An official website of the United States government
Abstract Global biodiversity is declining at rates faster than at any other point in human history. Experimental manipulations at small spatial scales have demonstrated that communities with fewer species consistently produce less biomass than higher diversity communities. Understanding the consequences of the global extinction crisis for ecosystem functioning requires understanding how local experimental results are likely to change with increasing spatial and temporal scales and from experiments to naturally assembled systems.Scaling across time and space in a changing world requires baseline predictions. Here, we provide a graphical null model for area scaling of biodiversity–ecosystem functioning relationships using observed macroecological patterns: the species–area curve and the biomass–area curve. We use species–area and biomass–area curves to predict how species richness–biomass relationships are likely to change with increasing sampling extent. We then validate these predictions with data from two naturally assembled ecosystems: a Minnesota savanna and a Panamanian tropical dry forest.Our graphical null model predicts that biodiversity–ecosystem functioning relationships are scale‐dependent. However, we note two important caveats. First, our results indicate an apparent contradiction between predictions based on measurements in biodiversity–ecosystem functioning experiments and from scaling theory. When ecosystem functioning is measured as per unit area (e.g. biomass per m2), as is common in biodiversity–ecosystem functioning experiments, the slope of the biodiversity ecosystem functioning relationship should decrease with increasing scale. Alternatively, when ecosystem functioning is not measured per unit area (e.g. summed total biomass), as is common in scaling studies, the slope of the biodiversity–ecosystem functioning relationship should increase with increasing spatial scale. Second, the underlying macroecological patterns of biodiversity experiments are predictably different from some naturally assembled systems. These differences between the underlying patterns of experiments and naturally assembled systems may enable us to better understand when patterns from biodiversity–ecosystem functioning experiments will be valid in naturally assembled systems.Synthesis. This paper provides a simple graphical null model that can be extended to any relationship between biodiversity and any ecosystem functioning across space or time. Furthermore, these predictions provide crucial insights into how and when we may be able to extend results from small‐scale biodiversity experiments to naturally assembled regional and global ecosystems where biodiversity is changing.
more »
« less
Shifting macroecological patterns and static theory failure in a stressed alpine plant community
Abstract Accumulating evidence suggests that ecological communities undergoing change in response to either anthropogenic or natural disturbances exhibit macroecological patterns that differ from those observed in similar types of communities in relatively undisturbed sites. In contrast to such cross‐site comparisons, however, there are few empirical studies of shifts over time in the shapes of macroecological patterns. Here, we provide a dramatic example of a plant community in which the species–area relationship and the species‐abundance distribution change markedly over a period of six years. These patterns increasingly deviate from the predictions of the maximum entropy theory of ecology (METE), which successfully predicts macroecological patterns in relatively static systems. The error in the species–area relationship prediction additionally correlates over time with increased stress measured as mortality minus recruitment, providing a link between demography and the failure of macroecological theory. Information on the dynamic state of an ecosystem inferred from snapshot measurements of macroecological community structure can potentially assist in identifying causes and consequences of disturbance and extending the domain of current theories and models to disturbed ecosystems.
more »
« less
- Award ID(s):
- 1751380
- PAR ID:
- 10360023
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Ecosphere
- Volume:
- 12
- Issue:
- 6
- ISSN:
- 2150-8925
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract The Maximum Entropy Theory of Ecology (METE) predicts the shapes of macroecological metrics in relatively static ecosystems, across spatial scales, taxonomic categories and habitats, using constraints imposed by static state variables. In disturbed ecosystems, however, with time‐varying state variables, its predictions often fail. We extend macroecological theory from static to dynamic by combining the MaxEnt inference procedure with explicit mechanisms governing disturbance. In the static limit, the resulting theory, DynaMETE, reduces to METE but also predicts a new scaling relationship among static state variables. Under disturbances, expressed as shifts in demographic, ontogenic growth or migration rates, DynaMETE predicts the time trajectories of the state variables as well as the time‐varying shapes of macroecological metrics such as the species abundance distribution and the distribution of metabolic rates over individuals. An iterative procedure for solving the dynamic theory is presented. Characteristic signatures of the deviation from static predictions of macroecological patterns are shown to result from different kinds of disturbance. By combining MaxEnt inference with explicit dynamical mechanisms of disturbance, DynaMETE is a candidate theory of macroecology for ecosystems responding to anthropogenic or natural disturbances.more » « less
-
Abstract AimCommunities contain more individuals of small species and fewer individuals of large species. According to the ‘metabolic theory of ecology’, the relationship of log mean abundance with log mean body size across communities should exhibit a slope of −3/4 that is invariant across environmental conditions. Here, we investigate whether this slope is indeed invariant or changes systematically across gradients in temperature, resource availability and predation pressure. Location1048 lakes across the USA. Time Period2012. Major Taxa StudiedPhytoplankton. ResultsWe found that the size–abundance relationship across all sampled phytoplankton communities was significantly lower than −3/4 and near −1 overall. More importantly, we found strong evidence that the environment affects the slope: it varies between −0.33 and −0.93 across interacting gradients of temperature, resource (phosphorus) supply and zooplankton predation pressure. Therefore, phytoplankton communities have orders of magnitude more small or large cells depending on environmental conditions across geographical locations. ConclusionOur results emphasise the importance of the environmental factors' effect on macroecological patterns that arise through physiological and ecological processes. An investigation of the mechanisms underlying the link between individual energetics constrain and macroecological patterns would allow to predict how global warming and changes in nutrients will alter large‐scale ecological patterns in the future.more » « less
-
Across diverse microbiotas, species abundances vary in time with distinctive statistical behaviors that appear to generalize across hosts, but the origins and implications of these patterns remain unclear. Here, we show that many of these macroecological patterns can be quantitatively recapitulated by a simple class of consumer-resource models, in which the metabolic capabilities of different species are randomly drawn from a common statistical distribution. Our model parametrizes the consumer-resource properties of a community using only a small number of global parameters, including the total number of resources, typical resource fluctuations over time, and the average overlap in resource-consumption profiles across species. We show that variation in these macroscopic parameters strongly affects the time series statistics generated by the model, and we identify specific sets of global parameters that can recapitulate macroecological patterns across wide-ranging microbiotas, including the human gut, saliva, and vagina, as well as mouse gut and rice, without needing to specify microscopic details of resource consumption. These findings suggest that resource competition may be a dominant driver of community dynamics. Our work unifies numerous time series patterns under a simple model, and provides an accessible framework to infer macroscopic parameters of effective resource competition from longitudinal studies of microbial communities.more » « less
-
The scaling relationship observed between species richness and the geographical area sampled (i.e. the species-area relationship (SAR)) is a widely recognized macroecological relationship. Recently, this theory has been extended to trophic interactions, suggesting that geographical area may influence the structure of species interaction networks (i.e. network-area relationships (NARs)). Here, we use a global dataset of host–helminth parasite interactions to test existing predictions from macroecological theory. Scaling between single locations to the global host–helminth network by sequentially adding networks together, we find support that geographical area influences species richness and the number of species interactions in host–helminth networks. However, species-area slopes were larger for host species relative to their helminth parasites, counter to theoretical predictions. Lastly, host–helminth network modularity—capturing the tendency of the network to form into separate subcommunities—decreased with increasing area, also counter to theoretical predictions. Reconciling this disconnect between existing theory and observed SAR and NAR will provide insight into the spatial structuring of ecological networks, and help to refine theory to highlight the effects of network type, species distributional overlap, and the specificity of trophic interactions on NARs.more » « less
