Layout 1 ARTICLE Introduction The distribution of wild life species on Earth is heterogeneous and requires ecologists and biogeographers to formulate hypotheses to explain their patterns. Understanding the spatial and temporal distribution of species as well as identifying the factors that restrict their area of occurrence is fundamental to biogeography, ecology, conservation, and ecosystem management (Brambilla et al., 2009; Thuiller et al., 2009; Heino et al., 2015) . However, elucidating the mechanisms that organize the species of a taxonomic group in space and time is complex (Pither, 2007) . Species distribution is often described as a combination of several ecological (i.e., resource availability, environmental heterogeneity, and biological interactions), historical (i.e., climatic variations), stochastic, and evolutionary (i.e., evolutionary time and diversification) mechanisms (Willig et al., 2003). Theoretical models have shown that the success of a population in a region depends on its dispersion skills to super- pass geographical barriers, the environmental, and physical and chemical conditions that provide physiological support for survival, and their performance with respect to inter-specific interactions (Krebs, 2009). Time is fundamental in the establishment of a species, regardless of scale. On a macroscale, intercontinental biogeographic patterns have historically been Geographical, environmental, and biotic constraints define the spatial distribution of Diaphanosoma species (Cladocera) Jaielle R. Nascimento1, Louizi S.M. Braghin2, Camila R. Cabral3, Adriano Caliman4, Nadson R. Simões5 1Programa de Pós-graduação em Sistemas Aquáticos Tropicais, Universidade Federal do Sul da Bahia, Itabuna, Brazil; 2Programa de Pós- graduação em Ecologia de Ambientes Aquáticos Continentais, Universidade Estadual de Maringá, Maringá, Paraná, Brazil; 3Instituto Federal Farroupilha, Campus Santo Augusto, Santo Augusto, Brazil; 4Departamento de Ecologia, Universidade Federal do Rio Grande do Norte, Campus Uni-versitário - Lagoa Nova, Natal, Brazil; 5Centro de Formação em Ciências Agroflorestais, Universidade Federal do Sul da Bahia, Itabuna, Brazil ABSTRACT Species distribution is a combination of ecological, historical, stochastic, and evolutionary mechanisms, and is a process that has been severely impacted by anthropogenic activities. Freshwater zooplankton is adequate to assess that combination because it groups cosmopolitan and endemic species. We hypothesized that the spatial distribution of Diaphanosoma species is defined by a complex interaction between factors such as spatial limitation, limitation of environmental conditions, and ecological conditions. We georeferenced the occurrence of Diaphanosoma in Brazil to study the potential distribution of the species, preference of ecoregions, environmental features associated with Diaphanosoma, and their co-occurring patterns. Five species of Diaphanosoma are widely distributed in Brazil. D. spinulosum and D. birgei were widely distributed while D. fluviatile and D. polyspina had a more restricted distribution. The occurrences of Diaphanosoma species were shown to have an association with factors such as the total concentrations of nitrogen and phosphorus, pH and, temperature, except in the case of the D. brevireme. Our results show that geographic, environmental, and biotic filters can drive the spatial distribution of species of the genus Diaphanosoma. Therefore, the distribution and spatial occurrence of these species depend on dispersal capacity and spatial restrictions, suitability of the abiotic environment, and ecological interactions. Corresponding author: Jaielle R. Nascimento, Programa de Pós- Graduação em Sistemas Aquáticos Tropicais, Universidade Federal do Sul da Bahia, Itabuna, Brazil. E-mail: jaiellerodrigues@hotmail.com Key words: environmental filters, competition, ecoregions, con- generic species, biogeography. Authors’ contributions: all the authors made a substantive intellec- tual contribution. All the authors have read and approved the final version of the manuscript and agreed to be held accountable for all aspects of the work. Conflict of interest: the authors declare no potential conflict of in- terest. Funding: none. Availability of data and materials: all data generated or analyzed during this study are included in this published article. Acknowledgements: we thank Tatiane Mantovano by suggestions in the manuscript and Universidade Federal do Sul da Bahia. