Non‐native species are now common in community assemblages, but the influence of multiple introductions on ecosystem functioning remains poorly understood. In highly invaded systems, one promising approach is to use functional traits to scale measured individuals’ effects on ecosystem function up to the community level. This approach assumes that functional traits provide a common currency among species to relate individuals to ecosystem functioning. The goals of this study were to (i) test whether the relationship between body size and ecosystem functioning (per capita nutrient recycling) was best described by general or species‐specific scaling models; (ii) relate community structure (total biomass, average body size, non‐native dominance) to aggregated, community‐level nutrient recycling rates and ratios; and (iii) determine whether conclusions regarding the relationships between community structure and aggregate ecosystem functioning differed between species‐specific and general scaling approaches. By combining experimental incubations and field surveys, we compare consumer‐mediated nutrient recycling of fish communities along a non‐native dominance gradient in the Verde River watershed of central Arizona, According to species‐specific models, stream fish communities recycled 1–12 mmol Community structure influenced aggregate nutrient recycling, but specific conclusions depended on the scaling approach. Total biomass explained much of the among‐community variation in aggregate Study results indicate that shifting fish community structure can substantially alter ecosystem functioning in this river system. However, some inferred relationships between community structure and aggregate nutrient recycling varied depending on whether general or species‐specific scaling approaches were taken. Although trait‐based approaches to link environmental change, community structure and ecosystem function hold much promise, it will be important to consider when species‐specific versus general models are necessary to scale from individuals to ecosystems.
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.
- NSF-PAR ID:
- 10453848
- Publisher / Repository:
- Wiley-Blackwell
- Date Published:
- Journal Name:
- Journal of Ecology
- Volume:
- 109
- Issue:
- 3
- ISSN:
- 0022-0477
- Format(s):
- Medium: X Size: p. 1549-1560
- Size(s):
- ["p. 1549-1560"]
- Sponsoring Org:
- National Science Foundation
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Abstract USA . Data from ˜340 field‐sampled freshwater fish demonstrated support for general allometric relationships predicted by the metabolic theory of ecology (NH 4‐N scaling coefficient = 0.72 [0.64–0.80];PO 4‐P = 0.67 [0.47–0.86]). However, the best‐fit models for N and P included species‐specific random effects for both allometric slopes and intercepts.NH 4‐N/hr (median = 2.8 mmol/hr) and 0.02–0.74 mmolPO 4‐P/hr (median = 0.07 mmol/hr) at N:P ratios between 13.3 and 83.5 (median = 28.8). General models generated similar estimates forNH 4‐N recycling but less accurate estimates forPO 4‐P. Stochastic simulations that incorporated error around allometric parameter estimates led to qualitatively similar but larger differences between general and species‐specific results.NH 4‐N andPO 4‐P for both model types, whereas non‐native dominance alone best predicted variation in aggregate N:P. Surprisingly, species‐specific and general models both reached significant yet quantitatively opposing conclusions regarding the relationship between N:P supply and non‐native dominance. -
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Abstract Aim Ecological patterns and process change across spatial, temporal and taxonomic scales. This confounds comparisons between modern and fossil communities, which are sampled across very different scales, especially temporal ones. We use a recent bone dataset (i.e., “death assemblages”) from a modern ecosystem to explore spatial, temporal and taxonomic scaling in biodiversity assessments. Our ultimate goal is to create a model based on these scaling relationships to facilitate meaningful comparisons between modern and fossil communities.
Location Amboseli National Park, southern Kenya.
Time period Mid‐1960 s to present day.
Major taxa studied Large mammals (>1 kg).
Methods We implemented a random placement null model and used model selection methods to investigate how species richness at Amboseli scales as a function of time and area [i.e., the species–time–area relationship (STAR) model]. We then analysed how the model coefficients change at different taxonomic scales (i.e., genus, family, order).
Results In agreement with previous studies, we find species richness scales positively with time and area but with a negative interaction between the two. Rates of richness turnover decrease as taxonomic scale increases.
