D. Locke, Sonya S. Sachdeva, Lynne M. Westphal, L. Kenefic, M. Dockry, C. L. Fisher
Diverse workforce representation helps organizations achieve their goals and is important for government agencies that seek to gain public trust. Prior research has examined patterns of representation in the USDA Forest Service and found an overall lack of representation despite advances at leadership levels. Federal agencies are required to report total workforce demographics; however, representation relative to local communities is rarely known. Using data from the US Census Bureau, we examined demographic profiles of populations within a 1-hour drive time around Forest Service workplaces relative to workforce demographics at each workplace. The Forest Service had a greater proportion of white employees than the US population as a whole, and racial/ethnicity diversity was lower than surrounding communities at 99.7% of Forest Service workplaces. Region-level summaries reinforce this pattern, suggesting the Forest Service is not a representative bureaucracy in any region or at any geographic scale. Given the Forest Service’s size, role in natural resources management, and geographic distribution of its workforce, disparities between demographic composition of the agency’s workforce and surrounding communities are striking. These results set a standard for spatially explicit assessments of workforce diversity as it relates to representative bureaucracy in geographically dispersed organizations like the Forest Service. Study Implications: Prior research showed that the USDA Forest Service had proportionally fewer Black/African American (~3 times fewer) and Asian (~2 times fewer) employees than the US civilian labor force as a whole. However, aggregate agency-level statistics and national comparisons may conceal local and regional level variation. To understand how the racial and ethnic diversity at each workplace compared with its surrounding geographic area’s local population, 690 workplaces were examined. Results were consistent across multiple drive times and levels of aggregation; the Forest Service’s workforce is less diverse than surrounding communities, which may potentially affect its ability to serve its many stakeholders.
{"title":"Spatially Explicit Assessment of the USDA Forest Service as a Representative Bureaucracy","authors":"D. Locke, Sonya S. Sachdeva, Lynne M. Westphal, L. Kenefic, M. Dockry, C. L. Fisher","doi":"10.1093/forsci/fxad018","DOIUrl":"https://doi.org/10.1093/forsci/fxad018","url":null,"abstract":"\u0000 Diverse workforce representation helps organizations achieve their goals and is important for government agencies that seek to gain public trust. Prior research has examined patterns of representation in the USDA Forest Service and found an overall lack of representation despite advances at leadership levels. Federal agencies are required to report total workforce demographics; however, representation relative to local communities is rarely known. Using data from the US Census Bureau, we examined demographic profiles of populations within a 1-hour drive time around Forest Service workplaces relative to workforce demographics at each workplace. The Forest Service had a greater proportion of white employees than the US population as a whole, and racial/ethnicity diversity was lower than surrounding communities at 99.7% of Forest Service workplaces. Region-level summaries reinforce this pattern, suggesting the Forest Service is not a representative bureaucracy in any region or at any geographic scale. Given the Forest Service’s size, role in natural resources management, and geographic distribution of its workforce, disparities between demographic composition of the agency’s workforce and surrounding communities are striking. These results set a standard for spatially explicit assessments of workforce diversity as it relates to representative bureaucracy in geographically dispersed organizations like the Forest Service.\u0000 Study Implications: Prior research showed that the USDA Forest Service had proportionally fewer Black/African American (~3 times fewer) and Asian (~2 times fewer) employees than the US civilian labor force as a whole. However, aggregate agency-level statistics and national comparisons may conceal local and regional level variation. To understand how the racial and ethnic diversity at each workplace compared with its surrounding geographic area’s local population, 690 workplaces were examined. Results were consistent across multiple drive times and levels of aggregation; the Forest Service’s workforce is less diverse than surrounding communities, which may potentially affect its ability to serve its many stakeholders.","PeriodicalId":12749,"journal":{"name":"Forest Science","volume":"24 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74670687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Maneesh Kumar Patasaraiya, Rinku Moni Devi, Bhaskar Sinha, Jigyasa Bisaria
Climate change impacts on tropical forests and tree species have been documented as changes in distribution, growing period, phenology, habitat, productivity, species composition, and migration. This study attempts to assess the current and future habitat suitability distribution of two dominant species of Central India, teak (Tectona grandis Linn. f.) and sal (Shorea robusta Gaertn. f.) using a maximum entropy (MaxEnt) model to predict species occurrences by finding the distribution that has the most spread. The future suitable habitat ranges of the species were modeled for two time periods (2050 and 2070) and two representative concentration pathways (RCP 2.6 and 8.5). Representative concentration pathways are scenarios that describe alternative trajectories for carbon dioxide emissions and the resulting atmospheric concentration from 2000 to 2100. We collected and modeled the spatially well-dispersed species occurrence points of teak and sal. The results suggested an increase in suitable habitat range for teak and a decrease for sal for both time periods and RCPs. Furthermore, the jackknife analysis identified temperature and precipitation seasonality as the major variables that influence the distribution of teak. In the case of sal, minimum temperature makes the maximum contribution to distribution changes. The suitable silvicultural strategies for forest management are proposed based on the future distribution of species in relation to the climate variables responsible for the change in their distribution range. These findings and strategies will help forest departments build future management plans for teak and sal forest with a focus on minimizing the impact of climate change. Study Implications: Our study used maximum entropy (MaxEnt) modeling to understand the impact of changing climate on the distribution of teak and sal forests of central India and to propose future silvicultural strategies. The study used MaxEnt model for two time periods and two climate change scenarios at highest resolution. An increase in future suitable habitat for teak and a decrease for sal is predicted by the model. Temperature for teak and precipitation for sal were identified as the major influencing climatic variables. We recommend forest and other related government departments to commission focused research to understand the changing patterns of species with climate change and design appropriate silviculture strategies for effective management.