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Received: 7 September 2022. Accepted: 19 January 2023. Publisher’s note: all claims expressed in this article are solely those of the authors and do not necessarily represent those of their affil- iated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher. ©Copyright: the Author(s), 2023 Licensee PAGEPress, Italy Advances in Oceanography and Limnology, 2023; 14:10848 DOI: 10.4081/aiol.2023.10848 This work is licensed under a Creative Commons Attribution- NonCommercial 4.0 International License (CC BY-NC 4.0). Non -co mmerc ial us e o nly J.R. Nascimento et al.2 defined by the movement of continents, glaciation events, and speciation rates (Whittaker et al., 2001) . At the mesoscale, geomorphology is responsible for barriers and environmental conditions in areas of survival (Poff, 1997) , which prevent gene flow between populations. Lastly, on a microscale, communities of organisms are outlined as a result of both interspecific (i.e., predation, parasitism, and competition) and abiotic interactions within local habitat patches (Cohen & Shurin, 2003) . Some researchers have argued that anthropogenic changes over the last 500 years (Anthropocene) have reshaped global communities (Ellis, 2019) and modified the biogeography of taxonomic groups (Dirzo et al., 2014) . This effect is particularly severe in aquatic ecosystems as the potential for organism distribution is determined by hydrological connectivity, the degree of isolation of these environments (Torrente-Vilara et al., 2011; Fletcher et al., 2018) , and environmental conditions, which have been severely impacted by human activities during this period (Best, 2019) . This has promoted ecological barriers that filter species and prevent gene flow between populations. Some mechanisms associated with the spatial distribution of aquatic microorganisms include: dispersal ability and species sorting (Finlay, 2002) , historical factors and body size (Martiny et al., 2006), historical events and contemporary environment (Wang et al., 2019) , monopolization of resources resulting from the priority effect (De Meester et al., 2002) , neutral dynamics based on the ecological equivalence of species (Hubbel, 2001) , and trophic interactions in the aquatic food web (St-Gelais et al., 2021). No exclusive hypothesis explains the distribution of aquatic invertebrates because of the evolutionary complexity of distinct groups, leading to a variety of behavioral responses to environmental stresses. The zooplankton community in inland waters, for example, is primarily composed of three large groups (Rotifera, Cladocera, and Copepoda), which, despite sharing the same habitat and being subject to similar environmental pressures, have different evolutionary histories. In this context, discriminating the mechanisms responsible for the spatial distribution of species and/or zooplankton groups is pivotal to better understand their ecology and biogeography. Freshwater zooplankton represent a group that was historically considered as dominated by cosmopolitan species (Xu et al., 2009) , following the assumption of ‘everything is everywhere’ (Baas-Becking, 1934) . According to Martiny et al. (2006), microorganisms have enormous dispersal capabilities that rapidly erase the effects of past evolutionary and ecological events. However, cosmopolitanism has been replaced by continental/regional endemism (Xu et al., 2009) , which believes that ‘everything is everywhere: but the environment selects’ (Finlay, 2002) . Recently, several studies have demonstrated the importance of environmental selection on zooplankton at the meso and macroscales (Viana et al., 2014; Perbiche-Neves et al., 2019; Sodré et al., 2020) . However, studies on the importance of biotic interactions to represent patterns of zooplankton species distribution are rare. To understand the processes related to the distribution of zooplankton species, we analyzed the spatial distribution of species of the genus Diaphanosoma (Sididae/Diplostraca/ Branchiopoda/Arthropoda), a representative genus of plankton found in tropical regions, to unveil the factors that organize the distribution and define characteristics of the niche of the Diaphanosoma species. Species of this genus have traits that permit easy identification at the intermediate level in the Cladocera taxonomy, thereby reducing identification errors and improving the quality of a biogeographic survey. Diaphanosoma is characterized by the absence of a rostrum, fornices, or ocellus. The first antennae are small, truncated, with terminal olfactory arrows and with a thin flagellum. Their second antennae have a bisegmented dorsal branch and a ventral section with three segments, and basal spine are absent in the post-abdomen region (Elmoor-Loureiro, 1997). Although the Diaphanosoma species are mostly limnetic, some species have been found in vegetation zones and bromeliads (Korovchinsky, 1992; Fuentes-Reines et al., 2012) . Despite the wide distribution of Diaphanosoma, local co- existence between three or more congeneric species is rare. Thus, we hypothesized that the spatial distribution of Diaphanosoma species is defined by a complex interaction between spatial limitation, environmental conditions, and ecological interactions. We predicted that: i) a spatial difference is present in the distributions of Diaphanosoma species; ii) some species show