In experimental systems, it has been shown that biodiversity indices based on traits or phylogeny can outperform species richness as predictors of plant ecosystem function. However, it is unclear ...whether this pattern extends to the function of food webs in natural ecosystems. Here we tested whether zooplankton functional and phylogenetic diversity explains the functioning of 23 natural pond communities. We used two measures of ecosystem function: (1) zooplankton community biomass and (2) phytoplankton abundance (Chl a). We tested for diversity-ecosystem function relationships within and across trophic levels. We found a strong correlation between zooplankton diversity and ecosystem function, whereas local environmental conditions were less important. Further, the positive diversity-ecosystem function relationships were more pronounced for measures of functional and phylogenetic diversity than for species richness. Zooplankton and phytoplankton biomass were best predicted by different indices, suggesting that the two functions are dependent upon different aspects of diversity. Zooplankton community biomass was best predicted by zooplankton trait-based functional richness, while phytoplankton abundance was best predicted by zooplankton phylogenetic diversity. Our results suggest that the positive relationship between diversity and ecosystem function can extend across trophic levels in natural environments, and that greater insight into variation in ecosystem function can be gained by combining functional and phylogenetic diversity measures.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We present results from a high-resolution chemical ionization time-of-flight mass spectrometer (HRToF-CIMS), operated with two different thermal desorption inlets, designed to characterize the gas ...and aerosol composition. Data from two field campaigns at forested sites are shown. Particle volatility distributions are estimated using three different methods: thermograms, elemental formulas, and measured partitioning. Thermogram-based results are consistent with those from an aerosol mass spectrometer (AMS) with a thermal denuder, implying that thermal desorption is reproducible across very different experimental setups. Estimated volatilities from the detected elemental formulas are much higher than from thermograms since many of the detected species are thermal decomposition products rather than actual SOA molecules. We show that up to 65% of citric acid decomposes substantially in the FIGAERO–CIMS, with ∼20% of its mass detected as gas-phase CO2, CO, and H2O. Once thermal decomposition effects on the detected formulas are taken into account, formula-derived volatilities can be reconciled with the thermogram method. The volatility distribution estimated from partitioning measurements is very narrow, likely due to signal-to-noise limits in the measurements. Our findings indicate that many commonly used thermal desorption methods might lead to inaccurate results when estimating volatilities from observed ion formulas found in SOA. The volatility distributions from the thermogram method are likely the closest to the real distributions.
Increases in atmospheric temperature and nutrients from land are thought to be promoting the expansion of harmful cyanobacteria in lakes worldwide, yet to date there has been no quantitative ...synthesis of long‐term trends. To test whether cyanobacteria have increased in abundance over the past ~ 200 years and evaluate the relative influence of potential causal mechanisms, we synthesised 108 highly resolved sedimentary time series and 18 decadal‐scale monitoring records from north temperate‐subarctic lakes. We demonstrate that: (1) cyanobacteria have increased significantly since c. 1800 ce, (2) they have increased disproportionately relative to other phytoplankton, and (3) cyanobacteria increased more rapidly post c. 1945 ce. Variation among lakes in the rates of increase was explained best by nutrient concentration (phosphorus and nitrogen), and temperature was of secondary importance. Although cyanobacterial biomass has declined in some managed lakes with reduced nutrient influx, the larger spatio‐temporal scale of sedimentary records show continued increases in cyanobacteria throughout the north temperate‐subarctic regions.
Climate warming is occurring in concert with other anthropogenic changes to ecosystems. However, it is unknown whether and how warming alters the importance of top-down vs. bottom-up control over ...community productivity and variability. We performed a 16-month factorial experimental manipulation of warming, nutrient enrichment, and predator presence in replicated freshwater pond mesocosms to test their independent and interactive impacts. Warming strengthened trophic cascades from fish to primary producers, and it decreased the impact of eutrophication on the mean and temporal variation of phytoplankton biomass. These impacts varied seasonally, with higher temperatures leading to stronger trophic cascades in winter and weaker algae blooms under eutrophication in summer. Our results suggest that higher temperatures may shift the control of primary production in freshwater ponds toward stronger top-down and weaker bottom-up effects. The dampened temporal variability of algal biomass under eutrophication at higher temperatures suggests that warming may stabilize some ecosystem processes.