{"title":"Predicting Impacts of Climate Change on Teak and Sal Forests in Central India Using Maximum Entropy Modeling: an Approach for Future Conservation and Silvicultural Strategies","authors":"Maneesh Kumar Patasaraiya, Rinku Moni Devi, Bhaskar Sinha, Jigyasa Bisaria","doi":"10.1093/forsci/fxad014","DOIUrl":"https://doi.org/10.1093/forsci/fxad014","url":null,"abstract":"\u0000 Climate change impacts on tropical forests and tree species have been documented as changes in distribution, growing period, phenology, habitat, productivity, species composition, and migration. This study attempts to assess the current and future habitat suitability distribution of two dominant species of Central India, teak (Tectona grandis Linn. f.) and sal (Shorea robusta Gaertn. f.) using a maximum entropy (MaxEnt) model to predict species occurrences by finding the distribution that has the most spread. The future suitable habitat ranges of the species were modeled for two time periods (2050 and 2070) and two representative concentration pathways (RCP 2.6 and 8.5). Representative concentration pathways are scenarios that describe alternative trajectories for carbon dioxide emissions and the resulting atmospheric concentration from 2000 to 2100. We collected and modeled the spatially well-dispersed species occurrence points of teak and sal. The results suggested an increase in suitable habitat range for teak and a decrease for sal for both time periods and RCPs. Furthermore, the jackknife analysis identified temperature and precipitation seasonality as the major variables that influence the distribution of teak. In the case of sal, minimum temperature makes the maximum contribution to distribution changes. The suitable silvicultural strategies for forest management are proposed based on the future distribution of species in relation to the climate variables responsible for the change in their distribution range. These findings and strategies will help forest departments build future management plans for teak and sal forest with a focus on minimizing the impact of climate change.\u0000 Study Implications: Our study used maximum entropy (MaxEnt) modeling to understand the impact of changing climate on the distribution of teak and sal forests of central India and to propose future silvicultural strategies. The study used MaxEnt model for two time periods and two climate change scenarios at highest resolution. An increase in future suitable habitat for teak and a decrease for sal is predicted by the model. Temperature for teak and precipitation for sal were identified as the major influencing climatic variables. We recommend forest and other related government departments to commission focused research to understand the changing patterns of species with climate change and design appropriate silviculture strategies for effective management.","PeriodicalId":12749,"journal":{"name":"Forest Science","volume":"12 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74661580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lumber prices can be volatile and hard to predict from month to month yet are important for many sectors of the economy, ranging from forestry and construction. An economic model of lumber prices was developed and applied to data representing multiple supply and demand determinants of lumber. Using a suite of econometric models, monthly lumber prices were related back to variables including construction permits, US reserve bank credit, tariffs with Canada, exchange rates with Canada, and variables representing shocks associated with the COVID-19 pandemic. Preferred models use relatively small amounts of publicly available information, making them more accessible to industry participants who want to make their own price predictions. Such information can help guide decisions about whether to expand or scale back an operation in preparation for likely future price movements. Study Implications: This study shows that Douglas-fir lumber prices in the US Northwest can be predicted quite accurately with selected macro-economic variables that are commonly reported in the public domain. Using statistical techniques, monthly lumber prices in the United States were related back to variables including new home construction permits, US reserve bank credit, tariffs, and exchange rates. With suitable assumptions about future economic conditions, the models could be used by researchers as well as professionals at lumber mills, wholesales, and retailers to make near term predictions.