regional distribution limited by space; iii) some species have a spatial distribution limited by environmental characteristics; and iv) a few species are excluded from the environment because of competitive interactions with species of the same genus. Materials and Methods Database Diaphanosoma were mapped using a georeferenced database to verify their distribution. We used data from studies conducted in the Brazil, a continental scale country with high variability in aquatic habitats. The Brazilian Government has divided the main hydrographic landscape into twelve hydrographic regions in accordance with the 32/2003 resolution of the National Council of Hydric Resources (Conselho Nacional de Recursos Hídricos, CNRH); the highest hydrographic region (Amazonas and Paraná) are among the major rivers of the Earth. The occurrence of the species was located by referencing papers published in national and international journals whose study on Cladocera was confined to Brazil. The papers were extracted from databases, such as Scielo (http://www.scielo.br/) and Web of Science (portal.isiknowledge.com). The last record was a paper published in June 2020 (Supplementary Material A). A total of 779 occurrence records were found (geographic coordinates), with at least one Diaphanosoma species in Brazil, which is referred to as the Total Base (TB) data. In addition to the georeferencing of occurrences, we also recorded limnological variables, such as water temperature, pH, dissolved oxygen, total nitrogen, and total phosphorus, from various studies. After georeferencing, we identified clusters of records with similar spatial information or studies from the same area of occurrence, but from different years that often overestimate the occurrences in that region. This sampling bias was resolved by dividing the map of Brazil into a 0.5° × 0.5° grid (hereafter termed Base of Distribution, BD), and only one record was marked in each cell. The spatial range of the species was analyzed using the latitudinal and longitudinal amplitudes Non -co mmerc ial us e o nly Geographical, environmental, and biotic constraints define the spatial distribution of Diaphanosoma species (Cladocera) 3 estimated using the BD. To estimate the potential distribution of Diaphanosoma, we created a geospatial model containing data on its presence and absence. We also modelled the distribution of each species using the kriging method, with an interpolation of the inverse distance power, as defined by Gräler et al. (2016) . The extrapolation of spatial data allows biologists to use statistical models and simulations, such as Species Distribution Modelling (SDM), which correlates the occurrence of species due to spatial autocorrelation or climatic-environmental data to identify favorable environmental conditions for target populations (Pearson et al., 2007; Franklin, 2010) . We also used the Bioclim model (Nix, 1986; Booth et al., 2014; Dou et al., 2022) to analyse the potential distribution using the bioclimatic data such as variables for temperature and precipitation (Table 1). However, this procedure was not efficient for our data, as it does not reflect the current distribution of Diaphanosoma. Potential distribution maps were generated using R Software version 4.1.0 (R Core Team, 2021) with the gstat package and its ‘predict’ function (Gräler et al., 2016). Data analysis First, the potential distribution of Diaphanosoma species in Brazil (hypothesis i) was compared through a visual analysis of the maps, based on BD. The frequency of occurrence of each species in a hydrographic region (hypothesis ii) was calculated by overlying the BD of all species with the BD of each species. Hydrographic regions were used as surrogate ecoregions. This procedure provided the percentage presence of each species in a hydrographic region with respect to the total occurrence of the species. The occurence frequency was categorized into the following groups: ≤20%, ≤40%, ≤60%, ≤80%, and ≤100%. Generalized additive models (Hastie & Tibshirani, 1990) were used to define whether the distribution of some Diaphanosoma species responds to environmental characteristics (hypothesis iii). In all models, the presence and absence of the species was considered as a response variable using a logit link function. Water temperature, pH, dissolved oxygen, total nitrogen, and total phosphorus were used as predictor variables in the model. To find the best fit, we examined the significance test and plot between environmental characteristics and occurrence probability. Finally, the effect of competition on the distribution of Diaphanosoma species (hypothesis iv) was assessed using the C-scores Index (Stone & Roberts, 1990), which represents the average number of checkerboard units for each unique species pair (Gotelli & Rohde, 2002). The higher the C-score value, the lower is the number of species co-occurring in an assembly. To check if the distribution pattern was different