Temperature and biodiversity changes occur in concert, but their joint effects on ecological stability of natural food webs are unknown. Here, we assess these relationships in 19 planktonic food webs. We estimate stability as structural stability (using the volume contraction rate) and temporal stability (using the temporal variation of species abundances). Warmer temperatures were associated with lower structural and temporal stability, while biodiversity had no consistent effects on either stability property. While species richness was associated with lower structural stability and higher temporal stability, Simpson diversity was associated with higher temporal stability. The responses of structural stability were linked to disproportionate contributions from two trophic groups (predators and consumers), while the responses of temporal stability were linked both to synchrony of all species within the food web and distinctive contributions from three trophic groups (predators, consumers, and producers). Our results suggest that, in natural ecosystems, warmer temperatures can erode ecosystem stability, while biodiversity changes may not have consistent effects.
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Abstract The measurement of uncharacterized pools of biological molecules through techniques such as metabarcoding, metagenomics, metatranscriptomics, metabolomics, and metaproteomics produces large, multivariate datasets. Analyses of these datasets have successfully been borrowed from community ecology to characterize the molecular diversity of samples ( ɑ -diversity) and to assess how these profiles change in response to experimental treatments or across gradients ( β -diversity). However, sample preparation and data collection methods generate biases and noise which confound molecular diversity estimates and require special attention. Here, we examine how technical biases and noise that are introduced into multivariate molecular data affect the estimation of the components of diversity (i.e., total number of different molecular species, or entities; total number of molecules; and the abundance distribution of molecular entities). We then explore under which conditions these biases affect the measurement of ɑ - and β -diversity and highlight how novel methods commonly used in community ecology can be adopted to improve the interpretation and integration of multivariate molecular data.more » « less
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The inclusion of community voices in research is important. Over the years, research training programs have continued to emphasize that engagement with communities at the focus of research can promote thoughtful, sensitive designs ( Rivera et al., 2004 ). In this paper, we discuss a method for youth participation in the research process. In an attempt to move beyond “staged and superficial” participation in gathering youth perspectives, we advocate for including co-researchers in the development and modification of fundamental aspects of the research process, from data analysis to the development of additional research questions and collection methods ( Guishard & Tuck, 2013 ). In the course of a study designed to enroll middle school students in participatory co-design sessions ( Cahill, 2007 ) to aid in the development of educational technologies, it became apparent that our youth participants, as co-researchers, could also aid in the development, analysis, and coding of anonymized interview transcripts; development of themes; and creation of models for behaviors found in the transcripts ( Docan-Morgan, 2010 ; Luchtenberg et al., 2020 ). Thus, this paper presents a practical example of a co-research process that includes youth participants, with an emphasis on training in qualitative coding and the fundamentals of research design.more » « less
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Global change drivers, such as anthropogenic nutrient inputs, are increasing globally. Nutrient deposition simultaneously alters plant biodiversity, species composition and ecosystem processes like aboveground biomass production. These changes are underpinned by species extinction, colonisation and shifting relative abundance. Here, we use the Price equation to quantify and link the contributions of species that are lost, gained or that persist to change in aboveground biomass in 59 experimental grassland sites. Under ambient (control) conditions, compositional and biomass turnover was high, and losses (i.e. local extinctions) were balanced by gains (i.e. colonisation). Under fertilisation, the decline in species richness resulted from increased species loss and decreases in species gained. Biomass increase under fertilisation resulted mostly from species that persist and to a lesser extent from species gained. Drivers of ecological change can interact relatively independently with diversity, composition and ecosystem processes and functions such as aboveground biomass due to the individual contributions of species lost, gained or persisting.more » « less
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Abstract Human impacts have led to dramatic biodiversity change which can be highly scale‐dependent across space and time. A primary means to manage these changes is via passive (here, the removal of disturbance) or active (management interventions) ecological restoration. The recovery of biodiversity, following the removal of disturbance, is often incomplete relative to some kind of reference target. The magnitude of recovery of ecological systems following disturbance depends on the landscape matrix and many contingent factors. Inferences about recovery after disturbance and biodiversity change depend on the temporal and spatial scales at which biodiversity is measured.
We measured the recovery of biodiversity and species composition over 33 years in 17 temperate grasslands abandoned after agriculture at different points in time, collectively forming a chronosequence since abandonment from 1 to 80 years. We compare these abandoned sites with known agricultural land‐use histories to never‐disturbed sites as relative benchmarks. We specifically measured aspects of diversity at the local plot‐scale (α‐scale, 0.5 m2) and site‐scale (γ‐scale, 10 m2), as well as the within‐site heterogeneity (β‐diversity) and among‐site variation in species composition (turnover and nestedness).
At our α‐scale, sites recovering after agricultural abandonment only had 70% of the plant species richness (and ~30% of the evenness), compared to never‐ploughed sites. Within‐site β‐diversity recovered following agricultural abandonment to around 90% after 80 years. This effect, however, was not enough to lead to recovery at our γ‐scale. Richness in recovering sites was ~65% of that in remnant never‐ploughed sites. The presence of species characteristic of the never‐disturbed sites increased in the recovering sites through time. Forb and legume cover declines in years since abandonment, relative to graminoid cover across sites.
Synthesis. We found that, during the 80 years after agricultural abandonment, old fields did not recover to the level of biodiversity in remnant never‐ploughed sites at any scale. β‐diversity recovered more than α‐scale or γ‐scale. Plant species composition recovered, but not completely, over time, and some species groups increased their cover more than others. Patterns of ecological recovery in degraded ecosystems across space and long time‐scales can inform targeted active restoration interventions and perhaps, lead to better outcomes. -
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Abstract Diversity and nitrogen addition have positive relationships with plant productivity, yet climate‐induced changes in water availability threaten to upend these established relationships. Using long‐term data from three experiments in a mesic grassland (ranging from 17 to 34 yr of data), we tested how the effects of species richness and nitrogen addition on community‐level plant productivity changed as a function of annual fluctuations in water availability using growing season precipitation and the Standardized Precipitation‐Evapotranspiration Index (SPEI). While results varied across experiments, our findings demonstrate that water availability can magnify the positive effects of both biodiversity and nitrogen addition on productivity. These results suggest that productivity responses to anthropogenic species diversity loss and increasing nitrogen deposition could depend on precipitation regimes, highlighting the importance of testing interactions between multiple global change drivers.
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Feedbacks are an essential feature of resilient socio-economic systems, yet the feedbacks between biodiversity, ecosystem services and human wellbeing are not fully accounted for in global policy efforts that consider future scenarios for human activities and their consequences for nature. Failure to integrate feedbacks in our knowledge frameworks exacerbates uncertainty in future projections and potentially prevents us from realizing the full benefits of actions we can take to enhance sustainability. We identify six scientific research challenges that, if addressed, could allow future policy, conservation and monitoring efforts to quantitatively account for ecosystem and societal consequences of biodiversity change. Placing feedbacks prominently in our frameworks would lead to (i) coordinated observation of biodiversity change, ecosystem functions and human actions, (ii) joint experiment and observation programmes, (iii) more effective use of emerging technologies in biodiversity science and policy, and (iv) a more inclusive and integrated global community of biodiversity observers. To meet these challenges, we outline a five-point action plan for collaboration and connection among scientists and policymakers that emphasizes diversity, inclusion and open access. Efforts to protect biodiversity require the best possible scientific understanding of human activities, biodiversity trends, ecosystem functions and—critically—the feedbacks among them.more » « less
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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.
