Although variation in effect sizes and predicted values among studies of similar phenomena is inevitable, such variation far exceeds what might be produced by sampling error alone. One possible explanation for variation among results is differences among researchers in the decisions they make regarding statistical analyses. A growing array of studies has explored this analytical variability in different fields and has found substantial variability among results despite analysts having the same data and research question. Many of these studies have been in the social sciences, but one small “many analyst” study found similar variability in ecology. We expanded the scope of this prior work by implementing a large-scale empirical exploration of the variation in effect sizes and model predictions generated by the analytical decisions of different researchers in ecology and evolutionary biology. We used two unpublished datasets, one from evolutionary ecology (blue tit, Cyanistes caeruleus, to compare sibling number and nestling growth) and one from conservation ecology (Eucalyptus, to compare grass cover and tree seedling recruitment). The project leaders recruited 174 analyst teams, comprising 246 analysts, to investigate the answers to prespecified research questions. Analyses conducted by these teams yielded 141 usable effects (compatible with our meta-analyses and with all necessary information provided) for the blue tit dataset, and 85 usable effects for the Eucalyptus dataset. We found substantial heterogeneity among results for both datasets, although the patterns of variation differed between them. For the blue tit analyses, the average effect was convincingly negative, with less growth for nestlings living with more siblings, but there was near continuous variation in effect size from large negative effects to effects near zero, and even effects crossing the traditional threshold of statistical significance in the opposite direction. In contrast, the average relationship between grass cover and Eucalyptus seedling number was only slightly negative and not convincingly different from zero, and most effects ranged from weakly negative to weakly positive, with about a third of effects crossing the traditional threshold of significance in one direction or the other. However, there were also several striking outliers in the Eucalyptus dataset, with effects far from zero. For both datasets, we found substantial variation in the variable selection and random effects structures among analyses, as well as in the ratings of the analytical methods by peer reviewers, but we found no strong relationship between any of these and deviation from the meta-analytic mean. In other words, analyses with results that were far from the mean were no more or less likely to have dissimilar variable sets, use random effects in their models, or receive poor peer reviews than those analyses that found results that were close to the mean. The existence of substantial variability among analysis outcomes raises important questions about how ecologists and evolutionary biologists should interpret published results, and how they should conduct analyses in the future.

Climate change is impacting forested ecosystems worldwide, particularly in the Northern Hemisphere where warming has increased at a faster rate than the rest of the globe. As climate warms, trembling aspen (Populus tremuloides) is expected to become more successful in northern boreal forests because of its current presence in drier areas of North America. However, large-scale productivity decline of aspen has recently been documented throughout the United States and Canada as a result of drought and insect outbreaks. We used tree ring measurements (basal area increment (BAI) and stable carbon isotopes (δ ¹³C)) and remote sensing indices of vegetation productivity (NDVI) to study the impact of climate and damage by the aspen epidermal leaf miner (Phyllocnistis populiella) on aspen productivity and physiology in interior Alaska. We found that productivity decreased with greater leaf mining and was not sensitive to growing season (GS) moisture availability. Although productivity decreased during high leaf mining years, it recovered to pre-outbreak levels during years of low insect damage, suggesting a degree of resilience to P. populiella mining. Climate and leaf mining interacted to influence tree ring δ ¹³C, with greater leaf mining resulting in decreased δ ¹³C when GS moisture availability was low. We also found that NDVI was negatively associated with leaf mining, and positively correlated with BAI and the δ ¹³C decrease corresponding to mining. This suggests that NDVI is capturing not only variations in productivity, but also changes in physiology associated with P. populiella. Overall, these findings indicate that the indirect effects of P. populiella mining have a larger impact on aspen productivity and physiology than climate under current conditions, and is essential to consider when assessing growth, physiology and NDVI trends in interior Alaska.