from a random distribution, a null model was constructed with a non-sequential algorithm for binary matrices that preserved the site (row) frequencies, but used column marginal frequencies as probabilities of selecting species (Gotelli & Rohde, 2002). We applied the probabilistic model of species co-occurrence that uses an algorithm to calculate the observed and expected frequencies of co-occurrence between each pair of species (Veech, 2013), using the R package cooccur (Griffith et al., 2016). Results Five species of Diaphanosoma were recorded in Brazil: Diaphanosoma birgei (Korineck 1981), Diaphanosoma brevireme (Sars 1901), Diaphanosoma fluviatile (Hansen 1899), Diaphanosoma polyspina (Korovchinsky 1982), and Diaphanosoma spinulosum (Herbest, 1967). D. spinulosum and D. birgei were widely distributed in Brazil, ranging from −1° to −32.5° S latitude and −35° to −68.5° W longitude (Figure 1a and 1b). D. fluviatile and D. polyspina were limited from −42.5° to −63.5° W (Figure 1d and 1e). D. fluviatile and D. brevireme occurred in eight hydrographic regions, whereas D. polyspina occurred in four of the twelve hydrographic regions in Brazil (Figure 2). In general, D. fluviatile, D. brevireme, and D. polyspina showed limited occurrences in the hydrographic regions. The frequencies of occurrence of D. spinulosum, D. birgei, D. fluviatile, and D. polyspina (Figure 3) were associated with environmental variables (Table 2, Supplementary Material A). An increase in pH favored the occurrence of D. spinulosum (positive coefficient), but did not favor the occurrence of D. polyspina. The frequencies of occurrence of D. birgei and D. fluviatile decreased with an increase in the concentration of total phosphorus. The frequency of occurrence of D. fluviatile was negatively associated with water temperature. Lastly, the frequency of occurrence of D. brevireme showed a low fit with environmental variables (Supplementary Material A). The co-occurrence analysis identified that the checkerboard patterns were higher than that expected at random (observed Cs=0.85; simulated Cs=0.60; p<0.001). Pairwise analysis between species identified negative relationships between the five species that occur in Brazil (Figure 4) except for D. brevireme and D. fluviatile. In addition, no positive relationships were observed. Table 1. Bioclimatic variables used in Bioclim model. Code Variables BIO1 Annual Mean Temperature BIO2 Mean Diurnal Range (Mean of monthly) BIO3 Isothermality BIO4 Temperature Seasonality BIO5 Max Temperature of Warmest Month BIO6 Min Temperature of Coldest Month BIO7 Temperature Annual Range BIO8 Mean Temperature of Wettest Quarter BIO9 Mean Temperature of Driest Quarter BIO10 Mean Temperature of Warmest Quarter BIO11 Mean Temperature of Coldest Quarter BIO12 Annual Precipitation BIO13 Precipitation of Wettest Month BIO14 Precipitation of Driest Month BIO15 Precipitation Seasonality BIO16 Precipitation of Wettest Quarter BIO17 Precipitation of Driest Quarter BIO18 Precipitation of Warmest Quarter BIO19 Precipitation of Coldest Quarter Non -co mmerc ial us e o nly J.R. Nascimento et al.4 Figure 1. Distribution of species of the Diaphanosoma genus as recorded in Brazil: presence (+) and absence (◦); heat map based on the spatial autocorrelation of the species. Non -co mmerc ial us e o nly Geographical, environmental, and biotic constraints define the spatial distribution of Diaphanosoma species (Cladocera) 5 Discussion Our results showed that geographic, environmental, and biotic filters determine the spatial distribution of the Diaphanosoma species. This indicates that the distribution and spatial occurrence of these species depend on dispersal capacity, spatial restrictions, suitability of the abiotic environment, and ecological interactions (St-Gelais et al., 2021), corroborating previous heuristic models that frame assemblage rules and species pools (Poff, 1997; Rahel, 2002). In this study, D. spinulosum and D. birgei displayed a wide spatial distribution, corroborating the hypothesis of the high dispersal capacity of zooplankton and that some species are extremely widespread, probably because of the plasticity of these species to environmental variation. This phenomenon can be associated with genetic diversity as the population variability of Diaphanosoma is associated with environmental gradients (Liu et al., 2021) . D. fluviatile and D. polyspina showed a narrower spatial distribution, suggesting that their distribution is a consequence of the joint influence of spatial limitation, preference for hydrographic regions, and ecological interactions. Brazil has a large continental extension (latitudinal range varying from ca. 5° in the north to ca. 33° in the south) and a high diversity of aquatic ecosystems, each with varying environmental conditions, which may have resulted in this distribution pattern. These aquatic environments are subject to different averages and temperature variations: