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The roles of dimensionality, canopies and complexity in ecosystem monitoring.

ABSTRACT: Canopies are common among autotrophs, increasing their access to light and thereby increasing competitive abilities. If viewed from above canopies may conceal objects beneath them creating a 'canopy effect'. Due to complexities in collecting 3-dimensional data, most ecosystem monitoring programmes reduce dimensionality when sampling, resorting to planar views. The resultant 'canopy effects' may bias data interpretation, particularly following disturbances. Canopy effects are especially relevant on coral reefs where coral cover is often used to evaluate and communicate ecosystem health. We show that canopies hide benthic components including massive corals and algal turfs, and as planar views are almost ubiquitously used to monitor disturbances, the loss of vulnerable canopy-forming corals may bias findings by presenting pre-existing benthic components as an altered system. Our reliance on planar views in monitoring ecosystems, especially coral cover on reefs, needs to be reassessed if we are to better understand the ecological consequences of ever more frequent disturbances.

SUBMITTER: Goatley CH

PROVIDER: S-EPMC3207849 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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The roles of dimensionality, canopies and complexity in ecosystem monitoring.

Goatley Christopher H R CH Bellwood David R DR

PloS one 20111103 11

Canopies are common among autotrophs, increasing their access to light and thereby increasing competitive abilities. If viewed from above canopies may conceal objects beneath them creating a 'canopy effect'. Due to complexities in collecting 3-dimensional data, most ecosystem monitoring programmes reduce dimensionality when sampling, resorting to planar views. The resultant 'canopy effects' may bias data interpretation, particularly following disturbances. Canopy effects are especially relevant ...[more]

PMID: 22073311

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Project description:BackgroundWith the recognition that environmental change resulting from anthropogenic activities is causing a global decline in biodiversity, much attention has been devoted to understanding how changes in biodiversity may alter levels of ecosystem functioning. Although environmental complexity has long been recognised as a major driving force in evolutionary processes, it has only recently been incorporated into biodiversity-ecosystem functioning investigations. Environmental complexity is expected to strengthen the positive effect of species richness on ecosystem functioning, mainly because it leads to stronger complementarity effects, such as resource partitioning and facilitative interactions among species when the number of available resource increases.Methodology/principal findingsHere we implemented an experiment to test the combined effect of species richness and environmental complexity, more specifically, resource richness on ecosystem functioning over time. We show, using all possible combinations of species within a bacterial community consisting of six species, and all possible combinations of three substrates, that diversity-functioning (metabolic activity) relationships change over time from linear to saturated. This was probably caused by a combination of limited complementarity effects and negative interactions among competing species as the experiment progressed. Even though species richness and resource richness both enhanced ecosystem functioning, they did so independently from each other. Instead there were complex interactions between particular species and substrate combinations.Conclusions/significanceOur study shows clearly that both species richness and environmental complexity increase ecosystem functioning. The finding that there was no direct interaction between these two factors, but that instead rather complex interactions between combinations of certain species and resources underlie positive biodiversity ecosystem functioning relationships, suggests that detailed knowledge of how individual species interact with complex natural environments will be required in order to make reliable predictions about how altered levels of biodiversity will most likely affect ecosystem functioning.

Project description:In an era of unprecedented ecological upheaval, monitoring ecosystem change at large spatial scales and over long-time frames is an essential endeavor of effective environmental management and conservation. However, economic limitations often preclude revisiting entire monitoring networks at high frequency. We aimed here to develop a prioritization strategy for monitoring networks to select a subset of existing sites that meets the principles of complementarity and representativeness of the whole ecological reality, and maximizes ecological complementarity (species accumulation) and the spatial and environmental representativeness. We applied two well-known approaches for conservation design, the "minimum set" and the "maximal coverage" problems, using a suite of alpha and beta biodiversity metrics. We created a novel function for the R environment that performs biodiversity metric comparisons and site prioritization on a plot-by-plot basis. We tested our procedures using plot data provided by the Terrestrial Ecosystem Research Network (TERN) AusPlots, an Australian long-term monitoring network of 774 vegetation and soil monitoring plots. We selected 250 plots and 80% of the total species recorded as targets for the maximal coverage and minimum set problems, respectively. We compared the subsets selected by the different biodiversity metrics in terms of complementarity and spatial and environmental representativeness. We found that prioritization based on species turnover (i.e., iterative selection of the most dissimilar plot to a cumulative sample in terms of species replacement) maximized ecological complementarity and spatial representativeness, while also providing high environmental coverage. Species richness was an unreliable metric for spatial representation. Selection based on range-rarity-richness was balanced in terms of complementarity and representativeness, whereas its richness-corrected implementation failed to capture ecological and environmental variation. Prioritization based on species turnover is desirable to cover the maximum variability of the whole network. Synthesis and applications: Our results inform monitoring design and conservation priorities, which can benefit by considering the turnover component of beta diversity in addition to univariate metrics. Our tool is computationally efficient, free, and can be readily applied to any species versus sites dataset, facilitating rapid decision-making.

Dataset Information

The roles of dimensionality, canopies and complexity in ecosystem monitoring.

Publications

The roles of dimensionality, canopies and complexity in ecosystem monitoring.

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