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Interspecific interactions are crucial in determining species occurrence and community assembly. Understanding these interactions is thus essential for correctly predicting species' responses to climate change. We focussed on an avian forest guild of four hole‐nesting species with differing sensitivities to climate that show a range of well‐understood reciprocal interactions, including facilitation, competition and predation. We modelled the potential distributions of black woodpecker and boreal, tawny and Ural owl, and tested whether the spatial patterns of the more widespread species (excluding Ural owl) were shaped by interspecific interactions. We then modelled the potential future distributions of all four species, evaluating how the predicted changes will alter the overlap between the species' ranges, and hence the spatial outcomes of interactions. Forest cover/type and climate were important determinants of habitat suitability for all species. Field data analysed with N‐mixture models revealed effects of interspecific interactions on current species abundance, especially in boreal owl (positive effects of black woodpecker, negative effects of tawny owl). Climate change will impact the assemblage both at species and guild levels, as the potential area of range overlap, relevant for species interactions, will change in both proportion and extent in the future. Boreal owl, the most climate‐sensitive species in the guild, will retreat, and the range overlap with its main predator, tawny owl, will increase in the remaining suitable area: climate change will thus impact on boreal owl both directly and indirectly. Climate change will cause the geographical alteration or disruption of species interaction networks, with different consequences for the species belonging to the guild and a likely spatial increase of competition and/or intraguild predation. Our work shows significant interactions and important potential changes in the overlap of areas suitable for the interacting species, which reinforce the importance of including relevant biotic interactions in predictive climate change models for increasing forecast accuracy. [ABSTRACT FROM AUTHOR]

Long‐term trends in ecosystem resource use efficiencies (RUEs) and their controlling factors are key pieces of information for understanding how an ecosystem responds to climate change. We used continuous eddy covariance and microclimate data over the period 1999–2017 from a 120‐year‐old black spruce stand in central Saskatchewan, Canada, to assess interannual variability, long‐term trends, and key controlling factors of gross ecosystem production (GEP) and the RUEs of carbon (CUE = net primary production [NPP]/GEP), light (LUE = GEP/absorbed photosynthetic radiation [APAR]), and water (WUE = GEP/evapotranspiration [E]). At this site, annual GEP has shown an increasing trend over the 19 years (p < 0.01), which may be attributed to rising atmospheric CO2 concentration. Interannual variability in GEP, aside from its increasing trend, was most strongly related to spring temperatures. Associated with the significant increase in annual GEP were relatively small changes in NPP, APAR, and E, so that annual CUE showed a decreasing trend and annual LUE and WUE showed increasing trends over the 19 years. The long‐term trends in the RUEs were related to the increasing CO2 concentration. Further analysis of detrended RUEs showed that their interannual variation was impacted most strongly by air temperature. Two‐factor linear models combining CO2 concentration and air temperature performed well (R2~0.60) in simulating annual RUEs. LUE and WUE were positively correlated both annually and seasonally, while LUE and CUE were mostly negatively correlated. Our results showed divergent long‐term trends among CUE, LUE, and WUE and highlighted the need to account for the combined effects of climatic controls and the 'CO2 fertilization effect' on long‐term variations in RUEs. Since most RUE‐based models rely primarily on one resource limitation, the observed patterns of relative change among the three RUEs may have important implications for RUE‐based modeling of C fluxes. [ABSTRACT FROM AUTHOR]

Abstract: Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple‐ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple‐ensemble probabilistic assessment, the median of simulated yield change was −4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981–2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple‐ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources. [ABSTRACT FROM AUTHOR]

Across Canada's boreal forest, linear disturbances, including cutlines such as seismic lines and roads, crisscross the landscape to facilitate resource exploration and extraction; many of these linear disturbances cross peatland ecosystems. Changes in tree canopy cover and the compression of the peat by heavy equipment alter local thermal, hydrological, and ecological conditions, likely changing carbon exchange on the disturbance, and possibly in the adjacent peatland. We measured bulk density, water table, soil temperature, plant cover, and CO2 and CH4 flux along triplicate transects crossing a winter road through a wooded fen near Peace River, Alberta, Canada. Sample plots were located 1, 5, and 10 m from the road on both sides with an additional three plots on the road. Productivity of the overstory trees, when present, was also determined. The winter road had higher bulk density, shallower water table, higher graminoid cover, and thawed earlier than the adjacent peatland. Tree productivity and CO2 flux varied between the plots, and there was no clear pattern in relation to distance from the road. The plots on the winter road acted as a greater CO2 sink and greater CH4 source compared to the adjacent peatland with plots on the winter road emitting on average (standard error) 479 (138) compared to 41 (10) mg CH4 m−2 day−1 in the adjacent peatland. Considering both gases, global warming potential increased from 70 to 250 g CO2e m−2 year−1 in the undisturbed area to 2100 g CO2e m−2 year−1 on the winter road. Although carbon fluxes on any given cutline through peatland will vary depending on level of compaction, line width and vegetation community shifts, the large number of linear disturbances in Canada's boreal forest and slow recovery on peatland ecosites suggest they could represent an important anthropogenic greenhouse gas source. [ABSTRACT FROM AUTHOR]

