Search

Thin plate smoothing spline models, covering Canada and the continental United States, were developed using ANUSPLIN for 30-year (1991-2020) monthly mean maximum and minimum temperature and precipitation. These models employed monthly weather station values from the North American dataset published by National Oceanic and Atmospheric Administration's (NOAA's) National Centers for Environmental Information (NCEI). Maximum temperature mean absolute errors (MAEs) ranged between 0.54 °C and 0.64 °C (approaching measurement error), while minimum temperature MAEs were slightly higher, varying from 0.87 °C to 1.0 °C. On average, thirty-year precipitation estimates were accurate to within approximately 10 % of total precipitation levels, ranging from 9.0 % in the summer to 12.2 % in the winter. Error rates were higher in Canada compared to estimates in the United States, consistent with a less dense station network in Canada relative to the United States. Precipitation estimates in Canada exhibited MAEs representing 14.7 % of mean total precipitation compared to 9.7 % in the United States. The datasets exhibited minimal bias overall; 0.004 °C for maximum temperature, 0.01 °C for minimum temperature, and 0.5 % for precipitation. Winter months showed a greater dry bias (0.8 % of total winter precipitation) compared to other seasons (-0.4 % of precipitation). These 30-year gridded datasets are available at ∼2 km resolution., (Crown Copyright © 2024 Published by Elsevier Inc.)

In anticipation of growing wildfire management challenges, the Canadian government is investing in WildFireSat, an Earth observation satellite mission designed to collect data in support of Canadian wildfire management. Although costs of the mission can be reasonably estimated, the benefits of such an investment are unknown. Here we forecast the possible benefits of WildFireSat via an avoided cost approach. We consider five socio-economic components: suppression costs (fixed and variable), timber losses, property, asset and infrastructure losses, evacuation costs, and smoke related health costs. Using a Monte Carlo analysis, we evaluated a range of possible changes to these components based on expert opinions. The resulting Net Present Value (NPV) estimates depend on the presumed impact of using WildFireSat decision support data products, with pessimistic and conservative assumptions generating mission costs that typically exceed potential benefits by 1.16 to 1.59 times, while more optimistic assumptions generate benefits in excess of costs by 8.72 to 10.48 times. The analysis here excludes some possibly significant market and non-market impacts expected from WildFireSat due to data limitations; accounting for these additional impacts would likely generate positive NPVs under even cautious impact assumptions., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Hope et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Heating degree days (HDD) represent a concise measure of heating energy requirements used to inform decision making about the impact of climate change on heating energy demand. This data paper presents spatial datasets of heating degree days (HDD) for Canada for two thirty-year periods, 1951-1980 and 1981-2010, using daily temperature gauge observations over these time periods. Stations with fewer than nine missing days in a year and greater than nine years of data over each thirty-year period were included, resulting in 1339 and 1679 stations for the 1951-1980 and 1981-2010 periods respectively. Mean absolute error (MAE) of the spatial models ranged from 124.2 Celsius degree days (C-days) for the 1951-1980 model (2.4% of the surface mean) to 137.6 C-days for the 1981-2010 model (2.7%). This note presents maps illustrating cross validation errors at a set of representative stations. The grids are available at ∼2 km resolutions., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Crown Copyright © 2023 Published by Elsevier Inc.)

Replacement of fossil fuels with bioenergy, often in concert with carbon capture and storage, plays an important role in published low-emission pathways from the Intergovernmental Panel on Climate Change (IPCC) and other agencies. National and regional net-zero greenhouse gas emission commitments have caused a dramatic increase in forest biomass consumption globally, and the rise has been accompanied by debates in the scholarly literature and in society at large about the ecological and climate change impacts of forest biomass. This paper presents a quantitative analysis of media headlines about forest bioenergy published in 75 Canadian newspapers from 2010 to 2020. Using a lexicon and rules-based sentiment analysis tool, we explore negative and positive media headlines about forest biomass. Despite our finding that Canadian headlines about forest bioenergy were twice as likely to be positive as negative, media items document reversals away from forest biomass-generated domestic electricity. Our analysis found that increases in electricity costs following the introduction of forest biomass as a fuel type for Canadian electricity generation was a primary cause of these reversals. Headlines also critiqued the expanded production of wood pellets, citing forest ecological impacts and the debate about the net carbon impacts of forest biomass-generated energy. Safety issues, including stories about workplace injuries, and pellet plant fires, and economic issues, such as fiber supply and mill closures, were also featured. This research contributes a social science lens to understand perceptions over time about forest biomass for heat and power., Competing Interests: The authors declare the following conflict of interests: Member of Bioeconomy Technical Working Group, which is composed of members of the Canadian Forest Service and the Ontario Forestry Institute., (Crown Copyright © 2023 Published by Elsevier Ltd.)

