Management of temperate forests has the potential to increase carbon sinks and mitigate climate change. However, those opportunities may be confounded by negative climate change impacts. We therefore need a better understanding of climate change alterations to temperate forest carbon dynamics before developing mitigation strategies. The purpose of this project was to investigate the interactions of species composition, fire, management, and climate change in the Copper–Pine Creek valley, a temperate coniferous forest with a wide range of growing conditions. To do so, we used the LANDIS-II modelling framework including the new Forest Carbon Succession extension to simulate forest ecosystems under four different productivity scenarios, with and without climate change effects, until 2050. Significantly, the new extension allowed us to calculate the net sector productivity, a carbon accounting metric that integrates aboveground and belowground carbon dynamics, disturbances, and the eventual fate of forest products. The model output was validated against literature values. The results implied that the species optimum growing conditions relative to current and future conditions strongly influenced future carbon dynamics. Warmer growing conditions led to increased carbon sinks and storage in the colder and wetter ecoregions but not necessarily in the others. Climate change impacts varied among species and site conditions, and this indicates that both of these components need to be taken into account when considering climate change mitigation activities and adaptive management. The introduction of a new carbon indicator, net sector productivity, promises to be useful in assessing management effectiveness and mitigation activities.
As a global society, we depend on forests and land to take up about 2.5
Temperate forests offer many opportunities for increasing carbon sinks;
however, the risk of negative climate change effects and poor management
decisions may limit these opportunities. For example, starting from 2000 a
bark beetle outbreak (
Forest carbon dynamics depend on the management regime, expected growth and
mortality rates, regeneration ingress, decomposition rates, and natural
disturbances (Canadell and Raupach, 2008). The existing literature documents
the complexity of forest carbon dynamics to potential rising temperatures,
changing precipitation patterns, increasing atmospheric CO
An additional aspect of forest carbon dynamics typically excluded from ecosystem studies is the storage of carbon in harvested wood products. The storage and emissions from wood products have been shown to be important for considering emissions due to forest management, climate change mitigation activities, and life cycle assessments (e.g. Hennigar et al., 2008; Smyth et al., 2014; Lamers et al., 2014). While the combination of ecosystem and wood product carbon dynamics is recognised as important, there is a mixture of indicators (typically stocks) and terms in the literature. Here we propose a new metric, net sector productivity, to facilitate calculation and comparison among studies. This metric is based on the net ecosystem productivity minus emissions from disturbances and wood products.
Our purpose was to improve our understanding of the interactions of species
composition, climate change, fire, and management in temperate forest
ecosystem carbon dynamics. The Copper–Pine Creek valley in north-western BC
provides an exemplary landscape because it includes a variety of forest
ecosystems with naturally varying climate envelopes, tree species
composition, management activities, and natural disturbance rates within a
relatively small area of under 750 km
Ecoregions for LANDIS-II, biogeoclimatic variant names as used in BC, and fire regime zones as used in this study.
The Copper–Pine Creek study area (black polygon) near Smithers, Canada; ecoregions for LANDIS-II modelling and photograph looking south-west across part of the study area. See Table 1 for ecoregion descriptions.
The study area is 734 km
We simulated the forest dynamics using LANDIS-II, a spatially explicit forest
landscape modelling framework used to integrate ecosystem processes,
management, and disturbances (Scheller et al., 2007). LANDIS-II is a
framework within which users can choose amongst different extensions to
simulate stand dynamics and disturbances. The 39-year simulation period
(2012–2050) was run at a 100
The Forest Carbon Succession v2.0 (ForCSv2) extension for LANDIS-II
calculates how cohorts of trees reproduce, age, and die (Dymond et al.,
2012). Furthermore, changes in cohort biomass carbon, dead organic matter
(DOM), and soil carbon are tracked over time (Fig. 3). In addition to the
carbon stocks for each of 14 pools, ForCSv2 reports the fluxes: turnover, net
growth, net primary production (NPP), heterotrophic respiration
(
The ForCSv2 extension is integrated with harvesting, fire, and wind extensions of LANDIS-II. When a disturbance occurs, species-age cohorts may be killed by the disturbance extension. The transfers of carbon from biomass pools to dead organic matter, air, or the forest products sector are controlled by user input. In addition, disturbances can trigger emissions and transfers from the dead organic matter or soil pools. For the Copper–Pine Creek study area, wildfire impacts on carbon pools were based on Campbell et al. (2007). For harvest impacts, the model transferred 80 % of the merchantable-sized wood biomass out of the ecosystem during an event; any other killed biomass was transferred to the DOM pools.
