Shifts in Abiotic Variables and Consequences for Diversity

2009 ◽  
pp. 257-268 ◽  
Author(s):  
Christopher D.G. Harley ◽  
Sean D. Connell
Keyword(s):  
Abiotic Variables

scholarly journals A Network Perspective of the Ecosystem’s Health Provision Spectrum in the Tourist Trails of UNESCO Global Geoparks: Santo Sepulcro and Riacho do Meio Trails, Araripe UGG (NE of Brazil)

Geosciences ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 61
Author(s):  
Eduardo S. Guimarães ◽  
Ronaldo C. D. Gabriel ◽  
Artur A. Sá ◽  
Rafael C. Soares ◽  
Paulo Felipe R. Bandeira ◽  
...  
Keyword(s):  
Complex Systems ◽  
Ecosystem Health ◽  
Green Exercise ◽  
Sensory Experiences ◽  
Climate Exposure ◽  
Abiotic Variables

In this investigation, we formulated the Ecosystem’s Health Provision Spectrum and its centrality indicators, based on the identification of the Ecosystem Health Potentials and Opportunities on the trails of Santo Sepulcro and Riacho do Meio in the Araripe UNESCO Global Geopark (UGG), establishing a baseline for the promotion of green exercise and geotourism in the territory. Based on the network methodology for complex systems, we analyzed the closeness and strength of biotic, abiotic variables, nature phenomena, infrastructure, and sensory experiences in order to determine the configuration of these associations. In the Santo Sepulcro, regarding the association, two negative relations and two positive relations among the variables were highlighted; as for closeness and strength, Aquatic Diversity with the Scientific Values of Geodiversity stood out. In Riacho do Meio, we highlight three positive associations among the variables; as for connectivity, Biodiversity and Meteorological and Climate Exposure presented the highest values and, as for strength, the variables Biodiversity, Route Classification, and Aquatic Diversity were the most prominent. We conclude, based on the presented configuration, that the variables with greater connectivity act as hubs; if these variables are optimized, the network will present an acceptable theoretical configuration. However, neglecting central strength variables can cause the network to collapse.

Variation in climate determines differences in the effects of abiotic variables on the phytoplankton community in tropical ecosystems

2018 ◽  
Vol 69 (3) ◽  
pp. 357
Author(s):  
F. H. Portella Corrêa de Oliveira ◽  
A. N. Moura ◽  
Ê. W. Dantas
Keyword(s):  
Phytoplankton Community ◽  
Synergistic Effects ◽  
Climatic Conditions ◽  
Cylindrospermopsis Raciborskii ◽  
Tropical Reservoirs ◽  
Physicochemical Variables ◽  
Abiotic Variables ◽  
Tropical Climates ◽  
Semi Arid ◽  
Canonical Analyses

The present study demonstrates the effects of abiotic variables on phytoplankton in two different tropical climates. Samples were taken from tropical reservoirs, including six from a tropical climate (As) and five from a semi-arid climate (BSh). Phytoplankton samples were identified, biomass was quantified and climatic and physicochemical variables were evaluated. Canonical analyses were performed in order to observe the effects of abiotic variables on phytoplankton. In both As and BSh ecosystems, the effects of the physicochemical variables were significant, but the synergistic effects between variables and climatic conditions were more pronounced in BSh. Micronutrients had a significant role in structuring the phytoplankton community in both As and BSh. In As, Cylindrospermopsis raciborskii occurred in the presence of lower concentrations of zinc and copper, whereas in BSh this species was present in the presence of higher concentrations of zinc. In the As climate, Geitlerinema amphibium, Cyclotella meneghiniana, Planktothrix agardhii and Microcystis aeruginosa were associated with higher sodium concentrations in the water, whereas in the BSh climate these species experienced lower rainfall. The findings of the present study show that climate determines the effects of abiotic variables on the phytoplankton community in both an independent and synergistic manner. In the present study, phytoplankton in tropical and semi-arid reservoirs is mostly regulated by nutrients, the effects of which vary according to climate.

