In this synthesis paper, three articles relating to meta-analysis are presented. Meta-analysis is a term widely used in statistics which refers to the combined analysis of a range of individual studies that provide better and global insight of the problem being investigated. In the first article, published studies were compiled that explicitly manipulated soil biodiversity and measured responses of soil C cycling pools and/or processes. Using meta-analysis and regression analysis, it is shown that loss of soil biodiversity can have negative consequences for the soil carbon (C) cycle, significantly reduces plant tissue composition, soil respiration and litter decomposition. Second, meta-analysis has also helped the researchers to elucidate that “LOGDIST” was the main explanatory variable for the decline in abundance of bird populations due to infrastructure. Mammal and bird population densities declined with their proximity to infrastructure. Lastly, meta-analysis further showed that global mean temperature increases of more than 2oC above pre-industrial levels significantly affect local species richness. The resulting meta-model can be used for future biodiversity assessment to prevent further loss and degradation.
Abstract
In this synthesis paper, three articles relating to meta-analysis are presented. Meta-analysis is a term widely used in statistics which refers to the combined analysis of a range of individual studies that provide better and global insight of the problem being investigated. In the first article, published studies were compiled that explicitly manipulated soil biodiversity and measured responses of soil C cycling pools and/or processes. Using meta-analysis and regression analysis, it is shown that loss of soil biodiversity can have negative consequences for the soil carbon (C) cycle, significantly reduces plant tissue composition, soil respiration and litter decomposition. Second, meta-analysis has also helped the researchers to elucidate that “LOGDIST” was the main explanatory variable for the decline in abundance of bird populations due to infrastructure. Mammal and bird population densities declined with their proximity to infrastructure. Lastly, meta-analysis further showed that global mean temperature increases of more than 2oC above pre-industrial levels significantly affect local species richness. The resulting meta-model can be used for future biodiversity assessment to prevent further loss and degradation.
Keywords:Biodiversity, Meta-analysis, Ecology, Research studies
OVERVIEW:
Meta-analysis is the statistical analysis of a large collection of analysis results for the purpose of integrating the findings (Glass, 1981). The basic purpose of meta-analysis is to provide the same methodological rigor to a literature review that is required from experimental research. Meta-analyses are generally centered on the relationship between one explanatory and one response variable. This relationship, the effect of X on Y," defines the analysis.
Furthermore, meta-analysis provides an opportunity for shared subjectivity in reviews, rather than true objectivity. Authors of meta-analyses must sometimes make decisions based on their own judgment, such as when defining the boundaries of the analysis or deciding exactly how to code moderator variables (DeCoster, 2004).
By far the most common use of meta-analysis has been in quantitative literature reviews. These are review articles where the authors select a research finding or effect that has been investigated in primary research under a large number of different circumstances. They then use meta-analysis to help them describe the overall strength of the effect, and under what circumstances it is stronger and weaker (Morris and DeShon, 2002).
Recently, as knowledge of meta-analytic techniques has become more widespread, researchers have begun to use meta-analytic summaries within primary research papers. In this case, meta-analysis is used to provide information supporting a specific theoretical statement, usually about the overall strength or consistency of a relationship within the studies being conducted. As might be expected, calculating a meta-analytic summary is typically a much simpler procedure than performing a full quantitative literature review.
Meta-analyses are most easily performed with the assistance of computer databases (Microsoft Access, Paradox) and statistical software (DSTAT, SAS) (DeCoster, 2004).
ARTICLE REVIEW:
In the first article conducted by Graaff et al., (2015), published studies were compiled that explicitly manipulated soil biodiversity and measured responses of soil C cycling pools and/or processes. They were systematically searched in ISI Web of Science using all possible combinations of one soil C search term, one soil organism search term, and the term “diversity”.
Declining or loss of biodiversity impacts ecosystem functions, such as carbon (C) cycling. Soils are the largest terrestrial C pool, containing more C globally than the biotic and atmospheric pools together. Thus, cycling of soil C, and the processes controlling it, is potential to affect atmospheric CO2 concentrations and subsequent climate change.
Even with the growing evidence of links between plant diversity and soil C cycling, there is a lack of information on whether similar relationships exist between soil biodiversity and C cycling. This knowledge gap occurs even though there has been increased recognition that soil communities display high levels of both taxonomic and functional diversity and are key drivers of fluxes of C between the atmosphere and terrestrial ecosystems.
In this study, meta-analysis and regression analysis to quantitatively assess how soil biodiversity affects soil C cycling pools and processes (i.e., soil C respiration, litter decomposition, and plant biomass). The response of process variables was compared to changes in diversity both within and across groups of soil organisms that differed in body size, a grouping that typically correlates with ecological function.
When studies that manipulated both within- and across-body size group diversity were included in the meta-analysis, loss of diversity significantly reduced soil C respiration (27.5 %) and plant tissue decomposition (18 %) but did not affect above- or belowground plant biomass. The loss of within-group diversity significantly reduced soil C respiration, while loss of across-group diversity did not. Decomposition was negatively affected both by loss of within-group and across-group diversity.