Tree provenance trials consist of a variety of seed sources (or provenances) planted at several test sites across the range of a species. The resulting plantations are typically measured periodically to investigate provenance performance in relation to abiotic conditions, particularly climate. These trials are expensive and time consuming to establish, but are an important resource for seed transfer systems, which aim to match planting sites with well-adapted (climatically suitable) seed sources. Provenance trial measurements may be underutilized because the data are scattered across publications, conference proceedings, and university theses. Here we document an effort to collect available provenance trial measurements and associated climate data for seven eastern North American tree species (Pinus strobus, Pinus banksiana, Picea glauca, Picea mariana, Quercus rubra, Larix laricina, Betula alleghaniensis). The resulting datasets included a total of 773 provenances and 62 test sites, with 65 historical climate variables appended to each location. We hope this data will support forest managers in making seed transfer decisions, particularly in an era of rapid climate change.

We present historical monthly spatial models of temperature and precipitation generated from the North American dataset version "j" from the National Oceanic and Atmospheric Administration's (NOAA's) National Centres for Environmental Information (NCEI). Monthly values of minimum/maximum temperature and precipitation for 1901-2016 were modelled for continental United States and Canada. Compared to similar spatial models published in 2006 by Natural Resources Canada (NRCAN), the current models show less error. The Root Generalized Cross Validation (RTGCV), a measure of the predictive error of the surfaces akin to a spatially averaged standard predictive error estimate, averaged 0.94 °C for maximum temperature models, 1.3 °C for minimum temperature and 25.2% for total precipitation. Mean prediction errors for the temperature variables were less than 0.01 °C, using all stations. In comparison, precipitation models showed a dry bias (compared to recorded values) of 0.5 mm or 0.7% of the surface mean. Mean absolute predictive errors for all stations were 0.7 °C for maximum temperature, 1.02 °C for minimum temperature, and 13.3 mm (19.3% of the surface mean) for monthly precipitation.

We assess risks posed by oak wilt-a disease caused by the fungal pathogen Bretziella fagacearum. Though not currently found in Canada, our distribution models indicate that suitable climate conditions currently occur in southern Ontario for B. fagacearum and two of its main insect dispersal vectors, Colopterus truncatus and Carpophilus sayi. Climate habitat for these species is projected to expand northward under climate change, with much of the oak range in eastern Canada becoming climatically suitable within the next two decades. Potential costs for the removal and replacement of oak street trees ranged from CDN$266 to $420 million, with variation related to uncertainty in costs, rate of tree replacement, and city-level estimates of oak street tree density. The value of standing oak timber in eastern Canada was estimated at CDN$126 million using provincial stumpage fees and as a CDN$24 million annual contribution to national Gross Domestic Product (GDP) when calculated using a combination of economic and forestry product statistics. These values can help inform the scale of eradication and/or management efforts in the event of future oak wilt introductions.

This paper presents estimates of the effects of changing climate on crop yields for grain corn and soybeans in Ontario, Canada, for 1959-2013. We were able to use a database that is more comprehensive with respect to explanatory variables than some previous efforts had available. Our model includes climate variables, prices, land quality, groundwater level, CO 2 concentration, and a time trend. Our results indicate that trends in temperature and precipitation during our study period have not yet resulted in appreciable threats to crop yields in the region.