sites close to the equator are subject to higher temperatures that are stable over time, while those further south fall under a sub-tropical climate, and are subject to lower, but more variable temperatures. Under this spatial and environmental range, Diaphanosoma have been recorded in several aquatic environments: reservoirs, lakes, and perennial and intermittent rivers. Some Diaphanosoma species prefer small tropical water bodies with intermittent regimes, including Figure 2. Graphic representation of the occurrence frequencies of Diaphanosoma species as recorded in Brazilian hydrographic regions. The frequency of occurrence was categorized as: ≤20%, ≤40%, ≤60%, ≤80%, and ≤100%. Figure 3. Statistical summary of the limnological variables associated with Diaphanosoma distribution in the Brazil. Table 2. Relation between environmental variables and the frequency of occurrence of species of the genus Diaphanosoma, as recorded in Brazil. The models are a result of the smoothed logistic regression. Dissolved oxygen pH Temperature Total nitrogen Total phosphorus b R2 b R2 b R2 b R2 b R2 D. spinulosum 0.56 0.05 D. birgei -0.70 0.17 D. brevireme D. fluviatile -0.19 0.07 -0.47 0.09 D. polyspina -0.51 0.09 -0.77 0.09 b, angular coefficient; R2, coefficient of determination only significant coefficients (p<0.001) were shown. Non -co mmerc ial us e o nly J.R. Nascimento et al.6 temporary ones (Korovchinsky, 2016), and inhabit warm and food-rich water. This adaptation may confer a decisive advantage to life in tropical waters (Han et al., 2011). D. spinulosum is a good representation of this adaptive capacity as it is widely distributed and is characteristic of plankton in tropical regions (Dumont et al., 2021). This species is common in northeastern Brazil, which is composed of many intermittent rivers subject to high temperatures and ecological restrictions (Nobre et al., 2020) . Environmental conditions were also important in determining the spatial distributions of D. spinulosum, D. birgei, D. fluviatile, and D. polyspina. Ecological barriers were significant for Cladocera distribution (Korovchinsky, 2006) as the species have tolerance limits (minimum and maximum values) with respect to environmental conditions and resources (Shelford’s Law of tolerance), which limits their occurrence and establishment. Water temperature, dissolved oxygen, pH, and total phosphorus were all associated with species distribution, showing that aquatic conditions and/or eutrophication are also important drivers for the spatial distribution of Diaphanosoma species. D. spinulosum occurs in areas with higher pH values, primarily in northeastern Brazil where aquatic environments are naturally subject to reduced inlet water-to-evaporation ratios, which increases lake eutrophication (Menezes et al., 2019). However, these circumstances decreased the occurrence frequencies of D. fluviatile and D. polyspina, which were recorded in less eutrophic environments with lower water temperatures. The frequencies of D. birgei and D. fluviatile also decreased with increasing eutrophication. In general, Diaphanosoma prefers warm regions (Matveev & Gabriel, 1994) , but recent surveys have also suggested suitability for a subtropical climate with warm waters and cold winters (Dumont et al., 2021). Moreover, they have high energetic requirements (Sarma et al., 2005) and high bacteria-feeding efficiency, and in some situations prefer smaller food particles (Brendelberger, 1991). Our records suggest that the preference for temperature ranges is species-specific: D. spinulosum, D. polyspina, and D. brevireme prefer the tropics, whereas D. fluviatile and D. birgei prefer the subtropics. These results also have important implications with respect to preparing for the ongoing global warming, as an increase in eutrophication is expected with an increase in temperature, which may favor the distribution of D. spinulosum in Brazil, but restrict the distribution of other species. Interspecific interactions can also determine the spatial distribution of species; the exclusive competition might have contributed to the spatial distribution of some species of Diaphanosoma in Brazil. In the co-occurrence analysis, the checkboard pattern was higher than that expected at random, suggesting that the presence of one species, on an average, is associated with a low probability of others occurring in the same region at the same time. This corroborates our prediction of the low probability of three or more species of Diaphanosoma occurring together under the same conditions. Under our experimental conditions: i) species of the genus Diaphanosoma were competitively excluded by Ceriodaphnia because of direct competition for resources (exploratory competition), leading to adult individuals perishing because of limited resources (Matveev & Gabriel, 1994) ; ii) D. excisum showed competitive superiority over D. dubium in monopolizing available resources (Liu et