LANDIS-II has stochastic processes including wildfires and natural
regeneration. Therefore, we calculated landscape averages and standard
deviations from 20 Monte Carlo replicates to conduct
The harvested carbon output from ForCSv2 was run through the British Columbia Harvested Wood Product (v1) model (Dymond, 2012) to estimate storage and emissions on an annual basis. Those wood product emission estimates and wildfire emissions were subtracted from NEP to calculate the net sector productivity (NSP).
For the Copper–Pine Creek study area we gathered species life history
parameters required by ForCSv2 from the literature (Table 2). The main
sources of information were Klinka et al. (2000) and Burns and
Honkala (1990). Additional information for
The spatial forest inventory data set maintained by the Government of BC
provided the plant species and age information for the initial communities
map (BC MFLNR, 2011). The leading species in the inventory was most
frequently
For each ecoregion, historical daily weather data were collected from
corresponding meteorological stations and analysed using a rank and
percentile test. Based on the rank and percentile test, 10 historical years
of climate data were selected for each ecoregion and used as the historical
climate scenarios in the analysis. The 10 years of data represent the 90th,
75th, 50th, 25th, and 10th percentiles for both observed annual
precipitation and mean annual temperature (Nitschke et al., 2012). A direct
adjustment approach was used to create climate change scenarios from the
selected historical climate data and global climate model (GCM) predictions
for the study region (Nitschke et al., 2012). Monthly outputs from five GCMs
were obtained from the Pacific Climate Impacts Consortium (PCIC, 2012). The
GCMs and emission scenarios selected were Hadley GEM-A1B, Hadley CM3-A1B,
MIROC HIRES-A1B, GISS AOM-A1B, and Canadian GCM3-A2. Climate change is
projected to increase the study area's mean annual temperature by 1 to
3.5
Life history attributes for LANDIS-II.
Life history attributes for TACA-EM and TACA-GAP. See Table 1 for species codes.
We used the Tree and Climate Assessment Tool Establishment Model (TACA-EM) to
estimate the
Age class distribution in 2011 for the Copper–Pine Creek study area.
We used the Tree and Climate Assessment Tool Growth and Productivity
(TACA-GAP) model to estimate maximum ANPP and maximum biomass variables for
each species in each ecoregion. TACA-GAP uses the growth and response
functions in the BRIND (Shugart and Noble, 1981) and ZELIG
Summary of management prescriptions for different natural resource managers in the study area – the Wetzin'kwa Community Forest (WCF) and the British Columbia Timber Sales (BCTS).
To parameterise the fire regimes we used a combination of available information and scenarios representing possible disturbance regimes. Natural resource managers in the study area typically assume rates of natural disturbance based on the biogeoclimatic zones (BC Environment, 1995). We analysed the fire maps maintained by the Government of BC from the study area and the surrounding region indicated a much lower fire cycle than is assumed by managers (data not shown). Furthermore, studies by Haughain et al. (2012) and Boulanger et al. (2012) also indicate a low fire hazard in the region. Based on the climate parameters and spatial arrangement in the study area, the ecoregions were grouped into the fire regime zones listed in Table 1. The disturbance return intervals for the fire regime zones were assumed to be double those used for forest management. Climate change alterations to the fire regimes are expected to be small, and therefore none were simulated (Haughain et al., 2012).
Model comparison of various temperate forest carbon indicators
between published values and this study. Means
Given the large impact fires can have on carbon dynamics, we ran 20 Monte
Carlo simulations.
Carbon stock estimates in 2012 and 2050 by scenario and ecoregion.
Means and standard deviations were calculated between model simulations.
To determine the credibility of our model results, we conducted a model
comparison based on literature values (Table 5). However, the literature
review demonstrated that carbon stocks in forests are highly variable with
site type and age. The ForCSv2 carbon stock estimates for Copper–Pine Creek
were within the range of other published values for temperate coniferous
forests, except for the coldest ecoregions (1 and 2), which were relatively
low. Likewise, carbon fluxes can vary depending on site type, age,
interannual weather patterns, disturbances, and different models. The ForCSv2
results seem reasonable compared to the literature values, except again for
ecoregion 1, which had a relatively low NPP and
Overall, the probability of establishment decreased by 2050 for most species in most ecoregions (data not shown). The one exception was amabilis fir, which is currently at the northern edge of its range.