The Asian longhorned beetle (Anoplophora glabripennis Motschulsky) continues to pose a significant risk to deciduous forests around the world. We assess Asian longhorned beetle-related risks in eastern Canada by generating current and future climate suitability maps, import-based likelihood of introduction estimates for each urban center in our study area, and potential economic impacts in both urban and natural settings. For the current period, climatic suitability for Asian longhorned beetle was highest in southern Ontario, but was projected to expand significantly northward and eastward by midcentury. High likelihood of Asian longhorned beetle introduction was associated with large urban centers, but also smaller centers with high levels of pest-associated imports. Potential costs for the removal and replacement of Asian longhorned beetle-impacted street trees ranged from CDN$8.6 to $12.2 billion, with the exact amount and city-level ranking depending on the method used to calculate risk. Potential losses of merchantable maple (Acer) timber were estimated at CDN$1.6 billion using provincial stumpage fees and CDN$431 million annually when calculated using a combination of economic and forestry product statistics. The gross value of edible maple products, which could potentially be affected by Asian longhorned beetle, was estimated at CDN$358 million annually. These values can help inform the scale of early detection surveys, potential eradication efforts, and research budgets in the event of future Asian longhorned beetle introductions., (© The Author(s) 2019. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Competing Interests: Conflicts of interest All authors have no conflicts of interest to declare.

The growth response of trees to ongoing climate change has important implications for future forest dynamics, accurate carbon accounting, and sustainable forest management. We used data from black spruce (Picea mariana) and jack pine (Pinus banksiana) provenance trials, along with published data for three other northern conifers, to identify a consistent growth response to climate warming in which cold-origin populations are expected to benefit and warm-origin populations are expected to decline. Specifically, populations from across the geographic range of a species appear to grow well at temperatures characteristic of the southern portion of the range, indicating significant potential for a positive growth response to climate warming in cold-origin populations. Few studies have quantified and compared this pattern across multiple species using provenance data. We present a forest regeneration strategy that incorporates these anticipated growth responses to promote populations that are both local to the planting site and expected to grow well under climate change.

Climate-influenced changes in fire regimes in northern temperate and boreal regions will have both ecological and economic ramifications. We examine possible future wildfire area burned and suppression costs using a recently compiled historical (i.e., 1980-2009) fire management cost database for Canada and several Intergovernmental Panel on Climate Change (IPCC) climate projections. Area burned was modelled as a function of a climate moisture index (CMI), and fire suppression costs then estimated as a function of area burned. Future estimates of area burned were generated from projections of the CMI under two emissions pathways for four General Circulation Models (GCMs); these estimates were constrained to ecologically reasonable values by incorporating a minimum fire return interval of 20 years. Total average annual national fire management costs are projected to increase to just under $1 billion (a 60% real increase from the 1980-2009 period) under the low greenhouse gas emissions pathway and $1.4 billion (119% real increase from the base period) under the high emissions pathway by the end of the century. For many provinces, annual costs that are currently considered extreme (i.e., occur once every ten years) are projected to become commonplace (i.e., occur once every two years or more often) as the century progresses. It is highly likely that evaluations of current wildland fire management paradigms will be necessary to avoid drastic and untenable cost increases as the century progresses.

Seed mass is an adaptive trait affecting species distribution, population dynamics and community structure. In widely distributed species, variation in seed mass may reflect both genetic adaptation to local environments and adaptive phenotypic plasticity. Acknowledging the difficulty in separating these two aspects, we examined the causal relationships determining seed mass variation to better understand adaptability and/or plasticity of selected tree species to spatial/climatic variation. A total of 504, 481 and 454 seed collections of black spruce (Picea mariana (Mill.) B.S.P.), white spruce (Picea glauca (Moench) Voss) and jack pine (Pinus banksiana Lamb) across the Canadian Boreal Forest, respectively, were selected. Correlation analyses were used to determine how seed mass vary with latitude, longitude, and altitude. Structural Equation Modeling was used to examine how geographic and climatic variables influence seed mass. Climatic factors explained a large portion of the variation in seed mass (34, 14 and 29%, for black spruce, white spruce and jack pine, respectively), indicating species-specific adaptation to long term climate conditions. Higher annual mean temperature and winter precipitation caused greater seed mass in black spruce, but annual precipitation was the controlling factor for white spruce. The combination of factors such as growing season temperature and evapotranspiration, temperature seasonality and annual precipitation together determined seed mass of jack pine. Overall, sites with higher winter temperatures were correlated with larger seeds. Thus, long-term climatic conditions, at least in part, determined spatial variation in seed mass. Black spruce and Jack pine, species with relatively more specific habitat requirements and less plasticity, had more variation in seed mass explained by climate than did the more plastic species white spruce. As traits such as seed mass are related to seedling growth and survival, they potentially influence forest species composition in a changing climate and should be included in future modeling of vegetation shifts.

