Current understanding of life-history evolution and how demographic parameters contribute to population dynamics across species is largely based on assumptions of either constant environments or stationary environmental variation. Meanwhile, species are faced with non-stationary environmental conditions (changing mean, variance, or both) created by climate and landscape change. To close the gap between contemporary reality and demographic theory, we develop a set of transient life table response experiments (LTREs) for decomposing realised population growth rates into contributions from specific vital rates and components of population structure. Using transient LTREs in a theoretical framework, we reveal that established concepts in population biology will require revision because of reliance on approaches that do not address the influence of unstable population structure on population growth and mean fitness. Going forward, transient LTREs will enhance understanding of demography and improve the explanatory power of models used to understand ecological and evolutionary dynamics.

1. Upon arriving in a novel environment, invading populations are likely to be small and far from a stable stage structure. This unstable stage structure can cause transient (short-term) population dynamics to differ greatly from asymptotic (long-term) dynamics. Because the persistence of small populations depends heavily on population growth rate, short-term dynamics may strongly influence the viability of invading populations. 2. We used published matrix population models to study the dynamics of small 'invading' populations for 105 plant species spanning a range of life histories, including species classified as both invasive and non-invasive. We simulated the matrix population models to estimate the effect of transient dynamics on population viability (i.e. potential invasiveness) after a hypothetical seed dispersal event into a novel environment. We then evaluated the predictive power of transient and long-term population growth rates to explain variation in population viability and identified the life-history correlates of population dynamics that best explained establishment success. 3. Transient and long-term population growth rates were positively but independently correlated with population viability across species. Minimum transient density (minimum population density attained en route to a stable stage structure) was the best transient predictor of population viability. This suggests that avoidance of severe short-term population declines is more important during establishment than either the rate of decline or transient ability to increase in density following a decline. 4. Despite a negative correlation between transient density and fecundity, species with high fecundity had disproportionately favourable transient dynamics and higher long-term population growth rates, resulting in higher population viability. Together, these results suggest that highly fecund species are better equipped to overcome the early effects of demographic stochasticity in the establishment phase than less fecund species and help explain the common empirical finding that species invasiveness is correlated with fecundity. 5. Synthesis. Transient and long-term population dynamics are independent predictors of demographic performance that influence the viability of invading (i.e. small, unstable) populations subjected to strong effects of demographic stochasticity. Greater long-term population growth rates and disproportionately favourable transient dynamics may account for the commonly observed invasiveness of highly fecund species. Given the strong dependence of population viability on population growth and the wide range of transient responses among species, transient analysis may provide critical insights into the demographic correlates of biological invasion potential.

The Paris Agreement is a multinational initiative to combat climate change by keeping a global temperature increase in this century to 2°C above preindustrial levels while pursuing efforts to limit the increase to 1.5°C. Until recently, ensembles of coupled climate simulations producing temporal dynamics of climate en route to stable global mean temperature at 1.5 and 2°C above preindustrial levels were not available. Hence, the few studies that have assessed the ecological impact of the Paris Agreement used ad‐hoc approaches. The development of new specific mitigation climate simulations now provides an unprecedented opportunity to inform ecological impact assessments. Here we project the dynamics of all known emperor penguin (Aptenodytes forsteri) colonies under new climate change scenarios meeting the Paris Agreement objectives using a climate‐dependent‐metapopulation model. Our model includes various dispersal behaviors so that penguins could modulate climate effects through movement and habitat selection. Under business‐as‐usual greenhouse gas emissions, we show that 80% of the colonies are projected to be quasiextinct by 2100, thus the total abundance of emperor penguins is projected to decline by at least 81% relative to its initial size, regardless of dispersal abilities. In contrast, if the Paris Agreement objectives are met, viable emperor penguin refuges will exist in Antarctica, and only 19% and 31% colonies are projected to be quasiextinct by 2100 under the Paris 1.5 and 2 climate scenarios respectively. As a result, the global population is projected to decline by at least by 31% under Paris 1.5 and 44% under Paris 2. However, population growth rates stabilize in 2060 such that the global population will be only declining at 0.07% under Paris 1.5 and 0.34% under Paris 2, thereby halting the global population decline. Hence, global climate policy has a larger capacity to safeguard the future of emperor penguins than their intrinsic dispersal abilities.

Summer temperature on the Cape Churchill Peninsula (Manitoba, Canada) has increased rapidly over the past 75 years, and flowering phenology of the plant community is advanced in years with warmer temperatures (higher cumulative growing degree days). Despite this, there has been no overall shift in flowering phenology over this period. However, climate change has also resulted in increased interannual variation in temperature; if relationships between phenology and temperature are not linear, an increase in temperature variance may interact with an increase in the mean to alter how community phenology changes over time. In our system, the relationship between phenology and temperature was log-linear, resulting in a steeper slope at the cold end of the temperature spectrum than at the warm end. Because below-average temperatures had a greater impact on phenology than above-average temperatures, the long-term advance in phenology was reduced. In addition, flowering phenology in a given year was delayed if summer temperatures were high the previous year or 2 years earlier (lag effects), further reducing the expected advance over time. Phenology of early-flowering plants was negatively affected only by temperatures in the previous year, and that of late-flowering plants primarily by temperatures 2 years earlier. Subarctic plants develop leaf primordia one or more years prior to flowering (preformation); these results suggest that temperature affects the development of flower primordia during this preformation period. Together, increased variance in temperature and lag effects interacted with a changing mean to reduce the expected phenological advance by 94%, a magnitude large enough to account for our inability to detect a significant advance over time. We conclude that changes in temperature variability and lag effects can alter trends in plant responses to a warming climate and that predictions for changes in plant phenology under future warming scenarios should incorporate such effects.

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