Simulating effects of climate change on boreal ecosystem carbon pools in central Canada

Aim Possible effects of current and future climates on boreal vegetation dynamics and carbon (C) cycling were investigated using the CENTURY 4.0 soil process model and a modified version of the FORSKA2 forest patch model. Location Eleven climate station locations distributed along a transect across the boreal zone of central Canada. Methods Both models were driven by detrended long-term monthly climate data. Using a climate change signal derived from the GISS general circulation model (GCM) 2×CO₂ equilibrium climate scenario, the output from the two models was then used to compare simulated current and possible future total ecosystem C storage at the climate station locations. Results After allowing for their different underlying structures, comparison of output from both models showed good agreement with local field data under current climate conditions. CENTURY 4.0 was able to reproduce spatial variation in soil and litter C densities satisfactorily but tended to overestimate biomass productivity. FORSKA2 reproduced aboveground biomass productivity and spatially averaged biomass densities relatively well. Under the GISS 2×CO₂ scenario, both models generally predicted small increases in aboveground biomass C density for forest and tundra locations, but CENTURY 4.0 predicted greater decreases in soil and litter pools, for overall decreases in ecosystem C storage in the range 16–19%. Main conclusions With some caveats, results imply that effects of increased precipitation (as simulated by the GISS GCM) would more than compensate for any negative effects of increased temperature on forest growth. Increased temperature would also increase decomposition rates of soil and litter organic matter, however, for a net overall decrease in total ecosystem C storage.     

Projected climate change effects on Alberta's boreal forests imply future challenges for oil sands reclamation

Climate change will drive significant changes in vegetation cover and also impact efforts to restore ecosystems that have been disturbed by human activities. Bitumen mining in the Alberta oil sands region of western Canada requires reclamation to “equivalent land capability,” implying establishment of vegetation similar to undisturbed boreal ecosystems. However, there is consensus that this region will be exposed to relatively severe climate warming, causing increased occurrence of drought and wildfire, which threaten the persistence of both natural and reclaimed ecosystems. We used a landscape model, LANDIS‐II, to simulate plant responses to climate change and disturbances, forecasting changes to boreal forests within the oil sands region. Under the most severe climate forcing scenarios (representative concentration pathway [RCP] 8.5) the model projected substantial decreases in forest biomass, with the future forest being dominated by drought‐ and fire‐tolerant species characteristic of parkland or prairie ecosystems. In contrast, less extreme climate forcing scenarios (RCPs 2.6 and 4.5) had relatively minor effects on forest composition and biomass with boreal conifers continuing to dominate the landscape. If the climate continues to change along a trajectory similar to those simulated by climate models for the RCP 8.5 forcing scenario, current reclamation goals to reestablish spruce‐dominated boreal forest will likely be difficult to achieve. Results from scenario modeling studies such as ours, and continued monitoring of change in the boreal forest, will help inform reclamation practices, which could include establishment of species better adapted to warmer and drier conditions.     

Stochastic resonance in climate reddening increases the risk of cyclic ecosystem extinction via phase-tipping

Human activity is leading to changes in the mean and variability of climatic parameters in most locations around the world. The changing mean has received considerable attention from scientists and climate policy makers. However, recent work indicates that the changing variability, that is, the amplitude and the temporal autocorrelation of deviations from the mean, may have greater and more imminent impact on ecosystems. In this paper, we demonstrate that changes in climate variability alone could drive cyclic predator–prey ecosystems to extinction via so-called phase-tipping (P-tipping), a new type of instability that occurs only from certain phases of the predator–prey cycle. We construct a mathematical model of a variable climate and couple it to two self-oscillating paradigmatic predator–prey models. Most importantly, we combine realistic parameter values for the Canada lynx and snowshoe hare with actual climate data from the boreal forest. In this way, we demonstrate that critically important species in the boreal forest have increased likelihood of P-tipping to extinction under predicted changes in climate variability, and are most vulnerable during stages of the cycle when the predator population is near its maximum. Furthermore, our analysis reveals that stochastic resonance is the underlying mechanism for the increased likelihood of P-tipping to extinction.     