Canada's National Forest Inventory (CanFI) provides coarse-grained, aggregated information on a large number of forest attributes. Though reasonably well suited for summary reporting on national forest resources, the coarse spatial nature of this data limits its usefulness in modeling applications that require information on forest composition at finer spatial resolutions. An alternative source of information is the land cover classification produced by the Canadian Forest Service as part of its Earth Observation for Sustainable Development of Forests (EOSD) initiative. This product, which is derived from Landsat satellite imagery, provides relatively high resolution coverage, but only very general information on forest composition (such as conifer, mixedwood, and deciduous). Here we link the CanFI and EOSD products using a spatial randomization technique to distribute the forest composition information in CanFI to the forest cover classes in EOSD. The resultant geospatial coverages provide randomized predictions of forest composition, which incorporate the fine-scale spatial detail of the EOSD product and agree in general terms with the species composition summaries from the original CanFI estimates. We describe the approach and provide illustrative results for selected major commercial tree species in Canada.

We present the idea of using potential infringements on annual allowable harvest targets as an approach to estimate threats from invasive species to the forest products sector. The approach uses present-day harvest levels as a reference level to estimate when and where the impact of a nonnative forest pest could become economically damaging. We use a generic model that simulates spread and damage by nonnative invasive species, basic harvest and forest growth through time. The concept is illustrated with a case study of a new nonnative invasive pest, Sirex noctilio Fabricius on pine resources in eastern Canada. Impacts of invasion on wood supply, in particular, the point at which present-day harvest levels are not attainable, were identified for 77 non-overlapping geographical regions that delimit the primary wood supply areas around large mills and wood processing facilities in eastern Canada. The results identify the minimum area of a pest outbreak that could trigger harvest shortages (approximately 12.5-14 M ha of pine forests in Ontario and Quebec). Beyond this level, the amount of host resource available for harvesting in any given year declines rapidly. The failure to sustain broad-scale harvest targets may be an attractive and intuitive indicator for policy makers and regulators interested in developing control and "slow-the-spread" programs for non-native forest pests., (Crown Copyright © 2010. Published by Elsevier Ltd. All rights reserved.)

Pest risk maps can provide useful decision support in invasive species management, but most do not adequately consider the uncertainty associated with predicted risk values. This study explores how increased uncertainty in a risk model's numeric assumptions might affect the resultant risk map. We used a spatial stochastic model, integrating components for entry, establishment, and spread, to estimate the risks of invasion and their variation across a two-dimensional landscape for Sirex noctilio, a nonnative woodwasp recently detected in the United States and Canada. Here, we present a sensitivity analysis of the mapped risk estimates to variation in key model parameters. The tested parameter values were sampled from symmetric uniform distributions defined by a series of nested bounds (+/-5%, ... , +/-40%) around the parameters' initial values. The results suggest that the maximum annual spread distance, which governs long-distance dispersal, was by far the most sensitive parameter. At +/-15% or larger variability bound increments for this parameter, there were noteworthy shifts in map risk values, but no other parameter had a major effect, even at wider bounds of variation. The methodology presented here is generic and can be used to assess the impact of uncertainties on the stability of pest risk maps as well as to identify geographic areas for which management decisions can be made confidently, regardless of uncertainty.

Nonindigenous species have caused significant impacts to North American forests despite past and present international phytosanitary efforts. Though broadly acknowledged, the risks of pest invasions are difficult to quantify as they involve interactions between many factors that operate across a range of spatial and temporal scales: the transmission of invading organisms via various pathways, their spread and establishment in new environments. Our study presents a stochastic simulation approach to quantify these risks and associated uncertainties through time in a unified fashion. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. We simulate new potential entries of S. noctilio as a stochastic process, based on recent volumes of marine shipments of commodities from countries where S. noctilio is established, as well as the broad dynamics of foreign marine imports. The results are then linked with a spatial model that simulates the spread of S. noctilio within the geographical distribution of its hosts (pines) while incorporating existing knowledge about its behavior in North American landscapes. Through replications, this approach yields a spatial representation of S. noctilio risks and uncertainties in a single integrated product. The approach should also be appealing to decisionmakers, since it accounts for projected flows of commodities that may serve as conduits for pest entry. Our 30-year forecasts indicate high establishment probability in Ontario, Quebec, and the northeastern United States, but further southward expansion of S. noctilio is uncertain, ultimately depending on the impact of recent international treatment standards for wood packing materials.

