 1 °C above the historical average of the sea surface temperature in the study area.The foregoing discussion leads us to speculate that the studied population of T. roseus lives at the limit of its thermal tolerance, and the constant increase in ocean temperature due to global warming constitutes a threat to its survival and a constant source of stress for the population. This is because its early-development stages are more vulnerable to high temperature than other sea urchins that live in the same area and its population density is also significantly lower58.Phylogenetically T. roseus belongs to Family Toxopneustidae and although no other species within the genus Toxopneustes has shown hermaphroditism, this condition was reported in Tripneustes gratilla, which belongs to the same family36. Toxopneustids belong to the Order Camarodonta, and almost all the species of sea urchins in which hermaphroditism has been reported belong to this Order except for a couple that belong to the Arbacioida. At the same time, this order is contained in the Superorder Echinacea along with Camarodonta, according to the last exhaustive analysis resolving the position of the clades within Echinoidea66. In this context, theoretically T. roseus at some point underwent the environmental pressure of its early stage living under constantly rising temperatures, along with its low population densities in the study area. Consequently, it was able to develop hermaphroditism and, therefore, trioecy, similarly to what occurred to Hydra viridissima under conditions of extreme high temperature14. We hypothesize that these permanent conditions generate a constant source of strong environmental stress, which is the determining factor that keeps trioecy stable in the species in which it has been studied, and, thus, trioecy remains stable in this population of T. roseus.The mechanism of sex determination in echinoids, as well as in other echinoderms, is still unknown, although the sex ratio, which is generally close to 1:1, suggests that it occurs through sex chromosomes67. It is known that in mammals, sex determination is dictated by the presence or absence of the Y-chromosomal gene SRY. SRY functions as the primary sex-determining gene by activating testis formation, and in its absence, the embryo will form ovaries. SRY only exists in mammals; however it evolved as a duplication of the Sox gene family, which exists in all metazoans68.In vertebrates, Sox genes are involved in sex determination, neurogenesis, skeletonogenesis, eye development, pituitary development, pancreas formation, and neural crest and notochord formation69. In invertebrates, they are involved in processes such as metamorphosis, eye development, neural crest formation, and ectoderm formation70. In the sea urchin Strongylocentrotus purpuratus, SoxB1 was determined to be expressed in the primordial gut during development and is closely related in sequence to Sox genes of the mouse embryo71. An investigation of sex determination was carried out in the sea urchin Strongylocentrotus purpuratus using RNA-seq and quantitative mRNA measurements, but the mechanisms that govern sexual determination of the species could not be clearly established72. However; the results show that the male fate factors Dmrt and SoxH are expressed early and meiosis initiates early. Also, gonad-specific transcripts involved in egg and sperm biology, are first activated before rudiment formation in the larvae of this sea urchin. The study provided additional evidence for the hypothesis that in sea urchins, sex determination occurs genetically72. Another research with the sea cucumber Apostichopus japonicus, which integrated genome-wide association study and analyzes of sex-specific variations evidenced that the species exhibits genetic sexual determination73. Furthermore, analysis of homozygous and heterozygous genotypes of abundant sex-specific SNPs in females and males, confirmed that A.japonicus might have a XX/XY sex determination system73.On the other hand, it has been proposed that a deviation from the 1:1 sex ratio in echinoids could reflect environmental conditions that influence sex determination67. For example, a relatively large proportion of Lytechinus variegatus and Tripneustes ventricosus (as Tripneustes esculentus) hermaphrodites was recorded in southern Florida during an unusually cold winter, suggesting that adverse winter conditions in some way affected sex determination in juveniles74,75. Also relatively large number of Strongylocentrotus purpuratus hermaphrodites was reported in Bahía de Todos los Santos, Mexico, where extreme seasonal fluctuations in temperature (from about 12–24 °C) are recorded76. However, posterior studies did not find a single hermaphrodite of Strongylocentrotus purpuratus in more than 500 individuals analyzed77,78.Considering that sex determination in sea urchins is highly probable to occur genetically and the possibility that the environment may also influence sex determination, we think that in the case of Toxopneustes roseus, genetic sex determination and environmental sex determination are interacting to maintain the condition of trioecy stable. We propose that, especially because the cases in which environmental conditions have assumed to influence sex determination, extreme temperatures are invoked as the main affecting factor. However, more detailed studies are needed in terms of sexual determination and experimental evolution to be able to verify our assumption.In general, the efforts that have been made to explain the evolution of the sexes and the origin of hermaphroditism and trioecy are still scarce, and critical questions remain to be answered. The case of trioecy detected in T. roseus may constitute an important model to seek these answers about the evolution of sexual systems and the environmental mechanisms that trigger trioecy in marine macroinvertebrates and, in particular, in echinoderms. More

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