Examining forest resilience to changing fire frequency in a fire‐prone region of boreal forest

Future changes in climate are widely anticipated to increase fire frequency, particularly in boreal forests where extreme warming is expected to occur. Feedbacks between vegetation and fire may modify the direct effects of warming on fire activity and shape ecological responses to changing fire frequency. We investigate these interactions using extensive field data from the Boreal Shield of Saskatchewan, Canada, a region where >40% of the forest has burned in the past 30 years. We use geospatial and field data to assess the resistance and resilience of eight common vegetation states to frequent fire by quantifying the occurrence of short‐interval fires and their effect on recovery to a similar vegetation state. These empirical relationships are combined with data from published literature to parameterize a spatially explicit, state‐and‐transition simulation model of fire and forest succession. We use this model to ask if and how: (a) feedbacks between vegetation and wildfire may modify fire activity on the landscape, and (b) more frequent fire may affect landscape forest composition and age structure. Both field and GIS data suggest the probability of fire is low in the initial decades after fire, supporting the hypothesis that fuel accumulation may exert a negative feedback on fire frequency. Field observations of pre‐ and postfire composition indicate that switches in forest state are more likely in conifer stands that burn at a young age, supporting the hypothesis that resilience is lower in immature stands. Stands dominated by deciduous trees or jack pine were generally resilient to fire, while mixed conifer and well‐drained spruce forests were less resilient. However, simulation modeling suggests increased fire activity may result in large changes in forest age structure and composition, despite the feedbacks between vegetation–fire likely to occur with increased fire activity.     

The impacts and implications of an intensifying fire regime on Alaskan boreal forest composition and albedo

Climate warming and drying are modifying the fire dynamics of many boreal forests, moving them towards a regime with a higher frequency of extreme fire years characterized by large burns of high severity. Plot‐scale studies indicate that increased burn severity favors the recruitment of deciduous trees in the initial years following fire. Consequently, a set of biophysical effects of burn severity on postfire boreal successional trajectories at decadal timescales have been hypothesized. Prominent among these are a greater cover of deciduous tree species in intermediately aged stands after more severe burning, with associated implications for carbon and energy balances. Here we investigate whether the current vegetation composition of interior Alaska supports this hypothesis. A chronosequence of six decades of vegetation regrowth following fire was created using a database of burn scars, an existing forest biomass map, and maps of albedo and the deciduous fraction of vegetation that we derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite imagery. The deciduous fraction map depicted the proportion of aboveground biomass in deciduous vegetation, derived using a RandomForest algorithm trained with field data sets (n=69, 71% variance explained). Analysis of the difference Normalized Burn Ratio, a remotely sensed index commonly used as an indicator of burn severity, indicated that burn size and ignition date can provide a proxy of burn severity for historical fires. LIDAR remote sensing and a bioclimatic model of evergreen forest distribution were used to further refine the stratification of the current landscape by burn severity. Our results show that since the 1950s, more severely burned areas in interior Alaska have produced a vegetation cohort that is characterized by greater deciduous biomass. We discuss the importance of this shift in vegetation composition due to climate‐induced changes in fire severity for carbon sequestration in forest biomass and surface reflectance (albedo), among other feedbacks to climate.     