Simplified pools and fluxes represented in the Forest Carbon Succession module (v2) for LANDIS-II. In the left panel, carbon accumulates in the tree biomass pools based on the primary productivity input data. When mortality of a whole or part of a tree occurs, the carbon is transferred to the dead organic matter and soil pools in the three right-hand panels, or may be removed from the ecosystem through harvesting or combustion. As decay occurs, carbon is transferred among the dead organic matter and soil pools, eventually entering the belowground slow pool (BGS) or being emitted from the ecosystem. Fire and harvesting can also cause transfers or emissions from the dead organic matter pools.
Climate change alterations of site-level productivity were projected by the TACA-GAP model. The difference between maximum ANPP under the 2041–2070 climate and under the 1961–1990 climate depended on tree species, ecoregion, and global circulation model (Fig. 4). Productivity increased in ecoregions 3 and 4 where all the tree species appear to be currently living in conditions with cooler climates and shorter growing seasons or wetter soils than their optimum conditions (Table 3). In ecoregions 5–7 the results were more variable, depending on the change in conditions relative to the species-specific parameters. Given the decline in productivity by many species in ecoregion 7, these species appear to already be at or beyond optimum climate conditions.
Landscape-scale productivity projections differed in trend and magnitude,
depending on whether the ecoregion was cooler and moister (4) or warmer and
drier (7). Cooler and moister ecoregions were projected to have significantly
higher NPP and NEP because increased species-level productivity outweighed
the increasing temperature, causing greater
For the warmest and driest ecoregion (7), the NPP in the average scenario was
projected to decrease significantly by 2050 due to climate change impacts
(Fig. 5c and d). Resulting from that decreased productivity and the increased
Projections for ecoregion 6 produced different trends than any other
ecoregion. NPP in the average productivity scenario was projected to increase
to a small, but significant degree over no climate change, likely due to
higher productivity in some species offsetting declines in other species
(Fig. 5e). In contrast, NEP was lower in the average productivity scenario
compared to no change, indicating that increased productivity was less than
the increase in
The NBP in different ecoregions not only represents the carbon flux, but also reflects the different disturbance regimes (Figs. 6 and S3). Overall, the map of NBP shows a shift towards a stronger carbon sink. In ecoregions 1 and 2, fires are rare and there is no harvesting, resulting in small standard deviations and less spatial diversity in the NBP mosaic. Throughout the other ecoregions there was a finer mosaic of values throughout most of the landscape in 2050, reflecting the occurrences of harvesting and fires. The largest standard deviations for NBP are in ecoregion 7, which had harvesting and the most frequent fires.
For the landscape as a whole, NPP had a small but significant increase under the average productivity scenario compared to no climate change by 2050 (Fig. 7a). The relatively small change was due to the positive and negative changes in different ecoregions offsetting each other. Similarly, the decline in aboveground biomass in the warmer and drier ecoregions was offset by the increase in biomass in the cooler ecoregions in 2050, resulting in a projected increase in total aboveground biomass for the study area (Fig. 7b). The total landscape NEP followed similar trends to ecoregion 7, with climate change projections resulting in a reduction of NEP, although the landscape was a net carbon sink in most years and most scenarios. Accounting for the loss of carbon due to disturbances by using NBP lessened the differences between the simulations with or without climate change. The landscape was projected to have a NBP closer to zero under the average productivity scenario compared with a sink under no change.
Average ANPP differential from the 1961–1990 climate to 2041–2070 climate average estimated by the TACA-GAP model for the five main modelling ecoregions in the study area. Input NPP for ecoregions 1 and 2 was set at 50 % of regions 3 and 4 respectively.
Climate change impact projections on the NPP and NEP (average
Spatial distribution of NBP under the starting conditions
Climate change was projected to have no effect on the ability of forest managers to achieve the harvest as currently planned (Fig. 8a). However, the harvest rate markedly affected estimates of net carbon fluxes, with the lowest flux values in the first decade when harvest rates were highest (Fig. 8b). Similarly, the difference between the NSP and NBP is greatest during that first decade when harvest rates are high, and therefore considering the storage of carbon in wood products created a noticeable difference at the landscape scale. However, there were no visible trends in the NSP between the no climate change scenario and the average productivity scenario, although only one replicate is shown (Fig. 8c).
Despite our efforts to model climate change effects for each, there were no apparent changes to the distribution of the leading species (Fig. S4). There was however a marked reduction of subalpine fir and an increase in lodgepole pine and interior spruce as leading species through management activity. In contrast, the climate change scenarios did show a marked change in aboveground biomass stocks and spatial distribution of western hemlock (Fig. 9).
