Search

Moose (Alces alces) is a large herbivore that can mediate boreal forest regeneration after timber harvest through selective browsing of tree species. Despite increasing evidence of moose browsing influence on tree growth in early successional forests, climate effects due to changes in carbon sequestration rates and biophysical factors such as albedo remain largely unexplored. We used 11 years of data from 44 pair‐sites of herbivore exclosures within clear‐cut forests in Norway to investigate how moose browsing alters aboveground tree biomass and albedo. We find a higher total aboveground tree biomass (mainly deciduous species) in unbrowsed than browsed forest plots, as moose browsing limited the growth of tree biomass. The effect of moose exclosure on relative tree abundances differed between sites, suggesting that moose browsing has stronger effects on forest structure than composition. At the same time, moose increased forest albedo relative to un‐browsed forests, driving biophysical cooling. When averaged at regional levels, climate effects due to changes in biomass and albedo are of similar magnitude, but contributions can diverge in specific locations. In a region with intensive forestry operations and high moose density, CO2 emissions from moose browsing in post‐harvested sites can be equal to about 40% of the annual emissions of fossil fuels from that region. Cooling effects from increased albedo can offset about two thirds of this impact. Given its influence on tree growth rates and climate impacts, management of moose browsing density should be integrated into forest management plans to optimize climate change mitigation and forest productivity. Plain Language Summary: Moose play a key role in shaping landscape structure and forest composition. For example, moose influence vegetation and soils via foraging, trampling, and nutrient cycling, thereby affecting tree growth rate, community composition, and ecosystem carbon budget. It is estimated that moose alone can browse 10% of the annual harvest volume in Norway. Moose also alter land cover properties such as surface albedo (i.e., the fraction of reflected solar energy radiation), with direct implications for the climate. A better knowledge of the interactions of the climate‐forest‐moose nexus can help the identification of integrated management of forest resources and wild herbivores that maximize climate change mitigation benefits and ecosystem services, including timber value. Our study analyzed 11 years of empirical field measurements from 44 post‐harvest sites in Norway to study climate impacts from both carbon sequestration and albedo dynamics induced by moose browsing. We found that moose browsing cools the climate by increasing surface albedo and warms the climate by limiting forest carbon sequestration. The two effects tend to compensate for each other, but there are large regional variations. Given the potential effects on both tree growth and the climate, moose browsing should be more actively integrated into forest management plans. Key Points: Field data are used to study the effects of moose on forest albedo and carbon dynamicsMoose browsing contributes to warming by limiting carbon sequestration, but exerts a cooling effect by increasing surface albedoThe two effects have the same order of magnitude, but vary regionally, and forest management practices should consider these effects [ABSTRACT FROM AUTHOR]

The importance to consider changes in surface albedo and go beyond simple carbon accounting when assessing climate change impacts of forestry and land use activities is increasingly recognized. However, representation of albedo changes in climate models is complex and highly parameterized, thereby limiting their applications in climate impact studies. The availability of simple yet reliable albedo models can enhance consideration of albedo changes in land use studies. We propose a set of simplified models for estimating surface albedo in a boreal forest. We process and harmonize datasets of remotely‐sensed albedo estimates, forest structure parameters, and meteorological records for different forest locations in Norway. By combining linear unmixing with nonlinear programming, we simultaneously produce albedo estimates at the same resolution of the land cover dataset (16 m, notably higher than satellite retrievals) and a variety of flexible models for albedo predictions. We test different combinations of functional forms, variables, and constraints, including variants specific for snow‐free conditions. We find that models capture the seasonal pattern of surface albedo and the interactive effect of forest structures and meteorological parameters, and many of them show good statistical scores. The cross‐validation exercise shows that the models derived from one area perform reasonably well when applied to other forested areas in Norway, regardless of the temporal and spatial scales. By incorporating changes in forest structure and climate conditions as explicit variables, these models are simple to be used in different applications aiming at estimating albedo changes from forest management and climate change. Plain Language Summary: Surface albedo is the fraction of solar radiation reflected back into the atmosphere by a surface, and it determines how much energy is re‐distributed in the biosphere. It is one of the most important physical properties of land cover and a key mechanism for climate control. By combining satellite retrievals of Norwegian boreal forest with high resolution land cover data and meteorological records, our study produces a range of relatively simple models to estimate surface albedo using the forest structure parameters and climate data. The models require simple variables of forest structure information (age and/or volume) and temperature and/or snow water equivalents. These models are relatively easy and fast to be used for quantifying effects of forest management and climate change on surface albedo. Key Points: Availability of models for simulating surface albedo changes in climate impact assessment studies of forest management is limitedA set of flexible models based on forest and climate variables can predict albedo changes from forest management and climate changeThe models capture the seasonal pattern of surface albedo and the interactive effects of forest structure and meteorological parameters [ABSTRACT FROM AUTHOR]