Satellite microwave detection of boreal forest recovery from the extreme 2004 wildfires in Alaska and Canada

The rate of vegetation recovery from boreal wildfire influences terrestrial carbon cycle processes and climate feedbacks by affecting the surface energy budget and land‐atmosphere carbon exchange. Previous forest recovery assessments using satellite optical‐infrared normalized difference vegetation index (NDVI) and tower CO₂ eddy covariance techniques indicate rapid vegetation recovery within 5–10 years, but these techniques are not directly sensitive to changes in vegetation biomass. Alternatively, the vegetation optical depth (VOD) parameter from satellite passive microwave remote sensing can detect changes in canopy biomass structure and may provide a useful metric of post‐fire vegetation response to inform regional recovery assessments. We analyzed a multi‐year (2003–2010) satellite VOD record from the NASA AMSR‐E (Advanced Microwave Scanning Radiometer for EOS) sensor to estimate forest recovery trajectories for 14 large boreal fires from 2004 in Alaska and Canada. The VOD record indicated initial post‐fire canopy biomass recovery within 3–7 years, lagging NDVI recovery by 1–5 years. The VOD lag was attributed to slower non‐photosynthetic (woody) and photosynthetic (foliar) canopy biomass recovery, relative to the faster canopy greenness response indicated from the NDVI. The duration of VOD recovery to pre‐burn conditions was also directly proportional (P < 0.01) to satellite (moderate resolution imaging spectroradiometer) estimated tree cover loss used as a metric of fire severity. Our results indicate that vegetation biomass recovery from boreal fire disturbance is generally slower than reported from previous assessments based solely on satellite optical‐infrared remote sensing, while the VOD parameter enables more comprehensive assessments of boreal forest recovery.     

Satellite‐based evidence for shrub and graminoid tundra expansion in northern Quebec from 1986 to 2010

Global vegetation models predict rapid poleward migration of tundra and boreal forest vegetation in response to climate warming. Local plot and air‐photo studies have documented recent changes in high‐latitude vegetation composition and structure, consistent with warming trends. To bridge these two scales of inference, we analyzed a 24‐year (1986–2010) Landsat time series in a latitudinal transect across the boreal forest‐tundra biome boundary in northern Quebec province, Canada. This region has experienced rapid warming during both winter and summer months during the last 40 years. Using a per‐pixel (30 m) trend analysis, 30% of the observable (cloud‐free) land area experienced a significant (P < 0.05) positive trend in the Normalized Difference Vegetation Index (NDVI). However, greening trends were not evenly split among cover types. Low shrub and graminoid tundra contributed preferentially to the greening trend, while forested areas were less likely to show significant trends in NDVI. These trends reflect increasing leaf area, rather than an increase in growing season length, because Landsat data were restricted to peak‐summer conditions. The average NDVI trend (0.007 yr^?1) corresponds to a leaf‐area index (LAI) increase of ~0.6 based on the regional relationship between LAI and NDVI from the Moderate Resolution Spectroradiometer. Across the entire transect, the area‐averaged LAI increase was ~0.2 during 1986–2010. A higher area‐averaged LAI change (~0.3) within the shrub‐tundra portion of the transect represents a 20–60% relative increase in LAI during the last two decades. Our Landsat‐based analysis subdivides the overall high‐latitude greening trend into changes in peak‐summer greenness by cover type. Different responses within and among shrub, graminoid, and tree‐dominated cover types in this study indicate important fine‐scale heterogeneity in vegetation growth. Although our findings are consistent with community shifts in low‐biomass vegetation types over multi‐decadal time scales, the response in tundra and forest ecosystems to recent warming was not uniform.     