The purpose of this study was to improve our understanding of the interactions of species composition, climate change, fire, and management in temperate forest ecosystem carbon dynamics. Therefore we simulated the climate change impacts on productivity and natural regeneration interacting with management and wildfires within a region with steep elevational gradients using a new extension for LANDIS-II. Our results indicate that the effects of climate change on forest productivity and ecosystem carbon dynamics may be significant and substantial, but not uniform. The direction and magnitude of responses depended on the combination of species and site conditions, implying a dependence on how close the current and future climate was to the species optimum. The uncertainty of the changes depended on the assumed productivity and the natural disturbance rate. These results also demonstrate that the ForCSv2 extension to LANDIS-II can provide credible and useful information on future carbon dynamics.
In this study, tree productivity (as estimated by NPP and aboveground biomass) was projected to have the greatest downside risk in the most productive ecoregions (currently having the highest NPP and biomass), which implied that species were at or beyond their optimum conditions. In contrast, the results indicated that the species in the least productive ecoregions were able to take advantage of warmer conditions so as to have increased productivity under climate change. These results are consistent with the literature indicating that more productive areas within a region are likely to experience negative climate change impacts compared to less productive areas (e.g. Boisvenue and Running, 2010), but are in contrast to other studies that do not show this pattern (e.g. Scheller et al., 2012; Creutzburg et al., 2016). Carbon stocks tended to follow changes in productivity, increasing in ecoregions with greater productivity and decreasing where productivity was projected to fall, indicating a lower influence of changing decay rates on the stocks over this simulation period.
Relationship between harvest rate and carbon fluxes for a single
replicate. Removal of carbon from the ecosystem through logging
Over the landscape as a whole, there was a wide range of projected changes in NPP. Other landscape-scale studies of temperate conifer forests have projected increases (e.g. Crookston et al., 2010; Steenberg et al., 2011; Ma et al., 2014), decreases (e.g. Scheller et al., 2012; Galvez et al., 2014; Ma et al., 2014), or little change (e.g. Scheller et al., 2012; Creutzburg et al., 2015; Ma et al., 2014) in biomass or carbon stocks due to climate change.
As with NPP and carbon stocks, net carbon fluxes were highly sensitive to the
ecoregion in both absolute terms and in the impact of climate change. The NEP
and NBP results indicated likely greater carbon sinks due to the productivity
projections in the cooler and moister ecoregions, whereas for the more
productive ecoregions the projections ranged from little difference to
greatly increased carbon emissions due to lower growth and higher decay
rates. Those results differed from those presented by Hudiburg et al. (2013)
for temperate coniferous forests in Oregon, where cumulative NBP was
projected to increase in all regions by the end of the century. However,
those increases were smallest on the coast, the highest productivity region.
Note that their study included a much larger range of climate conditions and
CO
Ecoregion 6 provides the most interesting and counter-intuitive results
because NPP was projected to increase, but NEP decreased, indicating that
increases in productivity were insufficient to counter increased
Our uncertainty estimates for the different indicators were the range in values between the high productivity and low productivity scenarios. This is likely an overestimate of uncertainty because it is unlikely that all species in all ecoregions would follow the same trend of improving or declining productivity.
Western hemlock biomass distribution in 2050 with no climate change (no CC) and high and low productivity scenarios.
The projected leading species of the study area was, to a great extent, driven by management activities, planting in particular. This result reinforces the opportunities identified by others to adapt to climate change through management (e.g. Steenberg et al., 2011; Buma and Wessman, 2013). Adaptation may take the form of planting species currently viable, but with provenances more suitable to future climatic conditions than the ones in the local geographic area (Rehfeldt et al., 1999). That action could also provide climate change mitigation if it prevents declines in productivity. In addition, increasing tree species diversity may increase resilience to forest health damage or as a strategy for dealing with the uncertainty in future projections (Dymond et al., 2014).
The harvest rate in our study was highly variable over time due to the mortality caused by mountain pine beetle triggering salvage logging in the near term in the Wetzink'wa Community Forest (Fig. 8a). Similarly, BC Timber Sales anticipates logging rates decreasing within the study area by about 2020 in part because they operate across a much larger area. The planned harvest was achieved in the simulations despite declining productivity in some areas. This was likely due to the age class distribution of the forest being over 100 years old (Fig. 2). The near-term harvest relies on trees that have already reached maturity, and therefore the growing stock already exists on the landscape. A longer simulation period that incorporates harvesting of second growth stands may have different results. The changing productivity could lead to changes in harvest rates. If monitoring substantiates the projected productivity increases in ecoregions 3 and 4, there may be capacity to increase harvest. This would be consistent with the results found by Steenberg et al. (2011) that sustainable harvest could increase assuming higher productivity under climate change.
