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93.
BioSample of Deltaproteobacteria bacterium MAG_22204_dsfv_001. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911675 (2020).

94.
BioSample of Gammaproteobacteria bacterium MAG_00150_gam_010. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911649 (2020).

95.
BioSample of Gammaproteobacteria bacterium MAG_00160_gam_009. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911650 (2020).

96.
BioSample of Gammaproteobacteria bacterium MAG_00172_gam_018. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911651 (2020).

97.
BioSample of Gammaproteobacteria bacterium MAG_00188_gam_006. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911652 (2020).

98.
BioSample of Gammaproteobacteria bacterium MAG_00212_gam_1. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911653 (2020).

99.
BioSample of Gammaproteobacteria bacterium MAG_00215_gam_020. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911654 (2020).

100.
BioSample of Magnetococcales bacterium MAG_21055_mgc_1. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911672 (2020).

101.
BioSample of Nitrospinae bacterium MAG_09705_ntspn_70. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911661 (2020).

102.
BioSample of Nitrospirae bacterium MAG_10313_ntr_31. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911663 (2020).

103.
BioSample of Desulfuromonadales bacterium MAG_21601_9_030. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911674 (2020).

104.
BioSample of Desulfuromonadales bacterium MAG_13126_9_058. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911678 (2020).

105.
BioSample of Desulfuromonadales bacterium MAG_21600_9_004. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911673 (2020).

106.
BioSample of Planctomycetes bacterium MAG_11118_pl_115. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911664 (2020).

107.
BioSample of Planctomycetes bacterium MAG_17991_pl_60. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911669 (2020).

108.
BioSample of Planctomycetes bacterium MAG_18080_pl_157. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911671 (2020).

109.
BioSample of Rhodospirillaceae bacterium MAG_04806_tlms_2. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911657 (2020).

110.
BioSample of Rhodospirillaceae bacterium MAG_05422_2-02_14. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911658 (2020).

111.
BioSample of Rhodospirillaceae bacterium MAG_05596_2-02_51. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911659 (2020).

112.
BioSample of Rhodospirillaceae bacterium MAG_06104_tlms_034. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911660 (2020).

113.
BioSample of Rhodospirillaceae bacterium MAG_22225_2-02_112. NCBI BioSample https://identifiers.org/ncbi/biosample:SAMN14911676 (2020).