As thermal regimes change worldwide, projections of future population and species persistence often require estimates of how population growth rates depend on temperature. These projections rarely ...account for how temporal variation in temperature can systematically modify growth rates relative to projections based on constant temperatures. Here, we tested the hypothesis that time-averaged population growth rates in fluctuating thermal environments differ from growth rates in constant conditions as a consequence of Jensen's inequality, and that the thermal performance curves (TPCs) describing population growth in fluctuating environments can be predicted quantitatively based on TPCs generated in constant laboratory conditions. With experimental populations of the green alga Tetraselmis tetrahele, we show that nonlinear averaging techniques accurately predicted increased as well as decreased population growth rates in fluctuating thermal regimes relative to constant thermal regimes. We extrapolate from these results to project critical temperatures for population growth and persistence of 89 phytoplankton species in naturally variable thermal environments. These results advance our ability to predict population dynamics in the context of global change.
Our understanding of the relationship between biodiversity and ecosystem functioning (BEF) applies mainly to fine spatial scales. New research is required if we are to extend this knowledge to ...broader spatial scales that are relevant for conservation decisions. Here, we use simulations to examine conditions that generate scale dependence of the BEF relationship. We study scale by assessing how the BEF relationship (slope and
) changes when habitat patches are spatially aggregated. We find three ways for the BEF relationship to be scale-dependent: (i) variation among local patches in local (α) diversity, (ii) spatial variation in the local BEF relationship and (iii) incomplete compositional turnover in species composition among patches. The first two cause the slope of the BEF relationship to increase moderately with spatial scale, reflecting nonlinear averaging of spatial variation in diversity or the BEF relationship. The third mechanism results in much stronger scale dependence, with the BEF relationship increasing in the rising portion of the species area relationship, but then decreasing as it saturates. An analysis of data from the Cedar Creek grassland BEF experiment revealed a positive but saturating slope of the relationship with scale. Overall, our findings suggest that the BEF relationship is likely to be scale dependent.
Abstract
Time is running out to limit further devastating losses of biodiversity and nature's contributions to humans. Addressing this crisis requires accurate predictions about which species and ...ecosystems are most at risk to ensure efficient use of limited conservation and management resources. We review existing biodiversity projection models and discover problematic gaps. Current models usually cannot easily be reconfigured for other species or systems, omit key biological processes, and cannot accommodate feedbacks with Earth system dynamics. To fill these gaps, we envision an adaptable, accessible, and universal biodiversity modeling platform that can project essential biodiversity variables, explore the implications of divergent socioeconomic scenarios, and compare conservation and management strategies. We design a roadmap for implementing this vision and demonstrate that building this biodiversity forecasting platform is possible and practical.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The biodiversity and ecosystem functioning (BEF) relationship is expected to be scale-dependent. The autocorrelation of environmental heterogeneity is hypothesized to explain this scale dependence ...because it influences how quickly biodiversity accumulates over space or time. However, this link has yet to be demonstrated in a formal model. Here, we use a Lotka-Volterra competition model to simulate community dynamics when environmental conditions vary across either space or time. Species differ in their optimal environmental conditions, which results in turnover in community composition. We vary biodiversity by modelling communities with different sized regional species pools and ask how the amount of biomass per unit area depends on the number of species present, and the spatial or temporal scale at which it is measured. We find that more biodiversity is required to maintain functioning at larger temporal and spatial scales. The number of species required increases quickly when environmental autocorrelation is low, and slowly when autocorrelation is high. Both spatial and temporal environmental heterogeneity lead to scale dependence in BEF, but autocorrelation has larger impacts when environmental change is temporal. These findings show how the biodiversity required to maintain functioning is expected to increase over space and time.
Metacommunity theory provides an understanding of how spatial processes determine the structure and function of communities at local and regional scales. Although metacommunity theory has considered ...trophic dynamics in the past, it has been performed idiosyncratically with a wide selection of possible dynamics. Trophic metacommunity theory needs a synthesis of a few influential axis to simplify future predictions and tests. We propose an extension of metacommunity ecology that addresses these shortcomings by incorporating variability among trophic levels in ‘spatial use properties’. We define ‘spatial use properties’ as a set of traits (dispersal, migration, foraging and spatial information processing) that set the spatial and temporal scales of organismal movement, and thus scales of interspecific interactions. Progress towards a synthetic predictive framework can be made by (1) documenting patterns of spatial use properties in natural food webs and (2) using theory and experiments to test how trophic structure in spatial use properties affects metacommunity dynamics.
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