The excessive simplification of forest structure associated with clear-cutting can carry risks for biodiversity. Tree retention is an alternative practice that maintains greater structural diversity, but its effects on climate change impacts relative to conventional harvesting are largely unexplored. By integrating field measurements from 12 forest stands with modelling approaches, we investigated the post-harvest effects on radiative forcing of tree retention in a Swedish boreal pine forest. In the near-term, impacts from carbon fluxes and surface albedo were of the same order of magnitude but with opposite sign (warming for carbon and cooling for albedo), with a net warming effect. In the long-term, the net effect turns to cooling, as the forest becomes a strong carbon sink. Retention had a significant effect on climate in the near-term, where differences between the various retention levels are more evident. At increasing tree retention, warming impacts from carbon fluxes tend to decrease, but cooling contributions from surface albedo are less pronounced. Balancing these effects, we find a net climate warming that increases with tree retention. [ABSTRACT FROM AUTHOR]

Land surface albedo is a key parameter of the Earth's climate system. It has high variability in space, time and land cover and it is among the most important variables in climate models. Extensive large-scale estimates can help model calibration and improvement to reduce uncertainties in quantifying the influence of surface albedo changes on the planetary radiation balance. Here, we use satellite retrievals of Moderate Resolution Imaging Spectroradiometer (MODIS) surface albedo (MCD43A3), high-resolution land-cover maps and meteorological records to characterize climatological albedo variations in Norway across latitude, seasons, land-cover type (deciduous forests, coniferous forests and cropland), and topography. We also investigate the net changes in surface albedo and surface air temperature through site pair analysis to mimic the effects of land-use transitions between forests and cropland and among different tree species. We find that surface albedo increases at increasing latitude in the snow season, and cropland and deciduous forests generally have higher albedo values than coniferous forests, but for few days in spring. Topography has a large influence on MODIS albedo retrievals, with values that can change up to 100% for the same land-cover class (e.g. spruce in winter) under varying slopes and aspect of the terrain. Cropland sites have surface air temperature higher than adjacent forested sites, and deciduous forests are slightly colder than adjacent coniferous forests. By integrating satellite measurements and highresolution vegetation maps, our results provide a large semi-empirical basis that can assist future studies to better predict changes in a fundamental climate-regulating service such as surface albedo. [ABSTRACT FROM AUTHOR]

By altering fluxes of heat, momentum, and moisture exchanges between the land surface and atmosphere, forestry and other land-use activities affect climate. Although long recognized scientifically as being important, these so-called biogeophysical forcings are rarely included in climate policies for forestry and other land management projects due to the many challenges associated with their quantification. Here, we review the scientific literature in the fields of atmospheric science and terrestrial ecology in light of three main objectives: (i) to elucidate the challenges associated with quantifying biogeophysical climate forcings connected to land use and land management, with a focus on the forestry sector; (ii) to identify and describe scientific approaches and/or metrics facilitating the quantification and interpretation of direct biogeophysical climate forcings; and (iii) to identify and recommend research priorities that can help overcome the challenges of their attribution to specific land-use activities, bridging the knowledge gap between the climate modeling, forest ecology, and resource management communities. We find that ignoring surface biogeophysics may mislead climate mitigation policies, yet existing metrics are unlikely to be sufficient. Successful metrics ought to (i) include both radiative and nonradiative climate forcings; (ii) reconcile disparities between biogeophysical and biogeochemical forcings, and (iii) acknowledge trade-offs between global and local climate benefits. We call for more coordinated research among terrestrial ecologists, resource managers, and coupled climate modelers to harmonize datasets, refine analytical techniques, and corroborate and validate metrics that are more amenable to analyses at the scale of an individual site or region. [ABSTRACT FROM AUTHOR]