Climate change‐driven droughts and insect outbreaks are becoming more frequent and widespread, increasing forest vulnerability to mortality. By addressing the impacts of climate and insects on tree growth preceding death, we can better understand tree mortality risk under a changing climate. Here, we used tree stature and interannual growth (basal area increment; BAI) to assess processes leading to trembling aspen (Populus tremuloides) survival or mortality during an unprecedented leaf miner (Phyllocnistis populiella) outbreak in boreal North America. We identified eight sites (22 plots) in the longest running forest monitoring network in Alaska, spanning ~350 km of latitude, that experienced ≥0.25 Mg·ha⁻¹·yr⁻¹aspen mortality during the outbreak. We compared the size and canopy position, growth patterns, and sensitivity to climate and leaf mining of aspen that survived (living;n = 84) vs. died (dying;n = 76) and linked the normalized difference vegetation index (NDVI) to plot‐level aspen growth and stand biomass recruitment, growth, and mortality. Dying aspen were in the subcanopy, smaller in diameter, and after a drought in 1957 had lower growth than living aspen until death. Before the outbreak, growth of all trees was positively influenced by moisture and negatively by temperature, but only living trees maintained this climate response during the outbreak. Leaf mining reduced growth of both groups, exerting at least a twofold greater impact than climate. The NDVI captured plot‐level tree growth and stand biomass growth and mortality, yet it was nearly two times more strongly associated with living than dying tree growth and 12 times more strongly associated with biomass growth than mortality. These differences suggest that NDVI may inadequately detect insect‐driven dieback and dispersed mortality of aspen across the boreal biome. Our findings reveal that a historic drought triggered a multi‐decadal growth decline that predisposed aspen to mortality during the leaf miner outbreak and that while aspen growth is influenced by moisture and temperature, it is more strongly affected byP. populiella. We conclude that as the climate warms and insect outbreaks increase in frequency and magnitude at high latitudes, we should expect to see persistent and greater declines in aspen growth and increases in mortality.

Wildfire activity is increasing in boreal forests as climate warms and dries, furthering risks to rural and urban communities. In black spruce forests of Interior Alaska, fuel reduction treatments are increasingly used to reduce characteristics of fire behavior and create a defensible space for fire suppression. These treatments, however, introduce novel disturbance characteristics, making longer-term outcomes on ecosystem structure uncertain. By understanding how ecosystems respond to such treatments over time, we can improve management procedures and maintenance protocols so that they effectively reduce wildfire risk over decadal timescales. We remeasured a network of hand thinned and mechanically treated (‘shearbladed’) sites in Interior Alaska to assess how successional trajectories of tree dominance, understory composition, and permafrost change over ~20 years after treatment. We also assessed if these treatments reduce modeled surface rate of fire spread (ROS), flame length, and fireline intensity relative to an untreated black spruce stand, and if surface fire behavior changes over time. In thinned areas, soil organic layer (SOL) disturbance promoted tree seedling recruitment, with conifer seedlings dominating but deciduous broadleaf seedlings prevalent on the thinnest SOLs. In shearbladed areas conifer recruitment density increased over the sampling period at a slow rate (~0.2 stems m -2 yr -1 ) yet deciduous tree seedlings were nearly 20 times more abundant. Understory composition was not altered by thinning but in shearbladed treatments shifted from an initial high abundance of forbs and horsetail to tall deciduous shrubs and grasses over time. Thaw depth was greater in treated than unmanaged areas, and in shearbladed than thinned sites, but increased over time in both treatments. Although understory vegetation changed over time in shearbladed treatments, modeled surface fire behavior was constant, highlighting potential limitations of fuel models and the need for additional fuels-specific data to capture the changing vegetation structure within this treatment. Lastly, treatment effectiveness at reducing modeled surface ROS, flame length, and fireline intensity depended on the fuel model used for an untreated black spruce stand, pointing to uncertainties about the efficacy of these treatments at mitigating surface fire behavior. Overall, we show that fuel reduction treatments can promote low flammability, deciduous-dominated successional trajectories and that shearblading in particular has strong effects on understory composition and permafrost degradation that persist for nearly two decades after disturbance. Such factors need to be considered to enhance the design, management, and predictions of fire behavior in these treatments.