Meta‐analysis is increasingly used in ecology and evolutionary biology. Yet, in these fields this technique has an important limitation: phylogenetic non‐independence exists among taxa, violating the statistical assumptions underlying traditional meta‐analytic models. Recently, meta‐analytical techniques incorporating phylogenetic information have been developed to address this issue. However, no syntheses have evaluated how often including phylogenetic information changes meta‐analytic results. To address this gap, we built phylogenies for and re‐analysed 30 published meta‐analyses, comparing results for traditional vs. phylogenetic approaches and assessing which characteristics of phylogenies best explained changes in meta‐analytic results and relative model fit. Accounting for phylogeny significantly changed estimates of the overall pooled effect size in 47% of datasets for fixed‐effects analyses and 7% of datasets for random‐effects analyses. Accounting for phylogeny also changed whether those effect sizes were significantly different from zero in 23 and 40% of our datasets (for fixed‐ and random‐effects models, respectively). Across datasets, decreases in pooled effect size magnitudes after incorporating phylogenetic information were associated with larger phylogenies and those with stronger phylogenetic signal. We conclude that incorporating phylogenetic information in ecological meta‐analyses is important, and we provide practical recommendations for doing so.

Interactions between plants and microbes have important influences on evolutionary processes, population dynamics, community structure, and ecosystem function. We review the literature to document how climate change may disrupt these ecological interactions and develop a conceptual framework to integrate the pathways of plant-microbe responses to climate over different scales in space and time. We then create a blueprint to aid generalization that categorizes climate effects into changes in the context dependency of plant-microbe pairs, temporal mismatches and altered feedbacks over time, or spatial mismatches that accompany species range shifts. We pair a new graphical model of how plant-microbe interactions influence resistance to climate change with a statistical approach to predict the consequences of increasing variability in climate. Finally, we suggest pathways through which plant-microbe interactions can affect resilience during recovery from climate disruption. Throughout, we take a forward-looking perspective, highlighting knowledge gaps and directions for future research. Expected final online publication date for the Annual Review of Ecology, Evolution, and Systematics, Volume 51 is November 2, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

1. Human land uses, such as agriculture, can leave long-lasting legacies as ecosystems recover. As a consequence, active restoration may be necessary to overcome landuse legacies; however, few studies have evaluated the joint effects of agricultural history and restoration on ecological communities. Those that have studied this joint effect have largely focused on plants and ignored other communities, such as soil microbes. 2. We conducted a large-scale experiment to understand how agricultural history and restoration tree thinning affect soil bacterial and fungal communities within longleaf pine savannas of the southern United States. This experiment contained 64 pairs of remnant (no history of tillage agriculture) and post-agricultural (reforested following abandonment from tillage agriculture >60 years prior) longleaf pine savanna plots. Plots were each 1 ha and arranged into 27 blocks to minimize land-use decision-making biases. We experimentally restored half of the remnant and post-agricultural plots by thinning trees to reinstate open-canopy savanna conditions and collected soils from all plots five growing seasons after tree thinning. We then evaluated soil bacterial and fungal communities using metabarcoding. 3. Agricultural history increased bacterial diversity but decreased fungal diversity, while restoration increased both bacterial and fungal diversity. Both bacterial and fungal richness were correlated with a range of environmental variables including above-ground variables like leaf litter and plant diversity, and below-ground variables such as soil nutrients, pH and organic matter, many of which were also impacted by agricultural history and restoration. 4. Fungal and bacterial community compositions were shaped by restoration and agricultural history resulting in four distinct communities across the four treatment combinations. 5. Synthesis and applications. Past agricultural land use has left persistent legacies on soil microbial biodiversity, even over half a century after agricultural abandonment and after intensive restoration activities. The impacts of these changes on soil microbe biodiversity could influence native plant establishment, plant productivity and other aspects of ecosystem functioning following agricultural abandonment and during restoration.

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