Sensitivity of Siberian larch forests to climate change

The Northern Hemisphere's boreal forests, particularly the Siberian boreal forest, may have a strong effect on Earth's climate through changes in dominant vegetation and associated regional surface albedo. We show that warmer climate will likely convert Siberia's deciduous larch (Larix spp.) to evergreen conifer forests, and thus decrease regional surface albedo. The dynamic vegetation model, FAREAST, simulates Russian boreal forest composition and was used to explore the feedback between climate change and forest composition at continental, regional, and local scales. FAREAST was used to simulate the impact of changes in temperature and precipitation on total and genus‐level biomass at sites across Siberia and the Russian Far East (RFE), and for six high‐ and low‐diversity regions. Model runs with and without European Larch (Larix decidua) included in the available species pool were compared to assess the potential for this species, which is adapted to warmer climate conditions, to mitigate the effects of climate change, especially the shift to evergreen dominance. At the continental scale, when temperature is increased, larch‐dominated sites become vulnerable to early replacement by evergreen conifers. At the regional and local scales, the diverse Amur region of the RFE does not show a strong response to climate change, but the low‐diversity regions in central and southern Siberia have an abrupt vegetation shift from larch‐dominated forest to evergreen‐conifer forest in response to increased temperatures. The introduction of L. decidua prevents the collapse of larch in these low‐diversity areas and thus mitigates the response to warming. Using contemporary MODIS albedo measurements, we determined that a conversion from larch to evergreen stands in low‐diversity regions of southern Siberia would generate a local positive radiative forcing of 5.1±2.6 W m^?2. This radiative heating would reinforce the warming projected to occur in the area under climate change.     

BorealFireSim: A GIS-based cellular automata model of wildfires for the boreal forest of Quebec in a climate change paradigm

Wildfires are the main cause of forest disturbance in the boreal forest of Canada. Climate change studies forecast important changes in fire cycles, such as increases in fire intensity, severity, and occurrence. The geographical information system (GIS) based cellular automata model, BorealFireSim, serves as a tool to identify future fire patterns in the boreal forest of Quebec, Canada. The model was calibrated using 1950–2010 climate data for the present baseline and forecasts of burning probability up to 2100 were calculated using two RCP scenarios of climate change. Results show that, with every scenario, the mean area burned will likely increase on a provincial scale, while some areas might expect decreases with a low emission scenario. Comparison with other models shows that areas forecasted to have an increase in fire likelihood, overlap with predicted areas of higher vegetation productivity. The results presented in this research aid identifying key areas for fire-dependent species in the near future.     

Tree line identification from pollen data: beyond the limit?

Aim The boreal tree line is a prominent biogeographic feature, the position of which reflects climatic conditions. Pollen is the key sensor used to reconstruct past tree line patterns. Our aims in this study were to investigate pollen–vegetation relationships at the boreal tree line and to assess the success of a modified version of the biomization method that incorporates pollen productivity and dispersal in distinguishing the tree line. Location Northern Canada (307 sites) and Alaska (316 sites). Methods The REVEALS method for estimating regional vegetation composition from pollen data was simplified to provide correction factors to account for differential production and dispersal of pollen among taxa. The REVEALS‐based correction factors were used to adapt the biomization method and applied as a set of experiments to pollen data from lake sediments and moss polsters from the boreal tree line. Proportions of forest and tundra predicted from modern pollen samples along two longitudinal transects were compared with those derived from a vegetation map by: (1) a tally of ‘correct’ versus ‘incorrect’ assignments using vegetation in the relevant map pixels, and (2) a comparison of the shape and position of north–south forest‐cover curves generated from all transect pixels and from pollen data. Possible causes of bias in the misclassifications were assessed. Results Correcting for pollen productivity alone gave fewest misclassifications and the closest estimate of the modern mapped tree line position (Canada, + 300 km; Alaska, + 10 km). In Canada success rates were c. 40–70% and all experiments over‐predicted forest cover. Most corrections improved results over uncorrected biomization; using only lakes improved success rates to c. 80%. In Alaska success rates were 70–80% and classification errors were more evenly distributed; there was little improvement over uncorrected biomization. Main conclusions Corrected biomization should improve broad‐scale reconstructions of spatial patterns in forest/non‐forest vegetation mosaics and across climate‐sensitive ecotones. The Canadian example shows this is particularly the case in regions affected by taxa with extremely high pollen productivity (such as Pinus). Improved representation of actual vegetation distribution is most likely if pollen data from lake sediments are used because the REVEALS algorithm is based on the pollen dynamics of lake‐based systems.     

