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Ecological strategies shape the insurance potential of biodiversity.

Matias MG, Combe M, Barbera C, Mouquet N - Front Microbiol (2013)

Bottom Line: We present here a simple experimental study that illustrates how different ecological strategies (i.e., generalists vs. specialists) can shape the biodiversity-insurance relationship.We discuss our results in context with simple theoretical predictions and propose future directions for biological insurance theory.We argue that beyond species richness itself, it is essential to incorporate the distribution of ecological strategies across relevant environmental gradients as predictors of the insurance potential of biodiversity in natural ecosystems.

View Article: PubMed Central - PubMed

Affiliation: Institut des Sciences de l'Evolution, UMR CNRS-UM2 5554, Université Montpellier 2 Montpellier cedex 05, France.

ABSTRACT
Biodiversity is thought to provide insurance for ecosystem functioning under heterogeneous environments; however, such insurance potential is under serious threat following unprecedented loss of biodiversity. One of the key mechanism underlying ecological insurance is that niche differentiation allows asynchronous responses to fluctuating environments, although the role of different ecological strategies (e.g., specialists vs. generalists) has yet to be formally evaluated. We present here a simple experimental study that illustrates how different ecological strategies (i.e., generalists vs. specialists) can shape the biodiversity-insurance relationship. We assembled microcosm of generalists and specialist bacteria over a gradient of salinity and found that, bacterial communities made up of generalists were more productive and more stable over time under environmental fluctuations. We discuss our results in context with simple theoretical predictions and propose future directions for biological insurance theory. We argue that beyond species richness itself, it is essential to incorporate the distribution of ecological strategies across relevant environmental gradients as predictors of the insurance potential of biodiversity in natural ecosystems.

No MeSH data available.


Related in: MedlinePlus

General theoretical predictions of temporal mean productivity and its coefficient of variation. Predictions are presented for weak (θ = 0.2; panels A and B) and strong (θ = 2; panels C and D) trade-offs. Here, we ran simulations with all combinations of 10 levels of niche width (σ; from 2 to 100) and 10 levels of species richness (from 1 to 10); for each combination of parameters, we ran 100 independent simulations. Additional parameters are explained in detail in the “Appendix Methods: Model Description.” Darker cells indicate greater values of temporal mean productivity or coefficient of variation (CV).
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FA3: General theoretical predictions of temporal mean productivity and its coefficient of variation. Predictions are presented for weak (θ = 0.2; panels A and B) and strong (θ = 2; panels C and D) trade-offs. Here, we ran simulations with all combinations of 10 levels of niche width (σ; from 2 to 100) and 10 levels of species richness (from 1 to 10); for each combination of parameters, we ran 100 independent simulations. Additional parameters are explained in detail in the “Appendix Methods: Model Description.” Darker cells indicate greater values of temporal mean productivity or coefficient of variation (CV).

Mentions: Simple hypothetical predictions can be obtained using a phenomological model of the insurance effects. To do so we built a simple model of community dynamics across a continuum of diversity and strategies, varying the strength of the trade-off between specialization (i.e., niche width) and productivity (Figure 3A; see full description of the model and simulations in “Appendix Methods: Model Description”). We generated theoretical predictions of community productivity and insurance potential of biodiversity for assemblages with different levels of species richness and ecological strategies (see Figures 3B,C; see also Appendix Figure A2). We found that the species richness-temporal variability relationship in assemblages of generalists had higher intercept and slope than those made of specialists (Figure 3C; Appendix Figure A3). Assemblages made up of generalist species were better at insuring community productivity than assemblages made up of specialists that need greater numbers to maintain the insurance potential. Furthermore, the strength of the specialization-productivity trade-off (i.e., the cost paid by the species for being either generalist or specialist) alters the BEF (i.e., reduces the intercept) relationship in assemblages of generalists (as in Gravel et al., 2011). However, the strength of the specialization-productivity trade-off did not have a major effect on species diversity-temporal variability relationship of both strategies (Figure A3), which suggests that the presence/absence of different strategies, rather than the specialization trade-offs, might be determinant for estimating the insurance potential of biodiversity.


