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Subtropical forests are important ecosystems globally due to their extensive role in carbon sequestration. Extreme climate events are known to introduce disturbances in the ecosystem that cause long‐term changes in carbon balance and radiation reflectance. However, how these ecosystem function changes contribute to global warming in terms of radiative forcing (RF), especially in the years following a disturbance, still needs to be investigated. We studied an extreme snow event that occurred in a subtropical evergreen broadleaved forest in south‐western China in 2015 and used 9 years (2011–2019) of net ecosystem CO2 exchange (NEE) and surface albedo (α) data to investigate the effect of the event on the ecosystem RF changes. In the year of the disturbance, leaf area index (LAI) declined by 40% and α by 32%. The annual NEE was −718 ± 128 g C m−2 as a sink in the pre‐disturbance years (2011–2014), but after the event, the sink strength dropped significantly by 76% (2015). Both the vegetation, indicated by LAI, and α recovered to pre‐disturbance levels in the fourth post‐disturbance year (2018). However, the NEE recovery lagged and occurred a year later in 2019, suggesting a more severe and lasting impact on the ecosystem carbon balance. Overall, the extreme event caused a positive (warming effect) net RF which was predominantly caused by changes in α (90%–93%) rather than those in NEE. This result suggests that, compared to the climate effect caused by forest carbon sequestration changes, the climate effect of α alterations can be more sensitive to vegetation damage induced by natural disturbances. Moreover, this study demonstrates the important role of vegetation recovery in driving canopy reflectance and ecosystem carbon balance during the post‐disturbance period, which determines the ecosystem feedbacks to the climate change. [ABSTRACT FROM AUTHOR]

Ecological communities can remain stable in the face of disturbance if their constituent species have different resistance and resilience strategies. In turn, local stability scales up regionally if heterogeneous landscapes maintain spatial asynchrony across discrete populations—but not if large‐scale stressors synchronize environmental conditions and biological responses. Here, we hypothesized that droughts could drastically decrease the stability of invertebrate metapopulations both by filtering out poorly adapted species locally, and by synchronizing their dynamics across a river network. We tested this hypothesis via multivariate autoregressive state‐space (MARSS) models on spatially replicated, long‐term data describing aquatic invertebrate communities and hydrological conditions in a set of temperate, lowland streams subject to seasonal and supraseasonal drying events. This quantitative approach allowed us to assess the influence of local (flow magnitude) and network‐scale (hydrological connectivity) drivers on invertebrate long‐term trajectories, and to simulate near‐future responses to a range of drought scenarios. We found that fluctuations in species abundances were heterogeneous across communities and driven by a combination of hydrological and stochastic drivers. Among metapopulations, increasing extent of dry reaches reduced the abundance of functional groups with low resistance or resilience capacities (i.e. low ability to persist in situ or recolonize from elsewhere, respectively). Our simulations revealed that metapopulation quasi‐extinction risk for taxa vulnerable to drought increased exponentially as flowing habitats contracted within the river network, whereas the risk for taxa with resistance and resilience traits remained stable. Our results suggest that drought can be a synchronizing agent in riverscapes, potentially leading to regional quasi‐extinction of species with lower resistance and resilience abilities. Better recognition of drought‐driven synchronization may increase realism in species extinction forecasts as hydroclimatic extremes continue to intensify worldwide. [ABSTRACT FROM AUTHOR]

A major challenge in understanding the response of populations to climate change is to separate the effects of local drivers acting independently on specific populations, from the effects of global drivers that impact multiple populations simultaneously and thereby synchronize their dynamics. We investigated the environmental drivers and the demographic mechanisms of the widespread decline in marine survival rates of Atlantic salmon (Salmo salar) over the last four decades. We developed a hierarchical Bayesian life cycle model to quantify the spatial synchrony in the marine survival of 13 large groups of populations (called stock units, SU) from two continental stock groups (CSG) in North America (NA) and Southern Europe (SE) over the period 1971–2014. We found strong coherence in the temporal variation in postsmolt marine survival among the 13 SU of NA and SE. A common North Atlantic trend explains 37% of the temporal variability of the survivals for the 13 SU and declines by a factor of 1.8 over the 1971–2014 time series. Synchrony in survival trends is stronger between SU within each CSG. The common trends at the scale of NA and SE capture 60% and 42% of the total variance of temporal variations, respectively. Temporal variations of the postsmolt survival are best explained by the temporal variations of sea surface temperature (SST, negative correlation) and net primary production indices (PP, positive correlation) encountered by salmon in common domains during their marine migration. Specifically, in the Labrador Sea/Grand Banks for populations from NA, 26% and 24% of variance is captured by SST and PP, respectively and in the Norwegian Sea for populations from SE, 21% and 12% of variance is captured by SST and PP, respectively. The findings support the hypothesis of a response of salmon populations to large climate‐induced changes in the North Atlantic simultaneously impacting populations from distant continental habitats. [ABSTRACT FROM AUTHOR]