al., 2021) . These results suggest that zooplankton species that can better exploit resources dominate the environment and exclude other species from it. Thus, two mechanisms can explain the checkboard pattern of the various species of Diaphanosoma. i) Response to environmental conditions: due to the spatial extent of this study as well as the variety of environmental conditions intrinsic to the region studied, species may respond antagonistically to the effects of the environment. For example, D. spinulosum reacted positively to changes in pH, whereas D. polyspina responded negatively. ii) Competitive exclusion: some species may have the ability to exclude other species that could potentially occupy the same ecological niche. The pairwise co-occurrence analysis identified that a negative relationship existed between D. spinulosum and D. birgei and with other Diaphanosoma species. The competition between species of Diaphanosoma can be justified by behavioral, morphological, or physiological features, which improve fitness and offer competitive advantages in the exploration of the environment, and consequently, lead to niche differentiation. The main morphological differentiation between these species is the presence of duplication, thorn patterns on the edges of the carapace, and the number of arrows in the P6 endopotide (Elmoor-Loureiro, 1997; Dumont et al., 2021). However, the morphological conservatism through time (Jurassic–Cretaceous) suggests that natural selection cannot further refine the structural adaptation of these animals to their environments (Dumont et al., 2021). Thus, behavioral and/or physiological adaptations to explore specific conditions may be important in defining which species of Diaphanosoma inhabits a region at a specific time. In addition, D. brevireme was limited by interaction only due to competition, as it occurs in several hydrographic regions (althoughat a low frequency) and does not respond significantly to environmental variations. Phylogeographic estimates with cladocerans and rotifers indicated that the strong priority effect and local selective regime can structure populations with independent evolutionary trajectories (Xiang et al., 2011; Liu et al., 2021) , owing to the rapid growth and local adaptation in new habitats (De Meester et al., 2002) . Additionally, deeper phylogenetic patterns are known to be consistent with vicariance scenarios linked to continental Figure 4. Pairwise species co-occurrence matrix of the Di- aphanosoma species in Brasil. Non -co mmerc ial us e o nly Geographical, environmental, and biotic constraints define the spatial distribution of Diaphanosoma species (Cladocera) 7 (Adamowicz et al., 2009) and intracontinental (Xu et al., 2009) fragmentation. Hydrographic basins and ecoregions also have a selective role on the distribution of aquatic species (Poff, 1997), including zooplankton (Sodré et al., 2020). In South America, several fish species are endemic to watersheds (Albert & Reis, 2001), and biogeographical patterns in multiple species are frequent in large-scale analyses (Lansac-Tôha et al., 2020) . This indicates that allopatric divergence is also likely an important mechanism of diversification for invertebrates inhabiting continental waters (Adamowicz et al., 2009; Xu et al., 2009). Limitations of this study include: i) different databases were used to test the hypotheses owing to the absence of standardized information; ii) therefore, we did not partition the sources of variation in this study; iii) there are no identified confounding effects among filters; iv) the absence of information related to top-down control that can affect the cladoceran distribution; and v) the lack of information about competition with other cladocerans. However, these limitations do not invalidate the results and discussions presented in this study, but present a challenge for future perspectives. Conclusions In this study, we showed that spatial and ecological filters are crucial for the spatial distribution of species of the genus Diaphanosoma (Figure 5). Spatial filters (geographic constraints) defined the spatial distribution of D. fluviatile and D. polyspina. Environmental conditions were important for D. spinulosum and D. birgei, whereas ecological interactions were significant for D. brevireme. Thus, the distribution of Diaphanosoma species in Brazil may be a combination of founding historical events responsible for the colonization of habitats, historical adaptations that allowed species to survive in a variety of situations (such as tolerance to a wide temperature range and production of resistant eggs), ecological unpredictability defined by the randomness of dispersion but resulting in the priority effect and the monopolization of resources, and ecological responses to environmental variations underlying the quality of the environment (e.g., metabolism and eutrophication). 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