Ecological strategies shape the insurance potential of biodiversity.

Matias MG, Combe M, Barbera C, Mouquet N - Front Microbiol (2013)

General theoretical predictions of temporal mean productivity and its coefficient of variation. Predictions are presented for weak (θ = 0.2; panels A and B) and strong (θ = 2; panels C and D) trade-offs. Here, we ran simulations with all combinations of 10 levels of niche width (σ; from 2 to 100) and 10 levels of species richness (from 1 to 10); for each combination of parameters, we ran 100 independent simulations. Additional parameters are explained in detail in the “Appendix Methods: Model Description.” Darker cells indicate greater values of temporal mean productivity or coefficient of variation (CV).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3539934&req=5

FA3: General theoretical predictions of temporal mean productivity and its coefficient of variation. Predictions are presented for weak (θ = 0.2; panels A and B) and strong (θ = 2; panels C and D) trade-offs. Here, we ran simulations with all combinations of 10 levels of niche width (σ; from 2 to 100) and 10 levels of species richness (from 1 to 10); for each combination of parameters, we ran 100 independent simulations. Additional parameters are explained in detail in the “Appendix Methods: Model Description.” Darker cells indicate greater values of temporal mean productivity or coefficient of variation (CV).
Mentions: Simple hypothetical predictions can be obtained using a phenomological model of the insurance effects. To do so we built a simple model of community dynamics across a continuum of diversity and strategies, varying the strength of the trade-off between specialization (i.e., niche width) and productivity (Figure 3A; see full description of the model and simulations in “Appendix Methods: Model Description”). We generated theoretical predictions of community productivity and insurance potential of biodiversity for assemblages with different levels of species richness and ecological strategies (see Figures 3B,C; see also Appendix Figure A2). We found that the species richness-temporal variability relationship in assemblages of generalists had higher intercept and slope than those made of specialists (Figure 3C; Appendix Figure A3). Assemblages made up of generalist species were better at insuring community productivity than assemblages made up of specialists that need greater numbers to maintain the insurance potential. Furthermore, the strength of the specialization-productivity trade-off (i.e., the cost paid by the species for being either generalist or specialist) alters the BEF (i.e., reduces the intercept) relationship in assemblages of generalists (as in Gravel et al., 2011). However, the strength of the specialization-productivity trade-off did not have a major effect on species diversity-temporal variability relationship of both strategies (Figure A3), which suggests that the presence/absence of different strategies, rather than the specialization trade-offs, might be determinant for estimating the insurance potential of biodiversity.

Bottom Line: We present here a simple experimental study that illustrates how different ecological strategies (i.e., generalists vs. specialists) can shape the biodiversity-insurance relationship.We discuss our results in context with simple theoretical predictions and propose future directions for biological insurance theory.We argue that beyond species richness itself, it is essential to incorporate the distribution of ecological strategies across relevant environmental gradients as predictors of the insurance potential of biodiversity in natural ecosystems.

View Article: PubMed Central - PubMed

Affiliation: Institut des Sciences de l'Evolution, UMR CNRS-UM2 5554, Université Montpellier 2 Montpellier cedex 05, France.

ABSTRACT
Biodiversity is thought to provide insurance for ecosystem functioning under heterogeneous environments; however, such insurance potential is under serious threat following unprecedented loss of biodiversity. One of the key mechanism underlying ecological insurance is that niche differentiation allows asynchronous responses to fluctuating environments, although the role of different ecological strategies (e.g., specialists vs. generalists) has yet to be formally evaluated. We present here a simple experimental study that illustrates how different ecological strategies (i.e., generalists vs. specialists) can shape the biodiversity-insurance relationship. We assembled microcosm of generalists and specialist bacteria over a gradient of salinity and found that, bacterial communities made up of generalists were more productive and more stable over time under environmental fluctuations. We discuss our results in context with simple theoretical predictions and propose future directions for biological insurance theory. We argue that beyond species richness itself, it is essential to incorporate the distribution of ecological strategies across relevant environmental gradients as predictors of the insurance potential of biodiversity in natural ecosystems.

No MeSH data available.


Related in: MedlinePlus