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Forest aboveground carbon density (ACD) for the main eight Hawaiian Islands in 2015-2016. The data are in 30 meter resolution format with the units of Mg C per hectare. The file is a standard GeoTIFF. Use of these data requires citation of this dataset plus citation of the source study as follows: Asner, G.P., S. Sousan, D.E. Knapp, P.C. Selmants, R.E. Martin, R.F. Hughes, and C.P. Giardina. 2016. Rapid forest carbon assessments of oceanic islands: a case study of the Hawaiian archipelago. Carbon Balance and Management 11, doi:10.1186/s13021-015-0043-4

Correlations between chlorophyll a and total phosphorus in freshwater ecosystems were first documented in the 1960s and have been used since then to infer phosphorus limitation, build simple models, and develop management targets. Often these correlations are considered indicative of a cause-effect relationship. However, many scientists regard the use of these associations for modeling and inference to be misleading due to their potentially spurious nature. Using data from Saginaw Bay, Lake Huron, we examine the relationship among chlorophyll a, total phosphorus, and algal biomass measurements. We apply graphical models and recently developed "structure learning" principles that use conditional dependencies to help identify causal relationships among observational data. The spurious relationship suspected by some is not supported by our data, whereas a direct relationship between chlorophyll a and total phosphorus is always supported, and an additional indirect relationship with an algal biomass intermediary is plausible under some circumstances. Thus, we conclude that these correlations are useful for simple model building but encourage the use of modern statistical methods to avoid common model-assumption violations.

Forest soil acidification caused by acid deposition is a serious threat to the forest ecosystem. To investigate the liming effects of biomass ash (BA) and alkaline slag (AS) on the acidic topsoil and subsoil, a three-year field experiment under artificial Masson pine was conducted at Langxi, Anhui province in Southern China. The surface application of BA and AS significantly increased the soil pH, and thus decreased exchangeable acidity and active Al in the topsoil. Soil exchangeable Ca2+ and Mg2+ in topsoil were significantly increased by the surface application of BA and AS, while an increase in soil exchangeable K+ was only observed in BA treatments. The soil acidity and active Al in subsoil were decreased by the surface application of AS. Compared with the control, soluble monomeric and exchangeable Al in the subsoil was decreased by 38.0% and 29.4% after 3 years of AS surface application. There was a minimal effect on soluble monomeric and exchangeable Al after the application of BA. The soil exchangeable Ca2+ and Mg2+ in the subsoil increased respectively by 54% and 141% after surface application of 10 t ha-1 AS. The decrease of soil active Al and increase of base cations in subsoil were mainly attributed to the high migration capacity of base cations in AS. In conclusion, the effect of surface application of AS was superior to BA in ameliorating soil acidity and alleviating soil Al toxicity in the subsoil of this Ultisol.

Net primary production (NPP), the difference between CO2 fixed by photosynthesis and CO2 lost to autotrophic respiration, is one of the most important components of the carbon cycle. Our goal was to develop a simple regression model to estimate global NPP using climate and land cover data. Approximately 5600 global data points with observed mean annual NPP, land cover class, precipitation, and temperature were compiled. Precipitation was better correlated with NPP than temperature, and it explained much more of the variability in mean annual NPP for grass- or shrub-dominated systems (r2 = 0.68) than for tree-dominated systems (r2 = 0.39). For a given precipitation level, tree-dominated systems had significantly higher NPP (approximately 100-150 g C m(-2) yr(-1)) than non-tree-dominated systems. Consequently, previous empirical models developed to predict NPP based on precipitation and temperature (e.g., the Miami model) tended to overestimate NPP for non-tree-dominated systems. Our new model developed at the National Center for Ecological Analysis and Synthesis (the NCEAS model) predicts NPP for tree-dominated systems based on precipitation and temperature; but for non-tree-dominated systems NPP is solely a function of precipitation because including a temperature function increased model error for these systems. Lower NPP in non-tree-dominated systems is likely related to decreased water and nutrient use efficiency and higher nutrient loss rates from more frequent fire disturbances. Late 20th century aboveground and total NPP for global potential native vegetation using the NCEAS model are estimated to be approximately 28 Pg and approximately 46 Pg C/yr, respectively. The NCEAS model estimated an approximately 13% increase in global total NPP for potential vegetation from 1901 to 2000 based on changing precipitation and temperature patterns.

Please cite as: Wuebbles, D., J. Angel, K. Petersen, and A.M. Lemke, (Eds.), 2021: An Assessment of the Impacts of Climate Change in Illinois. The Nature Conservancy, Illinois, USA. https://doi.org/10.13012/B2IDB-1260194_V1 Climate change is a major environmental challenge that is likely to affect many aspects of life in Illinois, ranging from human and environmental health to the economy. Illinois is already experiencing impacts from the changing climate and, as climate change progresses and temperatures continue to rise, these impacts are expected to increase over time. This assessment takes an in-depth look at how the climate is changing now in Illinois, and how it is projected to change in the future, to provide greater clarity on how climate change could affect urban and rural communities in the state. Beyond providing an overview of anticipated climate changes, the report explores predicted effects on hydrology, agriculture, human health, and native ecosystems.