Climate and vegetation hierarchically structure patterns of songbird distribution in the Canadian boreal region

Environmental factors controlling the distribution and abundance of boreal avifauna are not fully understood, limiting our ability to predict the consequences of a changing climate and industrial development activities underway. We used a compilation of avian point‐count data, collected over 1990–2008 from nearly 36 000 locations, to model the abundance of individual forest songbird species within the Canadian boreal forest. We evaluated 30 vegetation and 101 climatic variables, representing most of the widely‐used dimensions of climate space, along with less usual measures of inter‐annual variability. Regression tree models allowed us to calculate the relative importance of climate and vegetation variable classes according to avian migration strategy without the need for a priori variable selection or dimension reduction. We tested for hierarchical habitat selection by formulating hypotheses on the locations of variables within the model tree structures. Climate variables explained the majority (77%) of deviance explained over 98 species modelled. As may be expected at high latitudes, we found energy availability (temperature, 65%) to be more important than moisture availability (precipitation, 12%). The contributions of inter‐ and intra‐annual climate variability (28%) were about half that of mean conditions. The relatively large contribution of remotely‐sensed vegetation metrics (23%) highlighted the importance of local vegetation heterogeneity controlled by non‐climatic factors. The two most important vegetation variables were landcover type and April leaf area index. When selected, these generally occurred in a model's right subtree, consistent with predictions from hierarchical habitat selection theory. When occupying the root node, landcover effectively delineated the historical forest‐prairie ecotone, reflecting the current disequilibrium between climate and vegetation due to human land use. Our findings suggest a large potential for avian distributional shifts in response to climate change, but also demonstrate the importance of finer scale vegetation heterogeneity in the spatial distribution of boreal birds.     

Assessing the response of area burned to changing climate in western boreal North America using a Multivariate Adaptive Regression Splines (MARS) approach

Fire is a common disturbance in the North American boreal forest that influences ecosystem structure and function. The temporal and spatial dynamics of fire are likely to be altered as climate continues to change. In this study, we ask the question: how will area burned in boreal North America by wildfire respond to future changes in climate? To evaluate this question, we developed temporally and spatially explicit relationships between air temperature and fuel moisture codes derived from the Canadian Fire Weather Index System to estimate annual area burned at 2.5° (latitude × longitude) resolution using a Multivariate Adaptive Regression Spline (MARS) approach across Alaska and Canada. Burned area was substantially more predictable in the western portion of boreal North America than in eastern Canada. Burned area was also not very predictable in areas of substantial topographic relief and in areas along the transition between boreal forest and tundra. At the scale of Alaska and western Canada, the empirical fire models explain on the order of 82% of the variation in annual area burned for the period 1960–2002. July temperature was the most frequently occurring predictor across all models, but the fuel moisture codes for the months June through August (as a group) entered the models as the most important predictors of annual area burned. To predict changes in the temporal and spatial dynamics of fire under future climate, the empirical fire models used output from the Canadian Climate Center CGCM2 global climate model to predict annual area burned through the year 2100 across Alaska and western Canada. Relative to 1991–2000, the results suggest that average area burned per decade will double by 2041–2050 and will increase on the order of 3.5–5.5 times by the last decade of the 21st century. To improve the ability to better predict wildfire across Alaska and Canada, future research should focus on incorporating additional effects of long‐term and successional vegetation changes on area burned to account more fully for interactions among fire, climate, and vegetation dynamics.     