Empirical models alongside remotely sensed and station measured meteorological observations are employed to investigate both the local and global direct climate change impacts of alternative forest management strategies within a boreal ecosystem of eastern Norway. Stand-level analysis is firstly executed to attribute differences in daily, seasonal, and annual mean surface temperatures to differences in surface intrinsic biophysical properties across conifer, deciduous, and clear-cut sites. Relative to a conifer site, a slight local cooling of −0.13 °C at a deciduous site and −0.25 °C at a clear-cut site were observed over a 6-year period, which were mostly attributed to a higher albedo throughout the year. When monthly mean albedo trajectories over the entire managed forest landscape were taken into consideration, we found that strategies promoting natural regeneration of coniferous sites with native deciduous species led to substantial global direct climate cooling benefits relative to those maintaining current silviculture regimes - despite predicted long-term regional warming feedbacks and a reduced albedo in spring and autumn months. The magnitude and duration of the cooling benefit depended largely on whether management strategies jointly promoted an enhanced material supply over business-as-usual levels. Expressed in terms of an equivalent CO2 emission pulse at the start of the simulation, the net climate response at the end of the 21st century spanned −8 to −159 Tg- CO2-eq., depending on whether near-term harvest levels increased or followed current trends, respectively. This magnitude equates to approximately −20 to −300% of Norway's annual domestic (production) emission impact. Our analysis supports the assertion that a carbon-only focus in the design and implementation of forest management policy in boreal and other climatically similar regions can be counterproductive - and at best - suboptimal if boreal forests are to be used as a tool to mitigate global warming. [ABSTRACT FROM AUTHOR]

Abstract: Life cycle assessment (LCA) can be an invaluable tool for the structured environmental impact assessment of bioenergy product systems. However, the methodology''s static temporal and spatial scope combined with its restriction to emission-based metrics in life cycle impact assessment (LCIA) inhibits its effectiveness at assessing climate change impacts that stem from dynamic land surface–atmosphere interactions inherent to all biomass-based product systems. In this paper, we focus on two dynamic issues related to anthropogenic land use that can significantly influence the climate impacts of bioenergy systems: i) temporary changes to the terrestrial carbon cycle; and ii) temporary changes in land surface albedo—and illustrate how they can be integrated within the LCA framework. In the context of active land use management for bioenergy, we discuss these dynamics and their relevancy and outline the methodological steps that would be required to derive case-specific biogenic CO2 and albedo change characterization factors for inclusion in LCIA. We demonstrate our concepts and metrics with application to a case study of transportation biofuel sourced from managed boreal forest biomass in northern Europe. We derive GWP indices for three land management cases of varying site productivities to illustrate the importance and need to consider case- or region-specific characterization factors for bioenergy product systems. Uncertainties and limitations of the proposed metrics are discussed. [Copyright &y& Elsevier]

Summary There is a strong need for methods within life cycle assessment (LCA) that enable the inclusion of all complex aspects related to land use and land use change (LULUC). This article presents a case study of the use of one hectare (ha) of forest managed for the production of wood for bioenergy production. Both permanent and temporary changes in above-ground biomass are assessed together with the impact on biodiversity caused by LULUC as a result of forestry activities. The impact is measured as a product of time and area requirements, as well as by changes in carbon pools and impacts on biodiversity as a consequence of different management options. To elaborate the usefulness of the method as well as its dependency on assumptions, a range of scenarios are introduced in the study. The results show that the impact on climate change from LULUC dominates the results, compared to the impact from forestry operations. This clearly demonstrates the need to include LULUC in an LCA of forestry products. For impacts both on climate change and biodiversity, the results show large variability based on what assumptions are made; and impacts can be either positive or negative. Consequently, a mere measure of land used does not provide any meaning in LCA, as it is not possible to know whether this contributes a positive or negative impact. [ABSTRACT FROM AUTHOR]

In Life Cycle Assessment (LCA), carbon dioxide (CO2) emissions from biomass combustion are traditionally assumed climate neutral if the bioenergy system is CO2 flux neutral, i.e. the quantity of CO2 released approximately equals the amount of CO2 sequestered in biomass. This convention is a plausible assumption for fast growing biomass species, but is inappropriate for slower growing biomass, like forests. In this case, the climate impact from biomass combustion can be potentially underestimated if CO2 emissions are ignored, or overestimated, if biogenic CO2 is considered equal to anthropogenic CO2. The estimation of the effective climate impact should take into account how the CO2 fluxes are distributed over time: the emission of CO2 from bioenergy approximately occurs at a single point in time, while the absorption by the new trees is spread over several decades. Our research target is to include this dynamic time dimension in unit-based impact analysis, using a boreal forest stand as case study. The boreal forest growth is modelled with an appropriate function, and is investigated under different forestry regimes (affecting the growth rate and the year of harvest). Specific atmospheric decay functions for biomass-derived CO2 are then elaborated for selected combinations of forest management options. The contribution to global warming is finally quantified using the GWPbio index as climate metric. Results estimates the effects of these practices on the characterization factor used for the global warming potential of CO2 from bioenergy, and point out the key role played by the selected time horizon. [Copyright &y& Elsevier]

