Postfire response of North American boreal forest net primary productivity analyzed with satellite observations

Fire is a major disturbance in the boreal forest, and has been shown to release significant amounts of carbon (C) to the atmosphere through combustion. However, less is known about the effects on ecosystems following fire, which include reduced productivity and changes in decomposition in the decade immediately following the disturbance. In this study, we assessed the impact of fire on net primary productivity (NPP) in the North American boreal forest using a 17‐year record of satellite NDVI observations at 8‐ km spatial resolution together with a light‐use efficiency model. We identified 61 fire scars in the satellite observations using digitized fire burn perimeters from a database of large fires. We studied the postfire response of NPP by analyzing the most impacted pixel within each burned area. NPP decreased in the year following the fire by 60–260 g C m^?2 yr^?1 (30–80%). By comparing pre‐ and postfire observations, we estimated a mean NPP recovery period for boreal forests of about 9 years, with substantial variability among fires. We incorporated this behavior into a carbon cycle model simulation to demonstrate these effects on net ecosystem production. The disturbance resulted in a release of C to the atmosphere during the first 8 years, followed by a small, but long‐lived, sink lasting 150 years. Postfire net emissions were three times as large as from a model run without changing NPP. However, only small differences in the C cycle occurred between runs after 8 years due to the rapid recovery of NPP. We conclude by discussing the effects of fire on the long‐term continental trends in satellite NDVI observed across boreal North America during the 1980s and 1990s.     

Relationships between individual‐tree mortality and water‐balance variables indicate positive trends in water stress‐induced tree mortality across North America

Accounting for water stress‐induced tree mortality in forest productivity models remains a challenge due to uncertainty in stress tolerance of tree populations. In this study, logistic regression models were developed to assess species‐specific relationships between probability of mortality (P_m) and drought, drawing on 8.1 million observations of change in vital status (m) of individual trees across North America. Drought was defined by standardized (relative) values of soil water content (W_s,z) and reference evapotranspiration (ET_r,z) at each field plot. The models additionally tested for interactions between the water‐balance variables, aridity class of the site (AC), and estimated tree height (h). Considering drought improved model performance in 95 (80) per cent of the 64 tested species during calibration (cross‐validation). On average, sensitivity to relative drought increased with site AC (i.e. aridity). Interaction between water‐balance variables and estimated tree height indicated that drought sensitivity commonly decreased during early height development and increased during late height development, which may reflect expansion of the root system and decreasing whole‐plant, leaf‐specific hydraulic conductance, respectively. Across North America, predictions suggested that changes in the water balance caused mortality to increase from 1.1% yr^?1 in 1951 to 2.0% yr^?1 in 2014 (a net change of 0.9 ± 0.3% yr^?1). Interannual variation in mortality also increased, driven by increasingly severe droughts in 1988, 1998, 2006, 2007 and 2012. With strong confidence, this study indicates that water stress is a common cause of tree mortality. With weak‐to‐moderate confidence, this study strengthens previous claims attributing positive trends in mortality to increasing levels of water stress. This ‘learn‐as‐we‐go’ approach – defined by sampling rare drought events as they continue to intensify – will help to constrain the hydraulic limits of dominant tree species and the viability of boreal and temperate forest biomes under continued climate change.     

Interpreting multiscale domains of tree cover disturbance patterns in North America

Spatial patterns at multiple observation scales provide a framework to improve understanding of pattern-related phenomena. However, the metrics that are most sensitive to local patterns are least likely to exhibit consistent scaling relations with increasing extent (observation scale). A conceptual framework based on multiscale domains (i.e., geographic locations exhibiting similar scaling relations) allows the use of sensitive pattern metrics, but more work is needed to understand the actual patterns represented by multiscale domains. The objective of this study was to improve the interpretation of scale-dependent patterns represented by multiscale domains. Using maps of tree cover disturbance covering North American forest biomes from 2000 to 2012, each 0.09-ha location was described by the proportion and contagion of disturbance in its neighborhood, for 10 neighborhood extents from 0.81 ha to 180 km². A k-means analysis identified 13 disturbance profiles based on the similarity of disturbance proportion and contagion across neighborhood extent. A wall to wall map of multiscale domains was produced by assigning each location (disturbed and undisturbed) to its nearest disturbance profile in multiscale pattern space. The multiscale domains were interpreted as representing two aspects of local patterns – the proximity of a location to disturbance, and the interior-exterior relationship of a location relative to nearby disturbed areas.     