The climate,the fuel and the land use: Long‐term regional variability of biomass burning in boreal forests

The influence of different drivers on changes in North American and European boreal forests biomass burning (BB) during the Holocene was investigated based on the following hypotheses: land use was important only in the southernmost regions, while elsewhere climate was the main driver modulated by changes in fuel type. BB was reconstructed by means of 88 sedimentary charcoal records divided into six different site clusters. A statistical approach was used to explore the relative contribution of (a) pollen‐based mean July/summer temperature and mean annual precipitation reconstructions, (b) an independent model‐based scenario of past land use (LU), and (c) pollen‐based reconstructions of plant functional types (PFTs) on BB. Our hypotheses were tested with: (a) a west‐east northern boreal sector with changing climatic conditions and a homogeneous vegetation, and (b) a north‐south European boreal sector characterized by gradual variation in both climate and vegetation composition. The processes driving BB in boreal forests varied from one region to another during the Holocene. However, general trends in boreal biomass burning were primarily controlled by changes in climate (mean annual precipitation in Alaska, northern Quebec, and northern Fennoscandia, and mean July/summer temperature in central Canada and central Fennoscandia) and, secondarily, by fuel composition (BB positively correlated with the presence of boreal needleleaf evergreen trees in Alaska and in central and southern Fennoscandia). Land use played only a marginal role. A modification towards less flammable tree species (by promoting deciduous stands over fire‐prone conifers) could contribute to reduce circumboreal wildfire risk in future warmer periods.     

Structural complexity and land‐surface energy exchange along a gradient from arctic tundra to boreal forest

Question: Current climate changes in the Alaskan Arctic, which are characterized by increases in temperature and length of growing season, could alter vegetation structure, especially through increases in shrub cover or the movement of treeline. These changes in vegetation structure have consequences for the climate system. What is the relationship between structural complexity and partitioning of surface energy along a gradient from tundra through shrub tundra to closed canopy forest? Location: Arctic tundra‐boreal forest transition in the Alaskan Arctic. Methods: Along this gradient of increasing canopy complexity, we measured key vegetation characteristics, including community composition, biomass, cover, height, leaf area index and stem area index. We relate these vegetation characteristics to albedo and the partitioning of net radiation into ground, latent, and sensible heating fluxes. Results: Canopy complexity increased along the sequence from tundra to forest due to the addition of new plant functional types. This led to non‐linear changes in biomass, cover, and height in the understory. The increased canopy complexity resulted in reduced ground heat fluxes, relatively conserved latent heat fluxes and increased sensible heat fluxes. The localized warming associated with increased sensible heating over more complex canopies may amplify regional warming, causing further vegetation change in the Alaskan Arctic.     

Effects of reindeer on boreal forest floor vegetation: Does grazing cause vegetation state transitions?

Intensive reindeer grazing has been hypothesized to drive vegetation shifts in the arctic tundra from a low-productive lichen dominated state to a more productive moss dominated state. Although the more productive state can potentially host more herbivores, it may still be less suitable as winter grazing grounds for reindeer, if lichens, the most preferred winter forage, are less abundant. Therefore, such a shift towards mosses may have severe consequences for reindeer husbandry if ground-growing lichens have difficulties to recover. We tested if reindeer cause this type of vegetation state shifts in boreal forest floor vegetation, by comparing plant species composition and major soil processes inside and outside of more than 40-year-old exclosures. Lichen biomass was more than twice as high inside exclosures than in grazed controls and almost 5 times higher than in heavily grazed patches. Contrary to our predictions, net N mineralization and plant production were higher in the exclosures than in the grazed controls. The lack of response of phytometer plants in a common garden bioassay indicated that changed soil moisture may drive effects of reindeer on plant productivity in these dry Pine forest ecosystems.     