Structural and physiological changes that occur as trees grow taller are associated with increased hydraulic constraints on leaf gas exchange, yet it is unclear if leaf-level constraints influence whole-tree growth as trees approach their maximum size. We examined variation in leaf physiology, leaf area to sapwood area ratio (L/S), and annual aboveground growth across a range of tree heights in Eucalyptus regnans. Leaf photosynthetic capacity did not differ among upper crown leaves of individuals 61.1-92.4 m tall. Maximum daily and integrated diurnal stomatal conductance (g s) averaged 36 and 34% higher, respectively, in upper crown leaves of ~60-m-tall, 80-year-old trees than in ~90-m-tall, 300-year-old trees, with larger differences observed on days with a high vapor pressure deficit (VPD). Greater stomatal regulation in taller trees resulted in similar minimum daily leaf water potentials (Ψ L) in shorter and taller trees over a broad range of VPDs. The long-term stomatal limitation on photosynthesis, as inferred from leaf δ (13)C composition, was also greater in taller trees. The δ (13)C of wood indicated that the bulk of photosynthesis used to fuel wood production in the main trunk and branches occurred in the upper crown. L/S increased with tree height, especially after accounting for size-independent variation in crown structure across 27 trees up to 99.8 m tall. Despite greater stomatal limitation of leaf photosynthesis in taller trees, total L explained 95% of the variation in annual aboveground biomass growth among 15 trees measured for annual biomass growth increment in 2006. Our results support a theoretical model proposing that, in the face of increasing hydraulic constraints with height, whole-tree growth is maximized by a resource trade-off that increases L to maximize light capture rather than by reducing L/S to sustain g s.

This chapter focuses on the evaluation of adaptive capacities of community-level human systems related to agriculture and food security. It highlights findings regarding approaches and domains to monitor and evaluate behavioral changes from CGIAR’s research program on climate change, agriculture and food security (CCAFS). This program, implemented in five West African countries, is intended to enhance adaptive capacities in agriculture management of natural resources and food systems. In support of participatory action research on climate-smart agriculture, a monitoring and evaluation plan was designed with the participation of all stakeholders to track changes in behavior of the participating community members. Individuals’ and groups’ stories of changes were collected using most significant change tools. The collected stories of changes were substantiated through field visits and triangulation techniques. Frequencies of the occurrence of characteristics of behavioral changes in the stories were estimated. The results show that smallholder farmers in the intervention areas adopted various characteristics of behavior change grouped into five domains: knowledge, practices, access to assets, partnership and organization. These characteristics can help efforts to construct quantitative indicators of climate change adaptation at local level. Further, the results suggest that application of behavioral change theories can facilitate the development of climate change adaptation indicators that are complementary to indicators of development outcomes. We conclude that collecting stories on behavioral changes can contribute to biophysical adaptation monitoring and evaluation.

This dataset includes 30-m gridded estimates of total plant aboveground biomass (AGB), the shrub AGB, and the shrub dominance (shrub/plant AGB) for non-water portions of the Beaufort Coastal Plain and Brooks Foothills ecoregions of the North Slope of Alaska. The estimates were derived by linking biomass harvests from 28 published field site datasets with Normalized Difference Vegetation Index (NDVI) from a regional Landsat mosaic derived from Landsat 5 and 7 satellite imagery. The data cover the period 2007-06-01 to 2016-08-31. The data provided are the best estimates from the described modeling and Monte Carlo approach for each 30-m pixel in the Landsat mosaic at the 50th percentile, and also at the 2.5 and 97.5 percentiles for each data type (plant AGB, shrub AGB, and shrub dominance) which together encompass 95% of predictions. The published field measurements of total plant and shrub AGB used in the modeling were collected between July 1998 and August 2008. The mean and standard error (SE) of plant and shrub AGB were also acquired or computed for the data at each site. The regional Landsat NDVI mosaic was derived from 1,721 summer scenes acquired between 2007 and 2016. Spectral reflectance information was extracted from these 'peak greenness' scenes on a per pixel basis. Empirical AGB-NDVI relationships were developed for the field sites and the relationships were applied to the mosaic. The Monte Carlo uncertainty analysis involved generating 1,000 regional maps of each ecosystem data type, where each map was produced by randomly permuting the underlying field and remote sensing datasets by their uncertainty due to sampling and sensor calibration errors. The data with this dataset are the 50th percentile (best estimates), the 2.5, and 97.5 percentiles of the 1,000 permutations. There are nine data files of mapped AGB and shrub dominance with this dataset in GeoTIFF (.tif) format and one shapefile (.shp) provided in compressed (.zip) format which provides the study locations. The study locations are also provided as a companion file in .kmz format for viewing in Google Earth. A companion file of the published field measurements of total plant and shrub AGB used in the modeling is also available as a .csv file.

AbstractAcross southern China, Moso bamboo has been encroaching on most neighboring secondary broad-leaved forests and/or coniferous plantations, leading to the land cover changes that alter abiotic and biotic conditions. Little is known about how this conversion alters soil carbon (C) and nitrogen (N). We selected three sites, each with three plots arrayed along the bamboo encroachment pathway: moso bamboo forest (BF); transition zone, mixed forest plots (MF); and broad-leaved forest (BLF), and examined how bamboo encroachment affects soil organic C (SOC), soil total N, microbial biomass C (MBC), microbial biomass N (MBN), water-soluble organic C (WSOC), and water-soluble organic N (WSON) in three forests. Over nine years, moso bamboo encroachment leads to a decrease in SOC and total soil N, an increase in MBC and WSOC, and a decrease in MBN and WSON. Changes in soil C and N occurred mainly in the topsoil. We conclude that moso bamboo encroachment on broadleaved forest not only substantially altered soil C and N pools, but also changed the distribution pattern of C and N in the studied forest soils. Continued bamboo encroachment into evergreen broadleaved forests seems likely to lead to net CO2 emissions to the atmosphere as ecosystem C stocks decline.