Land use change and forest management effects on soil carbon stocks in the Northeast U.S.

BACKGROUND: In most regions and ecosystems, soils are the largest terrestrial carbon pool. Their potential vulnerability to climate and land use change, management, and other drivers, along with soils' ability to mitigate climate change through carbon sequestration, makes them important to carbon balance and management. To date, most studies of soil carbon management have been based at either large or site-specific scales, resulting in either broad generalizations or narrow conclusions, respectively. Advancing the science and practice of soil carbon management requires scientific progress at intermediate scales. Here, we conducted the fifth in a series of ecoregional assessments of the effects of land use change and forest management on soil carbon stocks, this time addressing the Northeast U.S. We used synthesis approaches including (1) meta-analysis of published literature, (2) soil survey and (3) national forest inventory databases to examine overall effects and underlying drivers of deforestation, reforestation, and forest harvesting on soil carbon stocks. The three complementary data sources allowed us to quantify direction, magnitude, and uncertainty in trends. RESULTS: Our meta-analysis findings revealed regionally consistent declines in soil carbon stocks due to deforestation, whether for agriculture or urban development. Conversely, reforestation led to significant increases in soil C stocks, with variation based on specific geographic factors. Forest harvesting showed no significant effect on soil carbon stocks, regardless of place-based or practice-specific factors. Observational soil survey and national forest inventory data generally supported meta-analytic harvest trends, and provided broader context by revealing the factors that act as baseline controls on soil carbon stocks in this ecoregion of carbon-dense soils. These factors include a range of soil physical, parent material, and topographic controls, with land use and climate factors also playing a role. CONCLUSIONS: Forest harvesting has limited potential to alter forest soil C stocks in either direction, in contrast to the significant changes driven by land use shifts. These findings underscore the importance of understanding soil C changes at intermediate scales, and the need for an all-lands approach to managing soil carbon for climate change mitigation in the Northeast U.S.

Regional variation drives differences in microbial communities associated with sugar maple across a latitudinal range.

Climate change is prompting plants to migrate and establish novel interactions in new habitats. Because of the pivotal roles that microbes have on plant health and function, it is important to understand the ecological consequences of these shifts in host-microbe interactions with range expansion. Here we examine how the diversity of plant-associated microbes varies along the host's current range and extended range according with climate change predictions, and assess the relative influence of host genotype (seed provenance) and environment in structuring the host microbiome. We collected sugar maple seeds from across the species current range, then planted them in temperate and mixedwood/transitional forests (current range) and in the boreal region (beyond range but predicted future range in response to climate change). We used amplicon sequencing to quantify bacterial, fungal, and mycorrhizal communities from seedling leaves and roots. Variation among sites and regions were the main drivers of the differences in host microbial communities, whereas seed provenance did not play a large role. No unifying pattern was observed for microbial community richness, diversity, or specialization, demonstrating the complexity of responses of different taxa on above- and belowground plant compartments. Along the latitudinal gradient, we (1) observed reductions in mycorrhizal diversity that can negatively impact maple establishment; (2) and revealed reductions in fungal leaf pathogens that can have opposite effects. Our results highlight the need for an integrated approach including the examination of various microbial taxa on different plant compartments to improve our understanding of plant range shifts and plant-microbe interactions.

Perceptions of climate change across the Canadian forest sector: The key factors of institutional and geographical environment.

Assessing the perception of key stakeholders within the forest sector is critical to evaluating their readiness to engage in adapting to climate change. Here, we report the results of the most comprehensive survey carried out in the Canadian forestry sector to date regarding perceptions of climate change. A total of 1158 individuals, representing a wide range of stakeholders across the five most important forestry provinces in Canada, were asked about climate change, its impact on forest ecosystems, and the suitability of current forest management for addressing future impacts. Overall, we found that respondents were more concerned about climate change than the general population. More than 90% of respondents agreed with the anthropogenic origins of climate change, and > 50% considered it a direct threat to their welfare. Political view was the main driver of general beliefs about the causes of climate change and its future consequences, while the province of origin proved to be the best predictor of perceived current impacts on forest ecosystems and its associated risks; and type of stakeholder was the main driver of perceived need for adaptation. Industrial stakeholders were the most skeptical about the anthropogenic cause(s) of climate change (18% disagreed with this statement, compared to an average of 8% in the other stakeholders), its impacts on forest ecosystems (28% for industry vs. 10% for other respondents), and the need for new management practices (18% vs. 7%). Although the degree of awareness and the willingness to implement adaptive practices were high even for the most skeptical groups, our study identified priority sectors or areas for action when designing awareness campaigns. We suggest that the design of a strategic framework for implementing climate adaptation within the Canadian forest sector should focus on the relationship between climate change and changes in disturbance regimes, and above all on the economic consequences of these changes, but it should also take into account the positions shown by each of the actors in each province.

Cross-scale integration of knowledge for predicting species ranges: a metamodeling framework.

AIM: Current interest in forecasting changes to species ranges have resulted in a multitude of approaches to species distribution models (SDMs). However, most approaches include only a small subset of the available information, and many ignore smaller-scale processes such as growth, fecundity, and dispersal. Furthermore, different approaches often produce divergent predictions with no simple method to reconcile them. Here, we present a flexible framework for integrating models at multiple scales using hierarchical Bayesian methods. LOCATION: Eastern North America (as an example). METHODS: Our framework builds a metamodel that is constrained by the results of multiple sub-models and provides probabilistic estimates of species presence. We applied our approach to a simulated dataset to demonstrate the integration of a correlative SDM with a theoretical model. In a second example, we built an integrated model combining the results of a physiological model with presence-absence data for sugar maple (Acer saccharum), an abundant tree native to eastern North America. RESULTS: For both examples, the integrated models successfully included information from all data sources and substantially improved the characterization of uncertainty. For the second example, the integrated model outperformed the source models with respect to uncertainty when modelling the present range of the species. When projecting into the future, the model provided a consensus view of two models that differed substantially in their predictions. Uncertainty was reduced where the models agreed and was greater where they diverged, providing a more realistic view of the state of knowledge than either source model. MAIN CONCLUSIONS: We conclude by discussing the potential applications of our method and its accessibility to applied ecologists. In ideal cases, our framework can be easily implemented using off-the-shelf software. The framework has wide potential for use in species distribution modelling and can drive better integration of multi-source and multi-scale data into ecological decision-making.