• Forestry can influence the regional climate, but analysis with regional climate models are rare. • Less harvesting induces a summer cooling by increasing cloud cover. • Increased harvesting leads to summer warming with increased sensible heat fluxes. • More deciduous forests lead to summer cooling attributed to changes in surface albedo. Several studies investigated the regional temperature effects of afforestation or deforestation, but the impacts of different forest development stages or alternative forest management received limited attention. This is mainly due to challenges in representing area-limited forest dynamics in low-resolution climate models and the need for accurate forest parameters. This study investigates the impact of alternative forest development stages and composition on regional climate in Fennoscandia using a coupled regional climate model. By incorporating realistic and high-resolution forest maps, our modelling framework reduces biases in estimating surface temperature compared to default model runs. If today's forest composition of tree species is left to achieve a mature state (a proxy for the absence of harvesting), an annual mean reduction in 2 m air temperature is estimated, with a cooling peak in summer of -0.53 ± 0.20 °C (mean ± standard deviation) mainly induced by increased cloud cover. Conversely, undeveloped forests (a proxy for increased harvest) induce a contrasting seasonal response: a summer warming of 0.53 ± 0.15 °C (mainly caused by higher sensible heat fluxes), and a weak winter cooling of -0.14 ± 0.24 °C (mainly caused by a higher surface albedo). A transition from evergreen to deciduous forests shows a summer average cooling of -0.57 ± 0.28 °C, mainly attributed to changes in surface albedo. These temperature effects are equivalent to a relatively large fraction of the expected warming by 2050 in Fennoscandia (from 16 % to 70 %, depending on the specific scenario and season). Some modelling outputs appear inconsistent with observations and past modelling studies, such as the cooling effects in winter of more developed forests. Our results provide new insights into the complex relationships between forest dynamics and regional temperature, but modelling improvements are still needed to achieve a robust understanding of the regional climate effects of forest management. [ABSTRACT FROM AUTHOR]

• Using a machine learning-based system to predict the effects of forest management. • The system can accurately reproduce the observed temperature in Fennoscandia. • More developed forests are associated with a higher temperature than young forest. • Historical forest management had a mean annual cooling, but warming in the summer. • The approach is flexible and can be applied to different management scenarios. Forests interact with the local climate through a variety of biophysical mechanisms. Observational and modelling studies have investigated the effects of forested vs. non-forested areas, but the influence of forest management on surface temperature has received far less attention owing to the inherent challenges to adapt climate models to cope with forest dynamics. Further, climate models are complex and highly parameterized, and the time and resource intensity of their use limit applications. The availability of simple yet reliable statistical models based on high resolution maps of forest attributes representative of different development stages can link individual forest management practices to local temperature changes, and ultimately support the design of improved strategies. In this study, we investigate how forest management influences local surface temperature (LSTs) in Fennoscandia through a set of machine learning algorithms. We find that more developed forests are typically associated with higher LST than young or undeveloped forests. The mean multi-model estimates from our statistical system can accurately reproduce the observed LST. Relative to the present state of Fennoscandian forests, fully develop forests are found to induce an annual mean warming of 0.26 °C (0.03/0.69 °C as 5th/95th percentile), and an average cooling effect in the summer daytime from -0.85 to -0.23 °C (depending on the model). On the contrary, a scenario with undeveloped forests induces an annual average cooling of -0.29 °C (-0.61/-0.01 °C), but daytime warming in the summer that can be higher than 1 °C. A weak annual mean cooling of -0.01 °C is attributed to forest harvest from 2015 to 2018, with an increased daytime temperature in summer of about 0.04 °C. Overall, this approach is a flexible option to study effects of forest management on LST that can be applied at various scales and for alternative management scenarios, thereby helping to improve local management strategies with consideration of effects on local climate. [ABSTRACT FROM AUTHOR]