Furthermore, loss of microbial diversity strongly reduced soil C respiration (41 %). In contrast, plant tissue decomposition was negatively affected by loss of soil faunal diversity but was unaffected by loss of microbial diversity. Taken together, the findings show that loss of soil biodiversity strongly impacts on soil C cycling processes, and highlight the importance of diversity across groups of organisms (e.g., primary consumers and secondary decomposers) for maintaining full functionality of C cycle processes. However, understanding of the complex relationships between soil biodiversity and C cycling processes is currently limited by the sheer number of methodological concerns associated with these studies, which can greatly overestimate or underestimate the impact of soil biodiversity on soil C cycling, challenging extrapolation to natural field settings. Future studies should attempt to further elucidate the relative importance of taxonomic diversity (species numbers) versus functional diversity.
Moreover, meta-analyses were used to study the effects of infrastructure proximity on mammal and bird populations (Lopez et al., 2010).
Several studies have shown that biodiversity is being lost at an increased rate as a result of human activities. Infrastructural development is one of the major threats to biodiversity.
Data were gathered from 49 studies on 234 mammal and bird species. The main response by mammals and birds in the vicinity of infrastructure was either avoidance or a reduced population density. The mean species abundance, relative to non-disturbed distances (MSA), was used as the effect size measure. The impact of infrastructure distance on MSA was studied using meta-analyses. Possible sources of heterogeneity in the results of the meta-analysis were explored with meta-regression.
Mammal and bird population densities declined with their proximity to infrastructure. The effect of infrastructure on bird populations extended over distances up to about 1 km, and for mammal populations up to about 5 km. Mammals and birds seemed to avoid infrastructure in open areas over larger distances compared to forested areas, which could be related to the reduced visibility of the infrastructure in forested areas.
The authors did not find a significant effect of traffic intensity on the MSA of birds. Species varied in their response to infrastructure. Raptors were found to be more abundant in the proximity of infrastructure whereas other bird taxa tended to avoid it. Abundances were affected at variable distances from infrastructure: within a few meters for small-sized mammals and up to several hundred meters for large-sized mammals.
The findings show the importance of minimizing infrastructure development for wildlife conservation in relatively undisturbed areas. By combining actual species distributions with the effect distance functions, regions were developed that are sensitive to infrastructure development may be identified. Additionally, the effect distance functions can be used in models in support of decision making on infrastructure planning.
Lastly, Arets et al., (2014) also conducted a meta-analysis study of the effect of global warming on local species richness.
A systematic review of global and regional modelling studies was carried out in which shifts in species distributions under climate change were modelled. These studies included a large range of species groups and biomes worldwide. Based on the model results, the fraction of species was calculated that would remain at a locality in response to projected climate change and related this to the global mean temperature increase (GMTI) that was associated with projected climate change.
Out of 207 articles meeting the search terms used in Web of Science, 21 studies met the selection criteria and were included. This resulted in 239 data points of combinations of global mean temperature increase and effect on local species richness across different species groups and biomes.
Based on this a meta-analysis was carried out to investigate the relation between changes in global mean temperature increase and the fraction of remaining plant and vertebrate species at a geographic location.
The results showed that global mean temperature increases of more than 2°C above pre-industrial levels significantly affect local species richness. Both plants and vertebrate species showed a strong decline in the fraction remaining species with increasing temperature. The effect impacts seemed to be strongest in warm biomes and tended to be smaller in cool biomes. The resulting meta-model can be used to calculate the fraction of remaining species under different climate change scenarios.
REMARKS/CONCLUSION:
The results of the synthesis reveal an important implication. And that is the vital role of meta-analysis in various biodiversity studies. Meta-analysis approach was able to depict the adverse impacts of both anthropogenic and natural disturbance to the species composition and diversity in a community.
Using meta-analysis and regression analysis, it is shown that loss of soil biodiversity can have negative consequences for the soil carbon (C) cycle, significantly reduces plant tissue composition, soil respiration and litter decomposition.
Meta-analysis has also helped the researchers to elucidate that “LOGDIST” was the main explanatory variable for the decline in abundance of bird populations due to infrastructure.
The results of the meta-analysis and regression analysis support the concept that global mean temperatures in the future should not increase beyond 2 oC above pre-industrial levels. This further shows the impact of climate change on a broad range of plant and vertebrate species, biomes and geographic regions.
From these grounds, it is worth mentioning that meta-analysis provides a more global insight into the problem under investigation. This meta-model can readily be used for informed policy making and global biodiversity assessments.
References:
Arets, E. J., Viewer, C. Alkemade, R. (2014). Meta-analysis of the effect of global warming on local species richness.
De Graaf, M.A., Adkins, J., Kardol, P., Throop, H.L. (2015). A meta-analysis of soil biodiversity impacts o the carbon cycle.
DeCoster, J. (2004). Meta-Analysis notes. Department of Psychology, University of Alabama.
Glass, G. V., McGaw, B., & Smith, M. L. (1981). Meta-analysis in Social Research. Beverly Hills, CA:
Lopez, A.B., Alkemade, R., Verweij, P. A. (2010). The impacts of roads and other infrastructures on mammal and bird population: A meta-analysis. Elsevier Biological Conservation Journal. 143, 1307-1316.
Morris, S. B., & DeShon, R. P. (2002). Combining e®ect size estimates in meta-analysis with repeated measures and independent-groups designs. Psychological Methods, 7, 105-125. Sage Publications.
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- Arbeit zitieren
- Hazel Balan (Autor:in), 2018, Meta-Analysis. Its Vital Role in Biodiversity Studies, München, GRIN Verlag, https://www.grin.com/document/428911
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