This study explores the economic attractiveness of afforestation as a strategy for the joint production of fibre, carbon storage and biosolids (treated municipal sewage sludge) disposal for municipalities in Southern and Central Ontario, Canada. We use a spatial, stochastic model, the Canadian Forest Service Afforestation Feasibility Model (CFS-AFM), to simulate a range of spatial biosolids application scenarios in hybrid poplar afforestation projects. Results suggest that such joint afforestation strategies could be financially attractive. Significant cost savings can be expected through decreases in transportation distances and avoided waste disposal fees. Sensitivity analysis is used to examine the effects of variations in critical model parameters on net present values. Our findings indicate that waste disposal savings from application of biosolids on hybrid poplar plantations combined with incentives for landowners to sequester carbon can easily compete with agricultural land rental values in some regions of Ontario. Social acceptance of this kind of activity, however, may be an impediment to adoption.

Obesity is associated with the development of hypertension but it is still not clear why hypertension is not observed in all obese patients. Obesity is a risk factor for the development of obstructive sleep apnea syndrome (OSAS) in children. OSAS has been linked to the development of hypertension in adults and children. The purpose of this study was to test the hypothesis that OSAS is one of the reasons that some obese children are hypertensive and some are not. The overnight polysomnography records of 90 patients (aged 4.2-18.8 years) were reviewed. BMI(score) [body mass index (BMI)/95th percentile BMI for age, sex, and race] was used to express the degree of obesity. The severity of systolic hypertension and diastolic hypertension were expressed as SBP(score) (systolic BP/the 95th percentile systolic BP for age, sex, and height) and DBP(score) (diastolic BP/the 95th percentile diastolic BP for age, sex, and height), respectively. OSAS was defined as more than one episodes of apnea per hour (AI) or an O(2) saturation associated with obstructive apnea of less than 90%. There were 56 obese patients; 42 were hypertensive and 40 patients were diagnosed with OSAS. The incidence of hypertension (68% vs. 30%) and obesity (75% vs. 52%) was higher in OSAS patients than those without OSAS. Compared with the non-obese patients, obese patients had a higher incidence of hypertension or OSAS, a higher BMI(score), SBP(score), DBP(score), AI, hypopnea index (HI), and apnea-hypopnea index (AHI). In obese patients, both SBP(score) and DBP(score) correlated positively with BMI(score), arousal index, and HI. DBP(score) also correlated positively with AHI. Multiple regression analysis showed that HI and BMI(score) were significant independent predictors of SBP(score) or DBP(score). Obese and hypertensive patients had a higher HI, AHI, and incidence of OSAS (64% vs. 29%) than the obese and normotensive patients. In conclusion, HI had a significant correlation with the degree of hypertension in obese patients, which could not be attributed to the degree of obesity. These findings are consistent with the hypothesis that OSAS is one of the reasons why some obese children are hypertensive and some are not.

This paper briefly reviews the process of exotic pest risk assessments and presents some examples of emerging opportunities for spatial bioclimatic modeling of exotic species in Canada. This type of analysis can support risk assessments but does not replace the need for on-going high quality field-based observations to validate and update models. Bioclimatic analysis of several exotic pests is provided to illustrate both opportunities and limits. A link is demonstrated to the National Forest Inventory to characterize timber volumes at risk for one exotic species. 'Challenges' are both scientific and administrative. More accessible and current field survey data are required to improve models. Our experience is that for many exotic species, historical, and even current, data are not always digital or quality controlled for taxonomic identity and accurate geo-referencing. This inhibits their use for integrated spatial modeling applications.

Rapid changes in serum sodium concentration can result in adverse neurological outcome. The gradual correction of hypernatremia in the setting of acute renal failure can be difficult to achieve. We describe an obese female teenager who presented with severe hypernatremia, hyperosmolar hyperglycemic nonketotic coma, acute renal failure, and rhabdomyolysis. Her hypernatremia and other serum chemistries were gradually corrected by repeatedly adjusting the dialysate electrolyte composition used during continuous venovenous hemodiafiltration. She had a full recovery of her renal function. She does not have clinical neurological sequelae from hypernatremia during a 1-year follow-up period.