The impacts of climate change have re‐energized interest in understanding the role of climate in setting species geographic range edges. Despite the strong focus on species' distributions in ecology and evolution, defining a species range edge is theoretically and empirically difficult. The challenge of determining a range edge and its relationship to climate is in part driven by the nested nature of geography and the multidimensionality of climate, which together generate complex patterns of both climate and biotic distributions across landscapes. Because range‐limiting processes occur in both geographic and climate space, the relationship between these two spaces plays a critical role in setting range limits. With both conceptual and empirical support, we argue that three factors—climate heterogeneity, collinearity among climate variables, and spatial scale—interact to shape the spatial structure of range edges along climate gradients, and we discuss several ways that these factors influence the stability of species range edges with a changing climate. We demonstrate that geographic and climate edges are often not concordant across species ranges. Furthermore, high climate heterogeneity and low climate collinearity across landscapes increase the spectrum of possible relationships between geographic and climatic space, suggesting that geographic range edges and climatic niche limits correspond less frequently than we may expect. More empirical explorations of how the complexity of real landscapes shapes the ecological and evolutionary processes that determine species range edges will advance the development of range limit theory and its applications to biodiversity conservation in the context of changing climate. [ABSTRACT FROM AUTHOR]

Fire is a primary disturbance in boreal forests and generates both positive and negative climate forcings. The influence of fire on surface albedo is a predominantly negative forcing in boreal forests, and one of the strongest overall, due to increased snow exposure in the winter and spring months. Albedo forcings are spatially and temporally heterogeneous and depend on a variety of factors related to soils, topography, climate, land cover/vegetation type, successional dynamics, time since fire, season, and fire severity. However, how these variables interact to influence albedo is not well understood, and quantifying these relationships and predicting postfire albedo becomes increasingly important as the climate changes and management frameworks evolve to consider climate impacts. Here we developed a MODIS‐derived 'blue sky' albedo product and a novel machine learning modeling framework to predict fire‐driven changes in albedo under historical and future climate scenarios across boreal North America. Converted to radiative forcing (RF), we estimated that fires generate an annual mean cooling of −1.77 ± 1.35 W/m2 from albedo under historical climate conditions (1971–2000) integrated over 70 years postfire. Increasing postfire albedo along a south–north climatic gradient was offset by a nearly opposite gradient in solar insolation, such that large‐scale spatial patterns in RF were minimal. Our models suggest that climate change will lead to decreases in mean annual postfire albedo, and hence a decreasing strength of the negative RF, a trend dominated by decreased snow cover in spring months. Considering the range of future climate scenarios and model uncertainties, we estimate that for fires burning in the current era (2016) the cooling effect from long‐term postfire albedo will be reduced by 15%–28% due to climate change. [ABSTRACT FROM AUTHOR]

The 'Moran effect' predicts that dynamics of populations of a species are synchronized over similar distances as their environmental drivers. Strong population synchrony reduces species viability, but spatial heterogeneity in density dependence, the environment, or its ecological responses may decouple dynamics in space, preventing extinctions. How such heterogeneity buffers impacts of global change on large‐scale population dynamics is not well studied. Here, we show that spatially autocorrelated fluctuations in annual winter weather synchronize wild reindeer dynamics across high‐Arctic Svalbard, while, paradoxically, spatial variation in winter climate trends contribute to diverging local population trajectories. Warmer summers have improved the carrying capacity and apparently led to increased total reindeer abundance. However, fluctuations in population size seem mainly driven by negative effects of stochastic winter rain‐on‐snow (ROS) events causing icing, with strongest effects at high densities. Count data for 10 reindeer populations 8–324 km apart suggested that density‐dependent ROS effects contributed to synchrony in population dynamics, mainly through spatially autocorrelated mortality. By comparing one coastal and one 'continental' reindeer population over four decades, we show that locally contrasting abundance trends can arise from spatial differences in climate change and responses to weather. The coastal population experienced a larger increase in ROS, and a stronger density‐dependent ROS effect on population growth rates, than the continental population. In contrast, the latter experienced stronger summer warming and showed the strongest positive response to summer temperatures. Accordingly, contrasting net effects of a recent climate regime shift—with increased ROS and harsher winters, yet higher summer temperatures and improved carrying capacity—led to negative and positive abundance trends in the coastal and continental population respectively. Thus, synchronized population fluctuations by climatic drivers can be buffered by spatial heterogeneity in the same drivers, as well as in the ecological responses, averaging out climate change effects at larger spatial scales. [ABSTRACT FROM AUTHOR]

Abstract: Habitat fragmentation and climate change are both prominent manifestations of global change, but there is little knowledge on the specific mechanisms of how climate change may modify the effects of habitat fragmentation, for example, by altering dynamics of spatially structured populations. The long‐term viability of metapopulations is dependent on independent dynamics of local populations, because it mitigates fluctuations in the size of the metapopulation as a whole. Metapopulation viability will be compromised if climate change increases spatial synchrony in weather conditions associated with population growth rates. We studied a recently reported increase in metapopulation synchrony of the Glanville fritillary butterfly (Melitaea cinxia) in the Finnish archipelago, to see if it could be explained by an increase in synchrony of weather conditions. For this, we used 23 years of butterfly survey data together with monthly weather records for the same period. We first examined the associations between population growth rates within different regions of the metapopulation and weather conditions during different life‐history stages of the butterfly. We then examined the association between the trends in the synchrony of the weather conditions and the synchrony of the butterfly metapopulation dynamics. We found that precipitation from spring to late summer are associated with the M. cinxia per capita growth rate, with early summer conditions being most important. We further found that the increase in metapopulation synchrony is paralleled by an increase in the synchrony of weather conditions. Alternative explanations for spatial synchrony, such as increased dispersal or trophic interactions with a specialist parasitoid, did not show paralleled trends and are not supported. The climate driven increase in M. cinxia metapopulation synchrony suggests that climate change can increase extinction risk of spatially structured populations living in fragmented landscapes by altering their dynamics. [ABSTRACT FROM AUTHOR]