About: Environmental gradient is a research topic. Over the lifetime, 1092 publications have been published within this topic receiving 45797 citations.
TL;DR: In this article, a new multivariate analysis technique, called canonical correspondence analysis (CCA), was developed to relate community composition to known variation in the environment, where ordination axes are chosen in the light of known environmental variables by imposing the extra restriction that the axes be linear combinations of environmental variables.
Abstract: A new multivariate analysis technique, developed to relate community composition to known variation in the environment, is described. The technique is an extension of correspondence analysis (reciprocal averaging), a popular ordination technique that extracts continuous axes of variation from species occurrence or abundance data. Such ordination axes are typically interpreted with the help of external knowledge and data on environmental variables; this two—step approach (ordination followed by environmental gradient identification) is termed indirect gradient analysis. In the new technique, called canonical correspondence analysis, ordination axes are chosen in the light of known environmental variables by imposing the extra restriction that the axes be linear combinations of environmental variables. In this way community variation can be directly related to environmental variation. The environmental variables may be quantitative or nominal. As many axes can be extracted as there are environmental variables. The method of detrending can be incorporated in the technique to remove arch effects. (Detrended) canonical correspondence analysis is an efficient ordination technique when species have bell—shaped response curves or surfaces with respect to environmental gradients, and is therefore more appropriate for analyzing data on community composition and environmental variables than canonical correlation analysis. The new technique leads to an ordination diagram in which points represent species and sites, and vectors represent environmental variables. Such a diagram shows the patterns of variation in community composition that can be explained best by the environmental variables and also visualizes approximately the "centers" of the species distributions along each of the environmental variables. Such diagrams effectively summarized relationships between community and environment for data sets on hunting spiders, dyke vegetation, and algae along a pollution gradient.
TL;DR: There are two categories of environmental changes with altitude: those physically tied to meters above sea level, such as atmospheric pressure, temperature and clear-sky turbidity; and those that are not generally altitude specific, suchAs moisture, hours of sunshine, wind, season length, geology and even human land use.
Abstract: Altitudinal gradients are among the most powerful 'natural experiments' for testing ecological and evolutionary responses of biota to geophysical influences, such as low temperature. However, there are two categories of environmental changes with altitude: those physically tied to meters above sea level, such as atmospheric pressure, temperature and clear-sky turbidity; and those that are not generally altitude specific, such as moisture, hours of sunshine, wind, season length, geology and even human land use. The confounding of the first category by the latter has introduced confusion in the scientific literature on altitude phenomena.
TL;DR: The results suggest that both a habitat filter and a limit to the similarity of coexisting species can simultaneously shape the distribution of traits and the assembly of local plant communities.
Abstract: Community assembly processes are thought to shape the mean, spread, and spacing of functional trait values within communities Two broad categories of assembly processes have been proposed: first, a habitat filter that restricts the range of viable strategies and second, a partitioning of microsites and/or resources that leads to a limit to the similarity of coexisting species The strength of both processes may be dependent on conditions at a particular site and may change along an abiotic gradient We sampled environmental variables and plant communities in 44 plots across the varied topography of a coastal California landscape We characterized 14 leaf, stem, and root traits for 54 woody plant species, including detailed intraspecific data for two traits with the goal of understanding the connection between traits and assembly processes in a variety of environmental conditions We examined the within-community mean, range, variance, kurtosis, and other measures of spacing of trait values In this landscape, there was a topographically mediated gradient in water availability Across this gradient we observed strong shifts in both the plot-level mean trait values and the variation in trait values within communities Trends in trait means with the environment were due largely to species turnover, with intraspecific shifts playing a smaller role Traits associated with a vertical partitioning of light showed a greater range and variance on the wet soils, while nitrogen per area, which is associated with water use efficiency, showed a greater spread on the dry soils We found strong nonrandom patterns in the trait distributions consistent with expectations based on trait-mediated community assembly There was a significant reduction in the range of six out of 11 leaf and stem functional trait values relative to a null model For specific leaf area (SLA) we found a significant even spacing of trait values relative to the null model For seed size we found a more platykurtic distribution than expected These results suggest that both a habitat filter and a limit to the similarity of coexisting species can simultaneously shape the distribution of traits and the assembly of local plant communities
TL;DR: There was as much variation within individual soil pits as across surface soils from different biomes, emphasizing the importance of soil depth as an environmental gradient structuring soil microbial communities.
Abstract: Microorganisms exist throughout the soil profile and those microorganisms living in sub-surface horizons likely play key roles in nutrient cycling and soil formation However, the distributions of microbes through the soil profile remain poorly understood, as most studies focus only on those communities found in near-surface horizons Here we examined how microbial community structure changes within soil profiles, whether these changes are similar across soils from different landscape positions, and how the community-level variation within individual soil depth profiles compares to the variation across surface soils from a wide range of biomes We characterized changes in bacterial and archaeal community composition and diversity with depth through nine soil profiles located in a forested montane watershed in Colorado, USA Microbial community composition was determined by barcoded pyrosequencing of the 16S rRNA gene employing a primer set that captures both bacteria and archaea Relative microbial biomass and soil carbon concentrations decreased exponentially with depth while soil pH increased in nearly all of the profiles examined Bacterial diversity was typically highest in the top 10 cm of the profile; diversity typically dropped by 20–40% from the surface horizons to the deepest horizons sampled Community composition was significantly affected by soil depth in all profiles, driven primarily by a decline in the relative abundance of Bacteroidetes with depth and the peak in the relative abundance of Verrucomicrobia between 10 and 50 cm Microbial community composition across the nine pits was most variable in the surface horizons; communities at deeper soil depths were relatively similar regardless of landscape position When compared to the microbial communities from 54 previously-analyzed surface soils collected across a wide range of biome types, we found that there was as much variation within individual soil pits as across surface soils from different biomes, emphasizing the importance of soil depth as an environmental gradient structuring soil microbial communities
TL;DR: How abiotic factors change with elevation, how flora and fauna respond to these changes and how elevational species richness patterns have been studied are described to uncover drivers of biodiversity are described.
Abstract: The abiotic and biotic gradients on mountains have enormous potential to improve our understanding of species distributions, species richness patterns and conservation. Here we describe how abiotic factors change with elevation, how flora and fauna respond to these changes and how elevational species richness patterns have been studied to uncover drivers of biodiversity. There are four main trends in elevational species richness: decreasing richness with increasing elevation, plateaus in richness across low elevations then decreasing with or without a mid-elevation peak and a unimodal pattern with a mid-elevational peak. We discuss the history of elevational richness studies and overview the various hypotheses thought to be important in richness trends, including climatic, spatial, biotic and evolutionary factors.
Key Concepts:
Elevational gradients exhibit complex variation in abiotic conditions over short distances.
Patterns of elevational species richness follow four common patterns: mid-elevation peaks, decreasing, low-elevation plateaus and low plateaus with mid-elevation peaks.
Patterns of elevational species richness vary between taxonomic groups.
A combination of water availability and temperature is often found to be related to elevational species richness patterns.
No consistent support is found for the importance of area or mid-domain effects for elevational species richness patterns.
Support for the various mechanisms underlying elevational richness patterns tends to be related to the ecology and evolutionary history of the taxonomic group of interest.
Elevational gradients are valuable in our task to disentangle the causes behind broad-scale patterns in biodiversity, and in our quest to understand threats to biodiversity with climatic change.
Keywords:
climate;
biotic interactions;
diversity;
elevation;
environmental gradient;
mountains;
precipitation;
productivity;
species–area relationship;
temperature