happiness, inequality, Latin America, subjective well-being,

No abstract

The cost and difficulty of manipulative field studies makes low statistical power a pervasive issue throughout most ecological subdisciplines. Ecologists are already aware that small sample sizes increase the probability of committing Type II errors. In this article, we address a relatively unknown problem with low power: underpowered studies must overestimate small effect sizes in order to achieve statistical significance. First, we describe how low replication coupled with weak effect sizes leads to Type M errors, or exaggerated effect sizes. We then conduct a meta-analysis to determine the average statistical power and Type M error rate for manipulative field experiments that address important questions related to global change; global warming, biodiversity loss, and drought. Finally, we provide recommendations for avoiding Type M errors and constraining estimates of effect size from underpowered studies.

Climate extremes will elicit responses from the individual to the ecosystem level. However, only recently have ecologists begun to synthetically assess responses to climate extremes across multiple levels of ecological organization. We review the literature to examine how plant responses vary and interact across levels of organization, focusing on how individual, population and community responses may inform ecosystem-level responses in herbaceous and forest plant communities. We report a high degree of variability at the individual level, and a consequential inconsistency in the translation of individual or population responses to directional changes in community- or ecosystem-level processes. The scaling of individual or population responses to community or ecosystem responses is often predicated upon the functional identity of the species in the community, in particular, the dominant species. Furthermore, the reported stability in plant community composition and functioning with respect to extremes is often driven by processes that operate at the community level, such as species niche partitioning and compensatory responses during or after the event. Future research efforts would benefit from assessing ecological responses across multiple levels of organization, as this will provide both a holistic and mechanistic understanding of ecosystem responses to increasing climatic variability. This article is part of the themed issue ‘Behavioural, ecological and evolutionary responses to extreme climatic events’.

In semiarid regions, vegetation constraints on plant growth responses to precipitation (PPT) are hypothesized to place an upper limit on net primary productivity (NPP), leading to predictions of future shifts from currently defined linear to saturating NPP–PPT relationships as increases in both dry and wet PPT extremes occur. We experimentally tested this prediction by imposing a replicated gradient of growing season PPT (GSP, n = 11 levels, n = 4 replicates), ranging from the driest to wettest conditions in the 75‐yr climate record, within a semiarid grassland. We focused on responses of two key ecosystem processes: aboveground NPP (ANPP) and soil respiration (Rs). ANPP and Rs both exhibited greater relative responses to wet vs. dry GSP extremes, with a linear relationship consistently best explaining the response of both processes to GSP. However, this responsiveness to GSP peaked at moderate levels of extremity for both processes, and declined at the most extreme GSP levels, suggesting that greater sensitivity of ANPP and Rs to wet vs. dry conditions may diminish under increased magnitudes of GSP extremes. Underlying these responses was rapid plant compositional change driven by increased forb production and cover as GSP transitioned to extreme wet conditions. This compositional shift increased the magnitude of ANPP responses to wet GSP extremes, as well as the slope and variability explained in the ANPP–GSP relationship. Our findings suggest that rapid plant compositional change may act as a mediator of semiarid ecosystem responses to predicted changes in GSP extremes.

In terrestrial ecosystems, climate change forecasts of increased frequencies and magnitudes of wet and dry precipitation anomalies are expected to shift precipitation–net primary productivity (PPT–NPP) relationships from linear to nonlinear. Less understood, however, is how future changes in the duration of PPT anomalies will alter PPT–NPP relationships. A review of the literature shows strong potential for the duration of wet and dry PPT anomalies to impact NPP and to interact with the magnitude of anomalies. Within semi‐arid and mesic grassland ecosystems, PPT gradient experiments indicate that short‐duration (1 year) PPT anomalies are often insufficient to drive nonlinear aboveground NPP responses. But long‐term studies, within desert to forest ecosystems, demonstrate how multi‐year PPT anomalies may result in increasing impacts on NPP through time, and thus alter PPT–NPP relationships. We present a conceptual model detailing how NPP responses to PPT anomalies may amplify with the duration of an event, how responses may vary in xeric vs. mesic ecosystems, and how these differences are most likely due to demographic mechanisms. Experiments that can unravel the independent and interactive impacts of the magnitude and duration of wet and dry PPT anomalies are needed, with multi‐site long‐term PPT gradient experiments particularly well‐suited for this task.

Ongoing intensification of the hydrological cycle is altering rainfall regimes by increasing the frequency of extreme wet and dry years and the size of individual rainfall events. Despite long‐standing recognition of the importance of precipitation amount and variability for most terrestrial ecosystem processes, we lack understanding of their interactive effects on ecosystem functioning. We quantified this interaction in native grassland by experimentally eliminating temporal variability in growing season rainfall over a wide range of precipitation amounts, from extreme wet to dry conditions. We contrasted the rain use efficiency (RUE) of above‐ground net primary productivity (ANPP) under conditions of experimentally reduced versus naturally high rainfall variability using a 32‐year precipitation–ANPP dataset from the same site as our experiment. We found that increased growing season rainfall variability can reduce RUE and thus ecosystem functioning by as much as 42% during dry years, but that such impacts weaken as years become wetter. During low precipitation years, RUE is lowest when rainfall event sizes are relatively large, and when a larger proportion of total rainfall is derived from large events. Thus, a shift towards precipitation regimes dominated by fewer but larger rainfall events, already documented over much of the globe, can be expected to reduce the functioning of mesic ecosystems primarily during drought, when ecosystem processes are already compromised by low water availability.

Experiments are widely used in ecology, particularly for assessing global change impacts on ecosystem function. However, results from experiments often are inconsistent with observations made under natural conditions, suggesting the need for rigorous comparisons of experimental and observational studies. We conducted such a "reality check" for a grassland ecosystem by compiling results from nine independently conducted climate change experiments. Each experiment manipulated growing season precipitation (GSP) and measured responses in aboveground net primary production (ANPP). We compared results from experiments with long-term (33-yr) annual precipitation and ANPP records to ask if collectively (n = 44 experiment-years) experiments yielded estimates of ANPP, rain-use efficiency (RUE, grams per square meter ANPP per mm precipitation), and the relationship between GSP and ANPP comparable to observations. We found that mean ANPP and RUE from experiments did not deviate from observations. Experiments and observational data also yielded similar functional relationships between ANPP and GSP, but only within the range of historically observed GSP. Fewer experiments imposed extreme levels of GSP (outside the observed 33-yr record), but when these were included, they altered the GSP-ANPP relationship. This result underscores the need for more experiments imposing extreme precipitation levels to resolve how forecast changes in climate regimes will affect ecosystem function in the future.