The hypotheses that beta diversity should increase with decreasing latitude and increase with spatial extent of a region have rarely been tested based on a comparative analysis of multiple datasets, and no such study has focused on stream insects. We first assessed how well variability in beta diversity of stream insect metacommunities is predicted by insect group, latitude, spatial extent, altitudinal range, and dataset properties across multiple drainage basins throughout the world. Second, we assessed the relative roles of environmental and spatial factors in driving variation in assemblage composition within each drainage basin. Our analyses were based on a dataset of 95 stream insect metacommunities from 31 drainage basins distributed around the world. We used dissimilarity-based indices to quantify beta diversity for each metacommunity and, subsequently, regressed beta diversity on insect group, latitude, spatial extent, altitudinal range, and dataset properties (e.g., number of sites and percentage of presences). Within each metacommunity, we used a combination of spatial eigenfunction analyses and partial redundancy analysis to partition variation in assemblage structure into environmental, shared, spatial, and unexplained fractions. We found that dataset properties were more important predictors of beta diversity than ecological and geographical factors across multiple drainage basins. In the within-basin analyses, environmental and spatial variables were generally poor predictors of variation in assemblage composition. Our results revealed deviation from general biodiversity patterns because beta diversity did not show the expected decreasing trend with latitude. Our results also call for reconsideration of just how predictable stream assemblages are along ecological gradients, with implications for environmental assessment and conservation decisions. Our findings may also be applicable to other dynamic systems where predictability is low.
The fossil record acts as a time machine, providing data on the morphology, ecology and biogeography of ancient species. Therefore, ideally, fossil data should be included in evolutionary, macroecological and biogeographical studies. However, paleontological data are often not used in biological research, in part because of the difficulty of extracting occurrence records from the primary literature. The goal of the Paleobiology Database is to make these records generally accessible, but unlike databases such as Genbank and GBIF, a ready‐made interface to the R computing environment has not been available. We have developed paleobioDB, an R package designed to perform easy and flexible queries of the Paleobiology Database, including visualization, downloading and processing of selected data. This package facilitates access to paleontological data in a way that should allow further analysis using other packages and libraries available in R. The paleobioDB package should facilitate the integration of paleontological and neontological datasets, so that data from the deep past can be used to help inform our understanding of living biota, and vice versa.
Ecological communities are composed of a few common and several rare species. Many studies have evaluated the shape of abundance distribution curves, but few studies have assessed the causes of rarity. Using a dataset of stream macroinvertebrates, we investigated whether the excess of rare species in three focal communities of stones in riffles were common 1) in other habitats at the same stream site and period of sampling (environment), 2) in other stream sites in the same habitat and period of sampling (space), and 3) in other years in the same stream site and habitat (time). We observed that around 28% of the rare species were common in other habitats (environment), stream sites (space) or years (time). Among the three factors, rarity was mostly explained by habitat type, whereas a significant portion of the rare species in riffles were common in pools, submerged roots of terrestrial plants or in partially submerged moss patches. This result suggests that the presence in non‐optimum habitat is a strong determinant of the rarity observed in natural communities and most rare species are due to sampling artifacts or accidentally sampled transient species.
River floodplains are subject to different inundation scenarios, mainly related to the flood pulse. Moreover, the ecology of floodplain lakes is modulated by exchanges of water with the main stream. On Amazonian floodplains, the water level fluctuates seasonally, with four distinct stages during the year: rising, high, falling, and low water. This study evaluated how/which three functional approaches to phytoplankton (FG, functional groups; MFG, morphofunctional groups; and MBFG, morphology-based functional groups) showed the largest relation to the environmental variations in response to rising and falling water periods, using data of the seven lakes sampled during rising and falling water periods, on the Curuaí Floodplain system, Pará state, Brazil. We used a Principal Coordinates Analysis to check for differences in phytoplankton species composition between the rising and falling water periods and a Redundancy Analysis to evaluate the relationship between functional approaches and environmental. Electrical conductivity, silica, and pH were the most important environmental variables to structuring the phytoplankton. The biological dissimilarity was computed using Bray-Curtis index for species biovolume and indicated greater similarity among the species compositions in the lakes during the falling water period. During rising water species is adapted in almost all lentic ecosystems (FG Y) and autotrophic organisms typical from the meroplanktonic that can be found in phytoplankton samples of the shallow lakes (FG MP); cryptomonads (MFG 2d), large centrics (MFG 6a), and large pennates (MFG 6b); and nonflagellated organisms with siliceous exoskeletons (MBFG VI) and unicellular flagellates of medium to large size (MBFG V) were predominant. During falling water, species that tolerate eutrophic to hypertrophic environments with low nitrogen content predominated all shallow lakes (FGs H1 and M; MFGs 5e and 5b; and MBFGs III and VII) and Dolichospermum spp. formed blooms. Morphology-based functional groups were the larger relation with the environmental variations than did functional groups and morphofunctional groups. MBFGs provides a relatively simple and objective classification and were the best in characterizing phytoplankton dynamics on the Curuaí floodplain. Therefore, we recommend using these groups to study phytoplankton ecology in shallow floodplain lakes.
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