The influence of cattle grazing on tree mortality after drought in savanna woodland in north Queensland

Abstract Live and dead trees were measured in macropod-grazed and cattle-grazed Eucalyptus woodland in north Queensland following a severe drought between 1992 and 1994. ANCOVA revealed no effect of grazing treatment on the proportion of drought death. Twenty-seven per cent of all tree species were killed by the drought and the value ranged from about 4% for Corymbia dallachiana (Benth.), K. D. Hlll & L. A. S. Johnson to 29% for the dominant species Eucalyptus xanthoclada Brooker and A.R.Bean, although differences were non-significant. There was also no significant difference in mortality between poles (< 10 cm d.b.h.) and trees (> 10 cm d.b.h.). The study highlights a natural (as in pre-European), catastrophic structural collapse of tropical eucalypt woodland. Presumably the dramatic declines in basal area as a result of drought are recovered during successive relatively wet years by thickening events, although clearly this severe drought and its after-effects warrant further study.     

The greening and browning of Alaska based on 1982–2003 satellite data

Aim To examine the trends of 1982–2003 satellite‐derived normalized difference vegetation index (NDVI) values at several spatial scales within tundra and boreal forest areas of Alaska. Location Arctic and subarctic Alaska. Methods Annual maximum NDVI data from the twice monthly Global Inventory Modelling and Mapping Studies (GIMMS) NDVI 1982–2003 data set with 64‐km² pixels were extracted from a spatial hierarchy including three large regions: ecoregion polygons within regions, ecozone polygons within boreal ecoregions and 100‐km climate station buffers. The 1982–2003 trends of mean annual maximum NDVI values within each area, and within individual pixels, were computed using simple linear regression. The relationship between NDVI and temperature and precipitation was investigated within climate station buffers. Results At the largest spatial scale of polar, boreal and maritime regions, the strongest trend was a negative trend in NDVI within the boreal region. At a finer scale of ecoregion polygons, there was a strong positive NDVI trend in cold arctic tundra areas, and a strong negative trend in interior boreal forest areas. Within boreal ecozone polygons, the weakest negative trends were from areas with a maritime climate or colder mountainous ecozones, while the strongest negative trends were from warmer basin ecozones. The trends from climate station buffers were similar to ecoregion trends, with no significant trends from Bering tundra buffers, significant increasing trends among arctic tundra buffers and significant decreasing trends among interior boreal forest buffers. The interannual variability of NDVI among the arctic tundra buffers was related to the previous summer warmth index. The spatial pattern of increasing tundra NDVI at the pixel level was related to the west‐to‐east spatial pattern in changing climate across arctic Alaska. There was no significant relationship between interannual NDVI and precipitation or temperature among the boreal forest buffers. The decreasing NDVI trend in interior boreal forests may be due to several factors including increased insect/disease infestations, reduced photosynthesis and a change in root/leaf carbon allocation in response to warmer and drier growing season climate. Main conclusions There was a contrast in trends of 1982–2003 annual maximum NDVI, with cold arctic tundra significantly increasing in NDVI and relatively warm and dry interior boreal forest areas consistently decreasing in NDVI. The annual maximum NDVI from arctic tundra areas was strongly related to a summer warmth index, while there were no significant relationships in boreal areas between annual maximum NDVI and precipitation or temperature. Annual maximum NDVI was not related to spring NDVI in either arctic tundra or boreal buffers.     

