Narrative Style Influences Citation Frequency in Climate Change Science

<div><p>Peer-reviewed publications focusing on climate change are growing exponentially with the consequence that the uptake and influence of individual papers varies greatly. Here, we derive metrics of narrativity from psychology and literary theory, and use these metrics to test the hypothesis that more narrative climate change writing is more likely to be influential, using citation frequency as a proxy for influence. From a sample of 732 scientific abstracts drawn from the climate change literature, we find that articles with more narrative abstracts are cited more often. This effect is closely associated with journal identity: higher-impact journals tend to feature more narrative articles, and these articles tend to be cited more often. These results suggest that writing in a more narrative style increases the uptake and influence of articles in climate literature, and perhaps in scientific literature more broadly.</p></div

Nonparametric relationships between each narrative element and log(citations).

<p>For continuous variables, spearman correlations are given along with associated p-values. For binary variables, p-values are given for Wilcoxon rank-sum tests.</p

The relationship between the narrativity index (PC1) and journal impact factor.

<p>Response variables reflect journal means for articles in our dataset (N = 732); shaded area represents the 95% confidence interval for the best-fit line. Linear regression R² = 0.62, p = 6 x 10⁻⁵.</p

A systematic review of ecological attributes that confer resilience to climate change in environmental restoration

<div><p>Ecological restoration is widely practiced as a means of rehabilitating ecosystems and habitats that have been degraded or impaired through human use or other causes. Restoration practices now are confronted by climate change, which has the potential to influence long-term restoration outcomes. Concepts and attributes from the resilience literature can help improve restoration and monitoring efforts under changing climate conditions. We systematically examined the published literature on ecological resilience to identify biological, chemical, and physical attributes that confer resilience to climate change. We identified 45 attributes explicitly related to climate change and classified them as individual- (9), population- (6), community- (7), ecosystem- (7), or process-level attributes (16). Individual studies defined resilience as resistance to change or recovery from disturbance, and only a few studies explicitly included both concepts in their definition of resilience. We found that individual and population attributes generally are suited to species- or habitat-specific restoration actions and applicable at the population scale. Community attributes are better suited to habitat-specific restoration at the site scale, or system-wide restoration at the ecosystem scale. Ecosystem and process attributes vary considerably in their type and applicability. We summarize these relationships in a decision support table and provide three example applications to illustrate how these classifications can be used to prioritize climate change resilience attributes for specific restoration actions. We suggest that (1) including resilience as an explicit planning objective could increase the success of restoration projects, (2) considering the ecological context and focal scale of a restoration action is essential in choosing appropriate resilience attributes, and (3) certain ecological attributes, such as diversity and connectivity, are more commonly considered to confer resilience because they apply to a wide variety of species and ecosystems. We propose that identifying sources of ecological resilience is a critical step in restoring ecosystems in a changing climate.</p></div

Multipanel plot depicting the relationship between narrativity (individual indicators and single narrativity index given by PC1, labeled individually) and article citation frequency.

<p>The use of sensory language, conjunctions, connectivity, and appeal to the reader are significantly correlated with article citation frequency. PC1 index of narrativity is significantly correlated with article citation frequency (linear regression; shaded area indicates 95% confidence interval for the linear model parameters).</p

Fig 12 -

2014 (a) and 2015 (b) temperature versus salinity plots at 40 m nominal depth with lines of constant density. Warmer and fresher water is present during positive temperature anomaly events (colored dots) versus the non-event times (black dots).</p