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Typhlatya species are found throughout marine and fresh groundwater habitats and are some of the most abundant and widespread stygofauna component in the anchialine ecosystems of the Yucatan Peninsula3,15,18,19,20. In contrast with previous authors suggesting that anchialine fauna has no distribution patterns within underwater caves21, results herein show differently. Shrimp abundance varied markedly in space and the resulting patterns differed from one system to another depending on topographic features, solar influence and geographical position (Fig. 2B). In addition, we found both diel and seasonal variations in the vertical distribution and abundance of T. mitchelli, one of the most common species in the study area3,15. Furthermore, carbon source analysis show a distinct feeding pattern across Typhlatya species. Overall, our observations on three Typhlatya species in four groundwater systems of Yucatan portray a niche partitioning where salinity appears to play a fundamental role in separating the realized niche of T. dzilamensis from that of T. mitchelli and T. pearsei, whilst solar influence, food selection, space, and diel behavior would partitions the later species´ ecological niche. The upcoming discussion focuses on the biological processes that could explain the patterns identified in the present study.
One of the most outstanding characteristics of the karstic anchialine ecosystems in Yucatan is the vertical stratification of water masses, where the marine intrusion from the coast infiltrates under the meteoric water that infiltrates underground, resulting in clearly defined layers with marked salinity changes. Salinity gradients in aquatic habitats are considered one of the most important limiting factors of species distributions22. Changes in environmental salinity may impose severe physiological stress23. Therefore, salinity commonly governs geographical distributions, adaptive radiations, speciation and physiology22,24. Whilst crustaceans are known to have originated in the ocean, atyid shrimps have a long history since the colonization of freshwater environments and their systematics have revealed frequent cave invasions4,25,26. Studies on Halocaridina rubra from anchialine ponds in Hawaii, which are subject to marked daily fluctuations in environmental salinity, have shown these shrimp maintain constitutively activated mechanisms of ion regulation and high cellular osmoregulation in the gills regardless of salinity24. Typhlatya, as an anchialine cave restricted genus25, must have developed a series of adaptations enabling their survival in coastal caves. Furthermore, speciation in Yucatan’s Typhlatya must have resulted in physiological, biochemical and genetic adaptations that derived in a different tolerance to salinity between closely related species and the colonization of subterranean habitats which are heterogeneous in depth and distance from the coast. Our results show that these shrimps are distributed according to salinity: T. mitchelli was found in all sites exclusively in the freshwater layer, T. pearsei was only observed in the fresh water at Nohmozon, and T. dzilamensis was only found in saline water at Ponderosa. The distribution patterns of Typhlatya species observed in this study constitute initial evidence in support of a physiological differentiation among species. Future research in adaptive physiology in response to salinity is key to reveal the osmoregulatory mechanisms and bioenergetics that will further explain the habitat selection (or limits) of these anchialine species (Chávez-Solís et al. in prep.).
It is noteworthy that T. pearsei was most abundant in the system with the highest dissolved oxygen in our study (Fig. 1). Perhaps, T. pearsei is more sensitive to hypoxia than the rest of its congeners. If this hypothesis is true, future studies should demonstrate a reduced metabolic capacity of T. pearsei under hypoxia, whereas T. mitchelli and T. dzilamensis should be comparatively less affected. Moreover, T. mitchelli should present a higher physiological performance, enabling to outcompete T. pearsei in hypoxic freshwater environments. Correspondingly T. pearsei should outcompete T. mitchelli under normoxia. Research on tolerance to hypoxia in stygobionts could test these predictions and provide a deeper understanding of the distribution patterns and adaptation mechanisms to dissolved oxygen variations in caves.
Despite the importance of oxygen and salinity determining the distribution patterns of many crustacean populations22,27, it does not explain the vertical and horizontal distribution of Typhlatya species in systems without a halocline. Abundance differences of T. mitchelli with depth in both Tza Itza and Kankirixche (Fig. 5) suggest that other explanatory variables are involved. Whilst light would appear to be a poor candidate explaining the distribution of blind stygobionts, negative phototaxis, as suggested by the results in the present study, has also been observed in anophthalmic stygobiont beetles Paroster macrosturtensis from Australian calcrete aquifers28. Evidence of this behavior is supported by observations of T. pearsei in the cenote pool at Nohmozon occurring only at night. In addition, transects nearest to the surface in Tza Itza and Kankirixche (i.e. those where sunlight had its greatest influence) consistently had low occurrence of T. mitchelli, particularly during day observations (Fig. 5). Furthermore, day/night differences in the abundance of T. mitchelli in Tza Itza and Nohmozon were limited to the shallow transects, were light influence was strongest. Differences in the way direct sunlight enters and reaches the water surface at Kankirixche compared to Tza Itza, together with the negative phototaxis, could account for the variations in the daily patterns of T. mitchelli observed between these two systems. Measuring traces of light in a cavern with commercial instruments can be challenging. Mejía-Ortiz et al.29 implemented an elegant solution by using long exposure photographs to show trace light at different depths in a dry cavern. Automated light quantification, however, is needed to determine whether light intensity triggers diel behavior in Typhlatya.