{"title":"Determinants of Softwood Lumber Prices in the US Northwest","authors":"J. Reimer, Kenneth Annan","doi":"10.1093/forsci/fxad020","DOIUrl":"https://doi.org/10.1093/forsci/fxad020","url":null,"abstract":"\u0000 Lumber prices can be volatile and hard to predict from month to month yet are important for many sectors of the economy, ranging from forestry and construction. An economic model of lumber prices was developed and applied to data representing multiple supply and demand determinants of lumber. Using a suite of econometric models, monthly lumber prices were related back to variables including construction permits, US reserve bank credit, tariffs with Canada, exchange rates with Canada, and variables representing shocks associated with the COVID-19 pandemic. Preferred models use relatively small amounts of publicly available information, making them more accessible to industry participants who want to make their own price predictions. Such information can help guide decisions about whether to expand or scale back an operation in preparation for likely future price movements.\u0000 Study Implications: This study shows that Douglas-fir lumber prices in the US Northwest can be predicted quite accurately with selected macro-economic variables that are commonly reported in the public domain. Using statistical techniques, monthly lumber prices in the United States were related back to variables including new home construction permits, US reserve bank credit, tariffs, and exchange rates. With suitable assumptions about future economic conditions, the models could be used by researchers as well as professionals at lumber mills, wholesales, and retailers to make near term predictions.","PeriodicalId":12749,"journal":{"name":"Forest Science","volume":"12 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79043318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hassan A. M. Ali, J. Mohammadi, Shaban Shataee Jouibary
Accurate estimation of total aboveground biomass (TAGB) is an important challenge in evaluating and monitoring tree biomass. Thus, developing species-specific allometric models is essential. This study aimed to predict tree-level TAGB for Pinus brutia, Pinus pinea, Cupressus sempervirens, and the species-independent case using the most accurate allometric models, biomass conversion and expansion factor (BCEF), and mixed effect models in Golestan Province, Iran. The mean BCEFs for three species were 0.46, 0.47, and 0.86, respectively, and there was no significant difference (p>0.05) between TAGB predictions based on BCEF estimates for this study and observations of TAGB. The results revealed that compared with relative root mean square error (RMSE%) for the Intergovernmental Panel on Climate Change (IPCC) report–based BCEFs, the RMSE% for BCEFs estimated for this study were reduced by 46.91%. The results showed that a diameter at breast height (DBH), height (H), and wood density (ρ)-based model were the most accurate predictors for P. brutia (R2=0.98, RMSE%=14.11), whereas the DBH-based model and the DBH and H-based model were most accurate for P. pinea (R2=0.99, RMSE%=9.04) and C. sempervirens (R2=0.96, RMSE%=17.77), respectively. Compared to the allometric models, mixed-effect models using DBH, H, and ρ improved TAGB prediction for the species-independent case (3% increase in R2 and 6.81% decrease in RMSE%), but not for models for P. brutia, P. pinea, and C. sempervirens. Study Implications: Accurate prediction of total tree-level aboveground biomass (TAGB) requires the most accurate allometric models plus accurate biomass conversion and expansion factors (BCEFs). The relevance of this study is that few allometric models have been developed to predict tree-level TAGB for Pinus brutia, Pinus pinea, and Cupressus sempervirens. We developed allometric models and estimated BCEFs for predicting TAGB for P. brutia, P. pinea, and C. sempervirens in Golestan Province, Iran. We provide accurate allometric models and BCEFs based on available field data. Also, we provide tools to help forest managers predict TAGB.