The role of abiotic variables in an emerging global amphibian fungal disease in mountains

2021 ◽  
pp. 152735
Author(s):  
Marilen Haver ◽  
Gaël Le Roux ◽  
Jan Friesen ◽  
Adeline Loyau ◽  
Vance T. Vredenburg ◽  
...  
Keyword(s):  
Fungal Disease ◽  
Abiotic Variables

scholarly journals Temporal variation of the phytoplankton community at short sampling intervals in the Mundaú reservoir, Northeastern Brazil

2008 ◽  
Vol 22 (4) ◽  
pp. 970-982 ◽  
Author(s):  
Ênio Wocyli Dantas ◽  
Ariadne do Nascimento Moura ◽  
Maria do Carmo Bittencourt-Oliveira ◽  
João Dias de Toledo Arruda Neto ◽  
Airlton de Deus C. Cavalcanti
Keyword(s):  
Phytoplankton Community ◽  
Abiotic Factors ◽  
Distribution Patterns ◽  
Northeastern Brazil ◽  
Cylindrospermopsis Raciborskii ◽  
Algae Biomass ◽  
Dissolved Phosphorus ◽  
Sampling Intervals ◽  
Abiotic Variables ◽  
Dry And Rainy Seasons

The aim of this study was to determine how abiotic factors drive the phytoplankton community in a water supply reservoir within short sampling intervals. Samples were collected at the subsurface (0.1 m) and bottom of limnetic (8 m) and littoral (2 m) zones in both the dry and rainy seasons. The following abiotic variables were analyzed: water temperature, dissolved oxygen, electrical conductivity, total dissolved solids, turbidity, pH, total nitrogen, nitrite, nitrate, total phosphorus, total dissolved phosphorus and orthophosphate. Phytoplankton biomass was determined from biovolume values. The role abiotic variables play in the dynamics of phytoplankton species was determined by means of Canonical Correspondence Analysis. Algae biomass ranged from 1.17×10(4) to 9.21×10(4) µg.L-1; cyanobacteria had biomass values ranging from 1.07×10(4) to 8.21×10(4) µg.L-1. High availability of phosphorous, nitrogen limitation, alkaline pH and thermal stability all favored cyanobacteria blooms, particularly during the dry season. Temperature, pH, total phosphorous and turbidity were key factors in characterizing the phytoplankton community between sampling times and stations. Of the species studied, Cylindrospermopsis raciborskii populations were dominant in the phytoplankton in both the dry and rainy seasons. We conclude that the phytoplankton was strongly influenced by abiotic variables, particularly in relation to seasonal distribution patterns.

scholarly journals SPECIES: Supporting big-data-driven research

2019 ◽  
Vol 3 ◽  
Author(s):  
Raul Sierra-Alcocer ◽  
Christopher Stephens ◽  
Juan Barrios ◽  
Constantino González‐Salazar ◽  
Juan Carlos Salazar Carrillo ◽  
...  
Keyword(s):  
Web Application ◽  
Application Programming Interface ◽  
Data Driven ◽  
Spatial Correlations ◽  
Species Occurrence ◽  
Global Biodiversity Information Facility ◽  
Application Programming ◽  
Abiotic Variables ◽  
Programming Interface ◽  
Biodiversity Information