The NSP provides a metric that is sensitive to management changes in the forest, as indicated by the larger difference between the NSP and NBP when harvest rates were higher (Fig. 8b). Based on the wood product model documented behaviour (Dymond, 2012), the NSP will likely also be sensitive to the lifespan of products and their disposal. Therefore, we suggest this metric would be particularly useful when assessing climate change mitigation options available to the forest industry.
This study not only assessed climate change impacts on the productivity of the Copper–Pine Creek valley, but also provided a test case for the ForCSv2 extension to LANDIS-II. Unfortunately, whether the model is based on allometric equations (field plots), flux tower data, or more complex simulation models, it is nearly impossible to directly measure carbon stocks or fluxes, and so we must rely on model intercomparisons. The comparison of carbon stocks and fluxes with literature values in Table 5 provides some confidence that the ForCSv2 output is reasonable, although the variability is large. Therefore, this model is likely most useful for assessing differences between climate, management, or disturbance scenarios, rather than for predicting absolute values.
The LANDIS-II modelling of aboveground biomass, tree species growth,
competition, and natural regeneration has been extensively investigated and
the strengths and weaknesses are understood (e.g. Simons-Legaard et al.,
2015). The landscape NPP and aboveground biomass are highly sensitive to the
input variables: maximum NPP and maximum biomass for each species in each
ecoregion and the growth parameter
The ForCSv2 DOM and soil dynamics are built from the CBM-CFS3 (Kurz et al.,
2009). The CBM-CFS3 has also been investigated for parameter sensitivity
(e.g. White et al., 2008), compared with field estimates of carbon stocks
(Shaw et al., 2014) and with other estimates of NEP (e.g. Wang et al., 2011).
White et al. (2008) found that the DOM and soil carbon stocks and stock
changes were most sensitive to the base decay rates for the aboveground and
belowground slow pools and the transfer to air for the aboveground and
belowground very fast pools. Shaw et al. (2014) found that the CBM-CFS3 model output was reliable for
estimating total ecosystems stocks for the forests of Canada. However, they
did find it overestimated deadwood and underestimated forest floor and
mineral soil carbon stocks, primarily in stands of balsam fir and white and
black spruce due to the model not representing moss. Those stand types are
not found in the Copper–Pine Creek study area. Wang et al. (2011)
demonstrated the large uncertainty between different estimates of NEP among
six models over 8 years for a relatively small area around a flux tower
(
The productivity estimates used as input to ForCSv2 did not include the
positive impact of CO
Forest pests and diseases can have major impacts on forest carbon dynamics (e.g. Kurz et al., 2008) and damage may increase in the future (Woods et al., 2010). They were not included in this simulation modelling study due to a number of factors including the insect damage from the recent mountain pine beetle outbreak being taken into account in the starting inventory and the difficulty in estimating future outbreak events within the relatively short (38 years) simulation period. Future research will incorporate simulations of forest pests and diseases.
The results indicated that the relative position of species optimum to current and future site conditions strongly influenced projections of landscape carbon dynamics. Those productivity rates interacted with respiration and disturbance rates to shape the dynamics of net carbon fluxes of the ecosystem, biome, and sector. Climate change effects on forests vary with species, site conditions, management, and fire regime; therefore, all of these components need to be considered when planning climate change mitigation and adaptive management. This type of future research may consider ForCSv2 as a viable model within the LANDIS-II framework.
Caren C. Dymond led the development of the ForCSv2 extension, modelling at the landscape scale, and manuscript writing. Sarah Beukema provided the software development of ForCSv2 and technical support. Craig R. Nitschke contributed species-site level modelling of productivity and probability of natural regeneration, and contributed to the manuscript. David Coates provided an expert review of local forest stand and landscape dynamics, management prescriptions and manuscript edits. Robert M. Scheller provided key support for the software development of ForCSv2 and manuscript revisions.
We thank Werner Kurz for providing the software code from CBM-CFS3 that enabled the development of ForCSv2. We also thank Bill Golding, Forest Manager for the Wetzin'kwa Community Forest, and Dave Duncan, BC Timber Sales, for their support and review of the management simulations. We also appreciate Michael Magnan for providing technical support in running the BC-HWPv1. This research was funded by the BC Government, Ministry of Forests, Lands and Natural Resource Operations. Edited by: C. A. Williams