In the sporadic permafrost zone of northwestern Canada, boreal forest carbon dioxide ( CO2) fluxes will be altered directly by climate change through changing meteorological forcing and indirectly through changes in landscape functioning associated with thaw-induced collapse-scar bog ('wetland') expansion. However, their combined effect on landscape-scale net ecosystem CO2 exchange ( NEELAND), resulting from changing gross primary productivity ( GPP) and ecosystem respiration ( ER), remains unknown. Here, we quantify indirect land cover change impacts on NEELAND and direct climate change impacts on modeled temperature- and light-limited NEELAND of a boreal forest-wetland landscape. Using nested eddy covariance flux towers, we find both GPP and ER to be larger at the landscape compared to the wetland level. However, annual NEELAND (−20 g C m−2) and wetland NEE (−24 g C m−2) were similar, suggesting negligible wetland expansion effects on NEELAND. In contrast, we find non-negligible direct climate change impacts when modeling NEELAND using projected air temperature and incoming shortwave radiation. At the end of the 21st century, modeled GPP mainly increases in spring and fall due to reduced temperature limitation, but becomes more frequently light-limited in fall. In a warmer climate, ER increases year-round in the absence of moisture stress resulting in net CO2 uptake increases in the shoulder seasons and decreases during the summer. Annually, landscape net CO2 uptake is projected to decline by 25 ± 14 g C m−2 for a moderate and 103 ± 38 g C m−2 for a high warming scenario, potentially reversing recently observed positive net CO2 uptake trends across the boreal biome. Thus, even without moisture stress, net CO2 uptake of boreal forest-wetland landscapes may decline, and ultimately, these landscapes may turn into net CO2 sources under continued anthropogenic CO2 emissions. We conclude that NEELAND changes are more likely to be driven by direct climate change rather than by indirect land cover change impacts. [ABSTRACT FROM AUTHOR]

Turnover concepts in state-of-the-art global vegetation models ( GVMs) account for various processes, but are often highly simplified and may not include an adequate representation of the dominant processes that shape vegetation carbon turnover rates in real forest ecosystems at a large spatial scale. Here, we evaluate vegetation carbon turnover processes in GVMs participating in the Inter-Sectoral Impact Model Intercomparison Project ( ISI- MIP, including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT) using estimates of vegetation carbon turnover rate ( k) derived from a combination of remote sensing based products of biomass and net primary production ( NPP). We find that current model limitations lead to considerable biases in the simulated biomass and in k (severe underestimations by all models except JeDi and VISIT compared to observation-based average k), likely contributing to underestimation of positive feedbacks of the northern forest carbon balance to climate change caused by changes in forest mortality. A need for improved turnover concepts related to frost damage, drought, and insect outbreaks to better reproduce observation-based spatial patterns in k is identified. As direct frost damage effects on mortality are usually not accounted for in these GVMs, simulated relationships between k and winter length in boreal forests are not consistent between different regions and strongly biased compared to the observation-based relationships. Some models show a response of k to drought in temperate forests as a result of impacts of water availability on NPP, growth efficiency or carbon balance dependent mortality as well as soil or litter moisture effects on leaf turnover or fire. However, further direct drought effects such as carbon starvation (only in HYBRID4) or hydraulic failure are usually not taken into account by the investigated GVMs. While they are considered dominant large-scale mortality agents, mortality mechanisms related to insects and pathogens are not explicitly treated in these models. [ABSTRACT FROM AUTHOR]

As atmospheric CO2 levels rise, temperate and boreal forests in the Northern Hemisphere are gaining importance as carbon sinks. Quantification of that role, however, has been difficult due to the confounding effects of climate change. Recent large-scale experiments with quaking aspen ( Populus tremuloides), a dominant species in many northern forest ecosystems, indicate that elevated CO2 levels can enhance net primary production. Field studies also reveal that droughts contribute to extensive aspen mortality. To complement this work, we analyzed how the growth of wild aspen clones in Wisconsin has responded to historical shifts in CO2 and climate, accounting for age, genotype (microsatellite heterozygosity), and other factors. Aspen growth has increased an average of 53% over the past five decades, primarily in response to the 19.2% rise in ambient CO2 levels. CO2-induced growth is particularly enhanced during periods of high moisture availability. The analysis accounts for the highly nonlinear changes in growth rate with age, and is unaffected by sex or location sampled. Growth also increases with individual heterozygosity, but this heterozygote advantage has not changed with rising levels of CO2 or moisture. Thus, increases in future growth predicted from previous large-scale, common-garden work are already evident in this abundant and ecologically important tree species. Owing to aspen's role as a foundation species in many North American forest ecosystems, CO2-stimulated growth is likely to have repercussions for numerous associated species and ecosystem processes. [ABSTRACT FROM AUTHOR]