Drought-induced increase in tree mortality and corresponding decrease in the carbon sink capacity of Canada's boreal forests from 1970 to 2020

Canada's boreal forests, which occupy approximately 30% of boreal forests worldwide, play an important role in the global carbon budget. However, there is little quantitative information available regarding the spatiotemporal changes in the drought-induced tree mortality of Canada's boreal forests overall and their associated impacts on biomass carbon dynamics. Here, we develop spatiotemporally explicit estimates of drought-induced tree mortality and corresponding biomass carbon sink capacity changes in Canada's boreal forests from 1970 to 2020. We show that the average annual tree mortality rate is approximately 2.7%. Approximately 43% of Canada's boreal forests have experienced significantly increasing tree mortality trends (71% of which are located in the western region of the country), and these trends have accelerated since 2002. This increase in tree mortality has resulted in significant biomass carbon losses at an approximate rate of 1.51 ± 0.29 MgC ha⁻¹ year⁻¹ (95% confidence interval) with an approximate total loss of 0.46 ± 0.09 PgC year⁻¹ (95% confidence interval). Under the drought condition increases predicted for this century, the capacity of Canada's boreal forests to act as a carbon sink will be further reduced, potentially leading to a significant positive climate feedback effect.     

Moderate disturbances accelerate forest transition dynamics under climate change in the temperate–boreal ecotone of eastern North America

Several temperate tree species are expected to migrate northward and colonize boreal forests in response to climate change. Tree migrations could lead to transitions in forest types, but these could be influenced by several non‐climatic factors, such as disturbances and soil conditions. We analysed over 10,000 forest inventory plots, sampled from 1970 to 2018 in meridional Québec, Canada, to identify what environmental conditions promote or prevent regional‐scale forest transitions. We used a continuous‐time multi‐state Markov model to quantify the probabilities of transitions between forest states (temperate, boreal, mixed, pioneer) as a function of climate (mean temperature and climate moisture index during the growing season), soil conditions (pH and drainage) and disturbances (severity levels of natural disturbances and logging). We further investigate how different disturbance types and severities impact forests' short‐term transient dynamics and long‐term equilibrium using properties of Markov transition matrices. The most common transitions observed during the study period were from mixed to temperate states, as well as from pioneer to boreal forests. In our study, transitions were mainly driven by natural and anthropogenic disturbances and secondarily by climate, whereas soil characteristics exerted relatively minor constraints. While major disturbances only promoted transitions to the pioneer state, moderate disturbances increased the probability of transition from mixed to temperate states. Long‐term projections of our model under the current environmental conditions indicate that moderate disturbances would promote a northward shift of the temperate forest. Moreover, disturbances reduced turnover and convergence time for all transitions, thereby accelerating forest dynamics. Contrary to our expectation, mixed to temperate transitions were not driven by temperate tree recruitment but by mortality and growth. Overall, our results suggest that moderate disturbances could catalyse rapid forest transitions and accelerate broad‐scale biome shifts.     

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.     

Emergent climate and CO2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America

Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multimodel comparisons with data have largely focused on individual processes at subannual to decadal scales. Thus far, data‐based evaluations of emergent ecosystem responses to climate and CO₂ at multidecadal and centennial timescales have been rare. We compared the sensitivity of net primary productivity (NPP) to temperature, precipitation, and CO₂ in ten ecosystem models with the sensitivities found in tree‐ring reconstructions of NPP and raw ring‐width series at six temperate forest sites. These model‐data comparisons were evaluated at three temporal extents to determine whether the rapid, directional changes in temperature and CO₂ in the recent past skew our observed responses to multiple drivers of change. All models tested here were more sensitive to low growing season precipitation than tree‐ring NPP and ring widths in the past 30 years, although some model precipitation responses were more consistent with tree rings when evaluated over a full century. Similarly, all models had negative or no response to warm‐growing season temperatures, while tree‐ring data showed consistently positive effects of temperature. Although precipitation responses were least consistent among models, differences among models to CO₂ drive divergence and ensemble uncertainty in relative change in NPP over the past century. Changes in forest composition within models had no effect on climate or CO₂ sensitivity. Fire in model simulations reduced model sensitivity to climate and CO₂, but only over the course of multiple centuries. Formal evaluation of emergent model behavior at multidecadal and multicentennial timescales is essential to reconciling model projections with observed ecosystem responses to past climate change. Future evaluation should focus on improved representation of disturbance and biomass change as well as the feedbacks with moisture balance and CO₂ in individual models.     