Diel migrations and nocturnal activity as that observed in this study have been previously reported in other blind stygobitic crustacean species, such as Creaseria morleyi30,31, Halocaridina rubra32, and Hadenoecus subterraneous33. Species restricted to caves are generally characterized by the reduction of visual structures and are part of the common troglomorphic features observed in stygobionts. Although some vestigial eye structures are observable in Typhlatya, no sign of visual function or pigments are evident, suggesting these species could be grouped as microphthalmic, or even anophthalmic (sensu Friedrich33). Whilst the assumption of anophthalmy—defined as “the lack of eyes at any stage of the life cycle and across populations”—is based on the absence of peripherally observable eyes, it may overlook vestiges of internalized visual organs and does not exclude the existence of other extra-retinal photoreceptors33. The negative phototactic behavior as a probable cause for the diel migrations described in the present study must find support in a mechanism of light detection amongst Typhlatya or closely related species. If these shrimps are still capable of perceiving light despite their visual reduction, then the way light reaches the water column will have a relevant role in keeping the circadian clock tuned, hence activity confined exclusively to dark hours night. Our observations also suggest that populations inhabiting the aphotic cave hydro-regions are present regardless of the time of day or night, as in T. dzilamensis. The constancy of biotic and abiotic parameters in this region may prevent the synchronization of the biological clocks of stygobionts33. The lack of a synchronizer in a cave population could result in a shift of their circadian rhythm producing an unsynchronized circadian rhythm among the population, an arrhythmic biological clock33, or a reduction of sleep duration34. Our recurrent observations of T. dzilamensis in caves at any given time of day or night is consistent with any of these scenarios. Research on the anatomy of the eye, the nervous system, photoreceptors, biological clocks and genetic expression in Typhlatya is needed to further explain the differences in behavior and activity patterns observed both among and within these species.
A possible contributing factor to Typhlatya diel behavior in the cenote pools and light influenced caverns could be related to the presence of epigean and stygobitic predators that may also influence the distribution and size of prey populations. Predation has been shown to modify prey behavior by inducing vertical migration patterns or forcing prey to retrieve to refuges during light periods32,35. Predators in cenote pools include a diverse array of freshwater fish36 and other stygobionts, such as Ophisternon infernale, Typhlias pearsei, Creaseria morleyi and the stygofile Rhamdia guatemalensis, all of which were recorded during night observations in the present study.
Habitat preference in the underground ecosystems is certainly linked to a number of ecological tradeoffs. A balancing component for blind prey living in the sun influenced hydro regions (thus an easy prey) could be the access to recently deposited plant debris rich in nutrients, or algae which are high in nitrogen content and easier to assimilate than plants10,37. This could be selecting T. mitchelli and T. pearsei to remain close to the cenote pools.
Advantages of shallow waters could also be a greater amount of dissolved oxygen and other organic inputs that are unlikely to reach the cave passages. If cenote pools are the only place in anchialine systems where photosynthesis takes place and constitute sinkholes for allochthonous input, then these hydro regions represent a nutrient attraction for cave primary consumers. Stygobionts in this trophic level would increase in density at cenote pools, further attracting epigean and hypogean predators. Results in this direction would suggest that cenote pools are “feeding hotspots” for all species in the heterotrophic anchialine ecosystem. If, on the other hand, photosynthetic and allochthonous nutrient input is scarce or absent in the cenote pool or represents a decimating risk due to visual predators, then Typhlatya must find food in the oligotrophic caves. If the aphotic dwelling T. dzilamensis deep inside caves has developed a strategy to incorporate in situ production sources (such as chemosynthesis or methane derived biomass) to their diet, then most individuals would keep away from the busy photosynthetic hot-spots.
Caves are considered oligotrophic because of a severe and almost constant scarcity of food. Additionally, bacterial mats have been suggested to yield lower energy transfer than that of photosynthesis38. Even so, a trade-off in energy transfer versus the risk of predation can be recognized. In either scenario, the anchialine ecosystems would appear to have a bottom-up control trophic structure, where the availability of autotrophs governs the abundance and distribution of the community. Our results show a greater abundance in hydro-regions linked to the surface (namely cenote pools and caverns), while cave populations were the least abundant throughout this study. Stable isotopes and radiocarbon analysis would link the distribution patterns herein observed with the available feeding sources and the importance of these sources to each of the species.
Metabolic pathways in autotrophs have different isotopic fractionation rates—a differential uptake of isotopes—which create specific carbon-isotope fingerprints11. δ13C values of consumers reflect those of their feeding sources and will be passed on to higher trophic levels, enabling the reconstruction of food webs9,10,11. The wide range of δ13C and Δ14C values observed in Typhlatya species collected from fresh groundwater (FGW) and saline groundwater (SGW) environments suggests a mixed contribution of photosynthetic and chemosynthetic derived matter, as well as modern and ancient carbon contributing to their biomass. Nevertheless, our results show each species has a specific carbon composition indicating a differential food proportion from each of the available sources.
The range of C/N ratios of  More