SPECIES (Stephens et al. 2019) is a tool to explore spatial correlations in biodiversity occurrence databases. The main idea behind the SPECIES project is that the geographical correlations between the distributions of taxa records have useful information. The problem, however, is that if we have thousands of species (Mexico's National System of Biodiversity Information has records of around 70,000 species) then we have millions of potential associations, and exploring them is far from easy. Our goal with SPECIES is to facilitate the discovery and application of meaningful relations hiding in our data. The main variables in SPECIES are the geographical distributions of species occurrence records. Other types of variables, like the climatic variables from WorldClim (Hijmans et al. 2005), are explanatory data that serve for modeling. The system offers two modes of analysis. In one, the user defines a target species, and a selection of species and abiotic variables; then the system computes the spatial correlations between the target species and each of the other species and abiotic variables. The request from the user can be as small as comparing one species to another, or as large as comparing one species to all the species in the database. A user may wonder, for example, which species are usual neighbors of the jaguar, this mode could help answer this question. The second mode of analysis gives a network perspective, in it, the user defines two groups of taxa (and/or environmental variables), the output in this case is a correlation network where the weight of a link between two nodes represents the spatial correlation between the variables that the nodes represent. For example, one group of taxa could be hummingbirds (Trochilidae family) and the second flowers of the Lamiaceae family. This output would help the user analyze which pairs of hummingbird and flower are highly correlated in the database. SPECIES data architecture is optimized to support fast hypotheses prototyping and testing with the analysis of thousands of biotic and abiotic variables. It has a visualization web interface that presents descriptive results to the user at different levels of detail. The methodology in SPECIES is relatively simple, it partitions the geographical space with a regular grid and treats a species occurrence distribution as a present/not present boolean variable over the cells. Given two species (or one species and one abiotic variable) it measures if the number of co-occurrences between the two is more (or less) than expected. If it is more than expected indicates a signal of a positive relation, whereas if it is less it would be evidence of disjoint distributions. SPECIES provides an open web application programming interface (API) to request the computation of correlations and statistical dependencies between variables in the database. Users can create applications that consume this 'statistical web service' or use it directly to further analyze the results in frameworks like R or Python. The project includes an interactive web application that does exactly that: requests analysis from the web service and lets the user experiment and visually explore the results. We believe this approach can be used on one side to augment the services provided from data repositories; and on the other side, facilitate the creation of specialized applications that are clients of these services. This scheme supports big-data-driven research for a wide range of backgrounds because end users do not need to have the technical know-how nor the infrastructure to handle large databases. Currently, SPECIES hosts: all records from Mexico's National Biodiversity Information System (CONABIO 2018) and a subset of Global Biodiversity Information Facility data that covers the contiguous USA (GBIF.org 2018b) and Colombia (GBIF.org 2018a). It also includes discretizations of environmental variables from WorldClim, from the Environmental Rasters for Ecological Modeling project (Title and Bemmels 2018), from CliMond (Kriticos et al. 2012), and topographic variables (USGS EROS Center 1997b, USGS EROS Center 1997a). The long term plan, however, is to incrementally include more data, specially all data from the Global Biodiversity Information Facility. The code of the project is open source, and the repositories are available online (Front-end, Web Services Application Programming Interface, Database Building scripts). This presentation is a demonstration of SPECIES' functionality and its overall design.

scholarly journals Detecting environment-dependent diversification from phylogenies: a simulation study and some empirical illustrations

2017 ◽  
Author(s):  
Eric Lewitus ◽  
Hélène Morlon
Keyword(s):  
Environmental Variables ◽  
Relative Importance ◽  
Species Trees ◽  
Major Goal ◽  
Explanatory Variables ◽  
Extinction Rates ◽  
Dependency Tree ◽  
Species Evolution ◽  
Abiotic Variables

AbstractUnderstanding the relative influence of various abiotic and biotic variables on diversification dynamics is a major goal of macroevolutionary studies. Recently, phylogenetic approaches have been developed that make it possible to estimate the role of various environmental variables on diversification using time-calibrated species trees, paleoenvironmental data, and maximum-likelihood techniques. These approaches have been effectively employed to estimate how speciation and extinction rates vary with key abiotic variables, such as temperature and sea level, and we can anticipate that they will be increasingly used in the future. Here we compile a series of biotic and abiotic paleodatasets that can be used as explanatory variables in these models and use simulations to assess the statistical properties of the approach when applied to these paleodatasets. We demonstrate that environment-dependent models perform well in recovering environment-dependent speciation and extinction parameters, as well as in correctly identifying the simulated environmental model when speciation isenvironment-dependent. We explore how the strength of the environment-dependency, tree size, missing taxa, and characteristics of the paleoenvironmental curves influence the performance of the models. Finally, using these models, we infer environment-dependent diversification in three empirical phylogenies: temperature-dependence in Cetacea,δ13C-dependence in Ruminantia, andCO2-dependence in Portulacaceae. We illustrate how to evaluate the relative importance of abiotic and biotic variables in these three clades and interpret these results in light of macroevolutionary hypotheses for mammals and plants. Given the important role paleoenvironments are presumed to have played in species evolution, our statistical assessment of how environment-dependent models behave is crucial for their utility in macroevolutionary analysis.