Main conclusions We hypothesize that decreasing rates of turnover with increasing spatial and/or temporal scale are caused by taking progressively larger samples from a species pool that is changing at a slower rate relative to turnover at the scale of sampling. Because increasing area and time are simply alternative ways of uncovering the species pool, increased time‐averaging of communities results in a more spatially averaged ecological signal. Increasing taxonomic scale causes turnover rates to decrease because of how lower‐level taxa are aggregated into coarser, higher‐level ones. The STAR model presents a framework for extrapolating and comparing richness between small‐scale modern and large‐scale fossil communities, as well as a means to understand the general processes involved with changing scale.
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Positive biodiversity–ecosystem functioning (BEF) relationships observed in experiments can be challenging to identify in natural communities. Freshwater animal communities are disproportionately harmed by global change that results in accelerated species loss. Understanding how animal-mediated ecosystems functions may change as a result of global change can help determine whether biodiversity or species-specific conservation will be effective at maintaining function. Unionid mussels represent half of imperiled species in freshwater ecosystems globally and perform important ecological functions such as water filtration and nutrient recycling. We explored BEF relationships for 22 naturally assembled mussel aggregations spanning three river basins. We used the Price equation to partition the contributions of species richness, composition, and context dependent interactions to two functions of interests: spatially-explicit standing-stock biomass (indirect proxy for function) and species-specific nitrogen (N) excretion rates (direct measure of N recycling). Random and non-random species loss each reduced biomass and N recycling. Many rare species with low contributions to biomass contributed to standing-stock biomass in all basins. Widespread species had variable function across sites, such that context dependent effects (CDEs) outweighed richness effects on standing-stock biomass in two basins, and were similar to richness effects in the third. Richness effects outweighed CDEs for N recycling. Thus, many species contributed a low proportion to overall N-recycling; a product we attribute to the high evenness and functional effect trait diversity associated with these communities. The loss of low-functioning species reduced the function of persisting species. This novel result using observational data adds evidence that positive species interactions, such as interspecific facilitation, may be a mechanism by which biodiversity enhances ecosystem functions. Our work stresses the importance of evaluating species-specific contributions to functions in diverse systems, such as nutrient cycling when maintaining specific animal-mediated functions is a management goal because indirect proxies may not completely characterize BEF relationships.more » « less
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Abstract Clark et al. (2019) sought to extend the Loreau–Hector partitioning scheme by showing how to estimate selection and complementarity effects from an incomplete sample of species. We demonstrate that their approach suffers from serious conceptual and mathematical errors. Instead of finding unbiased estimators for a finite population, they inserted ad hoc correction factors into unbiased parameter estimators for an infinite population without any mathematical justification in order to force the sample estimators of an infinite population to converge to the true finite population parameter values as sample size
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Clark et al. also state that their method can be used to compare distinct experiments characterized by different species and diversity levels, or extrapolate from biodiversity experiments to natural systems. This is incorrect because relative yields are not a property of individual species like monoculture yields but an emergent and specific feature of an experimental community. As such, two experimental communities, even when overlapping significantly in species, are incommensurable for the purpose of predicting relative yields. In other words, different experimental communities are not equivalent to different samples taken from the same statistical population.
Finally, Clark et al. incorrectly claim that both the original Loreau–Hector partitioning scheme and their extension work for any baseline despite the fact that recent research has shown that a nonlinear relationship between monoculture density and ecosystem functioning will likely inflate the net biodiversity effect in plant systems, and will always lead to spurious measurements of complementarity and selection.
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Abstract After 25 years of biodiversity experiments, it is clear that higher biodiversity (B) plant communities are usually more productive and often have greater ecosystem functioning (EF) than lower diversity communities. However, the mechanisms underlying this positive biodiversity
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Importantly, mathematically partitioned complementarity effects include multiple facilitative mechanisms, including dilution of species‐specific pathogens, positive changes in soil nutrient cycling, associational defence and microclimate amelioration.
Synthesis . This Special Feature takes an experimental and mechanistic approach to teasing out the facilitative mechanisms that underlie positive BEF relationships. As an example, we demonstrate diversity‐driven changes in microclimate amelioration. Articles in this Special Feature explore photoinhibition, experimental manipulations of microclimate, lidar examinations of plant canopy effects and higher‐order trophic interactions as facilitative mechanisms behind classic BEF processes. We emphasize the need for future BEF experiments to disentangle the facilitative mechanisms that are interlinked with niche complementarity to better understand the fundamental processes by which diversity regulates life on Earth.