Microhabitat nest‐site selection by ducks in the boreal forest

The boreal forest is one of the North America’s most important breeding areas for ducks, but information about the nesting ecology of ducks in the region is limited. We collected microhabitat data related to vegetation structure and composition at 157 duck nests and paired random locations in Alberta’s boreal forest region from 2016 to 2018. We identified fine‐scale vegetation features selected by ducks for all nests, between nesting guilds, and among five species using conditional logistic regression. Ducks in the boreal forest selected nest sites with greater overhead and graminoid cover, but less forb cover than random sites. Characteristics of the nest sites of upland‐ and overwater‐nesting guilds differed, with species nesting in upland habitat selecting nests that provided greater shrub cover and less lateral concealment and species nesting over water selecting nests with less shrub cover. We examined the characteristics of nest sites of American Wigeon (Mareca americana), Blue‐winged Teal (Spatula discors), Green‐winged Teal (Anas crecca), Mallards (Anas platyrhynchos), and Ring‐necked Ducks (Aythya collaris), and found differences among species that may facilitate species coexistence at a regional scale. Our results suggest that females of species nesting in upland habitat selected nest sites that optimized concealment from aerial predators while also allowing detection of and escape from terrestrial predators. Consequently, alteration in the composition and heterogeneity of vegetation and predator communities caused by climate change and industrial development in the boreal forest of Canada may affect the nest‐site selection strategies of boreal ducks.     

气候变化和不同强度造林对大兴安岭主要树种林分信息和地上生物量的长期影响

气候变化及相应火干扰在不同尺度上影响着我国大兴安岭地区森林动态,且在未来的影响可能继续加剧。为了提高森林生态功能和应对气候变暖,国家在分类经营基础上全面实施抚育采伐和补植造林,效果较好,但抚育采伐对森林主要树种的长期影响知之甚少,其在未来气候下的可持续性也有待进一步评估,同时,探讨造林措施对未来森林的影响也显得尤为重要。本文运用森林景观模型LANDIS PRO,模拟气候变化及火干扰、采伐和造林对大兴安岭地区主要树种的长期影响。结果表明:1)模型初始化、短期和长期模拟结果均得到了有效验证,模拟结果与森林调查数据之间无显著性差异(P0.05),基于火烧迹地数据的林火干扰验证亦能够反映当前火干扰的效果,模型模拟结果的可信度较高;2)与当前气候相比,气候变暖及火干扰明显改变了树种组成、年龄结构和地上生物量,B1气候下研究区森林基本上以针叶树种为主要树种,A2气候下优势树种向阔叶树转变;3)与无采伐预案相比,当前气候下,抚育采伐使落叶松的林分密度和地上生物量分别降低了(165±94.9)株/hm~2和(8.5±5.1) Mg/hm~2,增加了樟子松、白桦和云杉等树木株数和地上生物量(3.3—753.4株/hm~2和0.2—4.0 Mg/hm~2),而对山杨的影响较小;B1和A2气候下抚育采伐显著改变林分密度,降低景观尺度地上生物量,进而表现为不可持续;4)B1气候下,推荐实施中低强度造林预案(10%和20%强度),在A2气候下,各强度造林均可在模拟后期增加树种地上生物量。     

Within‐stand spatial structure and relation of boreal canopy and understorey vegetation

Question: How do spatial patterns and associations of canopy and understorey vegetation vary with spatial scale along a gradient of canopy composition in boreal mixed‐wood forests, from younger Aspen stands dominated by Populus tremuloides and P. balsamifera to older Mixed and Conifer stands dominated by Picea glauca? Do canopy evergreen conifers and broad‐leaved deciduous trees differ in their spatial relationships with understorey vegetation? Location: EMEND experimental site, Alberta, Canada. Methods: Canopy and understorey vegetation were sampled in 28 transects of 100 contiguous 0.5 m × 0.5 m quadrats in three forest stand types. Vegetation spatial patterns and relationships were analysed using wavelets. Results: Boreal mixed‐wood canopy and understorey vegetation are patchily distributed at a range of small spatial scales. The scale of canopy and understorey spatial patterns generally increased with increasing conifer presence in the canopy. Associations between canopy and understorey were highly variable among stand types, transects and spatial scales. Understorey vascular plant cover was generally positively associated with canopy deciduous tree cover and negatively associated with canopy conifer tree cover at spatial scales from 5–15 m. Understorey non‐vascular plant cover and community composition were more variable in their relationships with canopy cover, showing both positive and negative associations at a range of spatial scales. Conclusions: The spatial structure and relation of boreal mixed‐wood canopy and understorey vegetation varied with spatial scale. Differences in understorey spatial structure among stand types were consistent with a nucleation model of patch dynamics during succession in boreal mixed‐wood forests.     