scholarly journals Change in the meiofauna community structure of sandy beaches of the Nuevo Gulf (Chubut, Argentina)

2012 ◽  
Vol 52 (34) ◽  
pp. 411-422 ◽  
Author(s):  
Carlos A. Harguinteguy ◽  
M. Noelia Cofré ◽  
Catalina T. Pastor de Ward
Keyword(s):  
Community Structure ◽  
Environmental Gradients ◽  
Sandy Beaches ◽  
Core Tube ◽  
Meiofauna Community ◽  
Diameter Core ◽  
Abiotic Variables ◽  
Abundance And Diversity ◽  
One Way Anova ◽  
Main Factor

The composition and distribution of the benthic meiofauna assemblages of the Nuevo Gulf (Chubut, Argentina) are described in relation to abiotic variables. The meiofauna and sediment samples were collected in the intertidal zone of four sandy beaches with different anthropic disturbances in June 2005. The samples were obtained at 20 sampling sites using a 2.5 cm diameter core tube at a depth of 10 cm. A total of 13 meiofauna taxa were identified, with the meiofauna being primarily represented by nematodes, gastrotrichs, ciliates and polychaetes and the meiofauna abundances ranging from 1.5 × 10³ to 6.5 × 10³ ind. 10 cm‑2. Univariate (one-way ANOVA test) and multivariate (ANOSIM/MDS test) analyses showed clear dissimilarities in community structures between sites with anthropic effects and those in pristine condition, revealed by the significant differences were found between beaches near to and far way from a city with port activity. The meiofaunal assemblage varied in abundance and diversity, and these changes in the community structure may have been related to environmental gradients on the shore. The BIO‑ENV analysis showed that the redox potential discontinuity depth might be the main factor in the spatial distribution of organisms.

scholarly journals Beta Diversity Partitioning and Drivers of Variations in Fish Assemblages in a Headwater Stream: Lijiang River, China

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 680 ◽  
Author(s):  
Liangliang Huang ◽  
Jian Huang ◽  
Zhiqiang Wu ◽  
Yuanmin Mo ◽  
Qi Zou ◽  
...  
Keyword(s):  
Species Composition ◽  
Beta Diversity ◽  
Fish Assemblages ◽  
Headwater Streams ◽  
Species Turnover ◽  
Diversity Partitioning ◽  
Spatial Variables ◽  
Lijiang River ◽  
Abiotic Variables ◽  
Hydrological Variables

Beta diversity partitioning has currently received much attention in research of fish assemblages. However, the main drivers, especially the contribution of spatial and hydrological variables for species composition and beta diversity of fish assemblages are less well studied. To link species composition to multiple abiotic variables (i.e., local environmental variables, hydrological variables, and spatial variables), the relative roles of abiotic variables in shaping fish species composition and beta diversity (i.e., overall turnover, replacement, and nestedness) were investigated in the upstream Lijiang River. Species composition showed significant correlations with environmental, hydrological, and spatial variables, and variation partitioning revealed that the local environmental and spatial variables outperformed hydrological variables, and especially abiotic variables explained a substantial part of the variation in the fish composition (43.2%). The overall species turnover was driven mostly by replacement (87.9% and 93.7% for Sørensen and Jaccard indices, respectively) rather than nestedness. Mantel tests indicated that the overall species turnover (ßSOR and ßJAC) and replacement (ßSIM and ßJTU) were significantly related to hydrological, environmental, and spatial heterogeneity, whereas nestedness (ßSNE or ßJNE) was insignificantly correlated with abiotic variables (P > 0.05). Moreover, the pure effect of spatial variables on overall species turnover (ßSOR and ßJAC) and replacement (ßSIM and ßJTU), and the pure effect of hydrological variables on replacement (ßSIM and ßJTU), were not important (P > 0.05). Our findings demonstrated the relative importance of interactions among environmental, hydrological, and spatial variables in structuring fish assemblages in headwater streams; these fish assemblages tend to be compositionally distinct, rather than nested derivatives of one another. Our results, therefore, indicate that maintaining natural flow dynamics and habitat continuity are of vital importance for conservation of fish assemblages and diversity in headwater streams.

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