基于树木年轮定量重建过去50年贵州典型森林优势树种的地上生物量与生产力变化

利用树木年轮宽度结合树木生物量方程,重建了贵州3个地区典型森林(2个常绿与落叶阔叶混交林和1个典型常绿阔叶林)6个优势树种(天龙山:化香树Platycarya strobilacea、安顺润楠Machilus cavaleriei;茂兰:化香树、马尾松Pinus massoniana;雷公山:华山松Pinus armandii、白梓树Pterostyrax psilophyllus)以树木个体为单元的地上生物量(AGB)与地上净初级生产力(ANPP);比较了喀斯特与非喀斯特地区树木AGB与ANPP的差异;并研究了近50年气候变化对ANPP的影响。结果显示,针叶树的平均年轮宽度大于阔叶树,喀斯特地区针叶树和阔叶树的平均树木年轮宽度,分别小于非喀斯特地区针叶树和阔叶树的平均树木年轮宽度。喀斯特地区树木的AGB及其变异幅度均小于非喀斯特地区树木。近50年来,喀斯特地区阔叶树与针叶树的ANPP平均分别为(2.4±1.2) kg a^-1株^-1和(4.6±4.1) kg a^-1株^-1,显著低于非喀斯特地区阔叶树...     

Assessing the response of forest productivity to climate extremes in Switzerland using model–data fusion

The response of forest productivity to climate extremes strongly depends on ambient environmental and site conditions. To better understand these relationships at a regional scale, we used nearly 800 observation years from 271 permanent long‐term forest monitoring plots across Switzerland, obtained between 1980 and 2017. We assimilated these data into the 3‐PG forest ecosystem model using Bayesian inference, reducing the bias of model predictions from 14% to 5% for forest stem carbon stocks and from 45% to 9% for stem carbon stock changes. We then estimated the productivity of forests dominated by Picea abies and Fagus sylvatica for the period of 1960–2018, and tested for productivity shifts in response to climate along elevational gradient and in extreme years. Simulated net primary productivity (NPP) decreased with elevation (2.86 ± 0.006 Mg C ha^?1 year^?1 km^?1 for P. abies and 0.93 ± 0.010 Mg C ha^?1 year^?1 km^?1 for F. sylvatica). During warm–dry extremes, simulated NPP for both species increased at higher and decreased at lower elevations, with reductions in NPP of more than 25% for up to 21% of the potential species distribution range in Switzerland. Reduced plant water availability had a stronger effect on NPP than temperature during warm‐dry extremes. Importantly, cold–dry extremes had negative impacts on regional forest NPP comparable to warm–dry extremes. Overall, our calibrated model suggests that the response of forest productivity to climate extremes is more complex than simple shift toward higher elevation. Such robust estimates of NPP are key for increasing our understanding of forests ecosystems carbon dynamics under climate extremes.     

利用马尾松年轮资料重建江苏暖湿地区气候的初步研究

利用树木年轮气候学方法,根据马尾松生长对气候变量具非线性响应,尝试重建江苏暖湿地区过去１１６年（１８７４～１９９０）的年平均气温和降水量。温度的重建效果优于降水量,实测值与重建值两者的缩减误差（ＲＥ）分别为０．１２和０．１０,两者的平均偏差百分率分别为２．３％和２０％。绝大部分重建结果可从观测记录和历史文献中得到验证,但在温度较高或降水量较多的若干年份,实测值与重建值有较大偏差。