Fire severity mediates climate‐driven shifts in understorey community composition of black spruce stands of interior Alaska

Question: How do pre‐fire conditions (community composition and environmental characteristics) and climate‐driven disturbance characteristics (fire severity) affect post‐fire community composition in black spruce stands? Location: Northern boreal forest, interior Alaska. Methods: We compared plant community composition and environmental stand characteristics in 14 black spruce stands before and after multiple, naturally occurring wildfires. We used a combination of vegetation table sorting, univariate (ANOVA, paired t‐tests), and multivariate (detrended correspondence analysis) statistics to determine the impact of fire severity and site moisture on community composition, dominant species and growth forms. Results: Severe wildfires caused a 50% reduction in number of plant species in our study sites. The largest species loss, and therefore the greatest change in species composition, occurred in severely burned sites. This was due mostly to loss of non‐vascular species (mosses and lichens) and evergreen shrubs. New species recruited most abundantly to severely burned sites, contributing to high species turnover on these sites. As well as the strong effect of fire severity, pre‐fire and post‐fire mineral soil pH had an effect on post‐fire vegetation patterns, suggesting a legacy effect of site acidity. In contrast, pre‐fire site moisture, which was a strong determinant of pre‐fire community composition, showed no relationship with post‐fire community composition. Site moisture was altered by fire, due to changes in permafrost, and therefore post‐fire site moisture overrode pre‐fire site moisture as a strong correlate. Conclusions: In the rapidly warming climate of interior Alaska, changes in fire severity had more effect on post‐fire community composition than did environmental factors (moisture and pH) that govern landscape patterns of unburned vegetation. This suggests that climate change effects on future community composition of black spruce forests may be mediated more strongly by fire severity than by current landscape patterns. Hence, models that represent the effects of climate change on boreal forests could improve their accuracy by including dynamic responses to fire disturbance.     

Net primary productivity mapped for Canada at 1-km resolution

Aim To map net primary productivity (NPP) over the Canadian landmass at 1‐km resolution. Location Canada. Methods A simulation model, the Boreal Ecosystem Productivity Simulator (BEPS), has been developed. The model uses a sunlit and shaded leaf separation strategy and a daily integration scheme in order to implement an instantaneous leaf‐level photosynthesis model over large areas. Two key driving variables, leaf area index (every 10 days) and land cover type (annual), are derived from satellite measurements of the Advanced Very High Resolution Radiometer (AVHRR). Other spatially explicit input data are also prepared, including daily meteorological data (radiation, precipitation, temperature, and humidity), available soil water holding capacity (AWC) and forest biomass. The model outputs are compared with ground plot data to ensure that no significant systematic biases are created. Results The simulation results show that Canada’s annual net primary production was 1.22 Gt C year^?1 in 1994, 78% attributed to forests, mainly the boreal forest, without considering the contribution of the understorey. The NPP averaged over the entire landmass was ~140 g C m^?2 year^?1 in 1994. Geographically, NPP varied greatly among ecozones and provinces/territories. The seasonality of NPP is characterized by strong summer photosynthesis capacities and a short growing season in northern ecosystems. Conclusions This study is the first attempt to simulate Canada‐wide NPP with a process‐based model at 1‐km resolution and using a daily step. The statistics of NPP are therefore expected to be more accurate than previous analyses at coarser spatial or temporal resolutions. The use of remote sensing data makes such simulations possible. BEPS is capable of integrating the effects of climate, vegetation, and soil on plant growth at a regional scale. BEPS and its parameterization scheme and products can be a basis for future studies of the carbon cycle in mid‐high latitude ecosystems.