{"title":"Allometric Models and Biomass Conversion and Expansion Factors to Predict Total Tree-level Aboveground Biomass for Three Conifers Species in Iran","authors":"Hassan A. M. Ali, J. Mohammadi, Shaban Shataee Jouibary","doi":"10.1093/forsci/fxad013","DOIUrl":"https://doi.org/10.1093/forsci/fxad013","url":null,"abstract":"\u0000 Accurate estimation of total aboveground biomass (TAGB) is an important challenge in evaluating and monitoring tree biomass. Thus, developing species-specific allometric models is essential. This study aimed to predict tree-level TAGB for Pinus brutia, Pinus pinea, Cupressus sempervirens, and the species-independent case using the most accurate allometric models, biomass conversion and expansion factor (BCEF), and mixed effect models in Golestan Province, Iran. The mean BCEFs for three species were 0.46, 0.47, and 0.86, respectively, and there was no significant difference (p>0.05) between TAGB predictions based on BCEF estimates for this study and observations of TAGB. The results revealed that compared with relative root mean square error (RMSE%) for the Intergovernmental Panel on Climate Change (IPCC) report–based BCEFs, the RMSE% for BCEFs estimated for this study were reduced by 46.91%. The results showed that a diameter at breast height (DBH), height (H), and wood density (ρ)-based model were the most accurate predictors for P. brutia (R2=0.98, RMSE%=14.11), whereas the DBH-based model and the DBH and H-based model were most accurate for P. pinea (R2=0.99, RMSE%=9.04) and C. sempervirens (R2=0.96, RMSE%=17.77), respectively. Compared to the allometric models, mixed-effect models using DBH, H, and ρ improved TAGB prediction for the species-independent case (3% increase in R2 and 6.81% decrease in RMSE%), but not for models for P. brutia, P. pinea, and C. sempervirens.\u0000 Study Implications: Accurate prediction of total tree-level aboveground biomass (TAGB) requires the most accurate allometric models plus accurate biomass conversion and expansion factors (BCEFs). The relevance of this study is that few allometric models have been developed to predict tree-level TAGB for Pinus brutia, Pinus pinea, and Cupressus sempervirens. We developed allometric models and estimated BCEFs for predicting TAGB for P. brutia, P. pinea, and C. sempervirens in Golestan Province, Iran. We provide accurate allometric models and BCEFs based on available field data. Also, we provide tools to help forest managers predict TAGB.","PeriodicalId":12749,"journal":{"name":"Forest Science","volume":"62 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79976109","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Preferential tax programs for forest landowners are used to achieve land use–related environmental and social objectives. Nonindustrial landowners are likely to own forests near development boundaries, which may lead to a higher likelihood of land conversion from forests to alternative uses. This article answers the question of how preferential tax programs for small-tract forestland (STF) owners have influenced the conversion of forested lands in Oregon since 2005. We find that a 10% increase in STF program participation within a county (as measured by acreage enrolled) can lead to a conversion of 127 ac from wildland forest to mixed forest/agriculture since the prior forest inventory period. Compared with the default “Forestland” tax program, participation in the alternative STF tax program has had a smaller and statistically weaker effect on the number of acres converted to low-density residential use. However, hypothetical elimination of the STF tax program would increase enrollment in the default Forestland tax program, which was measured to have a greater effect on the conversion of wildland forest to low-density residential land. Hence, the results overall provide evidence that the STF program has achieved its objective of mitigating development pressures and reducing conversion of forestland to nonforest uses. Study Implications: Forest landowners enrolled in preferential forest property tax programs pay lower property taxes. One objective of these programs is to reduce conversion of forests to other, nonforested land uses. We estimate the impact of such a tax program on land conversion in Oregon and find that participation rates do not contribute to land conversion towards low-density residential uses. However, enrollment in the alternative tax program does contribute to such conversion.
{"title":"Impacts of the Small-Tract Forestland Tax Program on Forestland Use in Oregon","authors":"D. Rossi, Ben Rushakoff, Olli-Pekka Kuusela","doi":"10.1093/forsci/fxad019","DOIUrl":"https://doi.org/10.1093/forsci/fxad019","url":null,"abstract":"\u0000 Preferential tax programs for forest landowners are used to achieve land use–related environmental and social objectives. Nonindustrial landowners are likely to own forests near development boundaries, which may lead to a higher likelihood of land conversion from forests to alternative uses. This article answers the question of how preferential tax programs for small-tract forestland (STF) owners have influenced the conversion of forested lands in Oregon since 2005. We find that a 10% increase in STF program participation within a county (as measured by acreage enrolled) can lead to a conversion of 127 ac from wildland forest to mixed forest/agriculture since the prior forest inventory period. Compared with the default “Forestland” tax program, participation in the alternative STF tax program has had a smaller and statistically weaker effect on the number of acres converted to low-density residential use. However, hypothetical elimination of the STF tax program would increase enrollment in the default Forestland tax program, which was measured to have a greater effect on the conversion of wildland forest to low-density residential land. Hence, the results overall provide evidence that the STF program has achieved its objective of mitigating development pressures and reducing conversion of forestland to nonforest uses.\u0000 Study Implications: Forest landowners enrolled in preferential forest property tax programs pay lower property taxes. One objective of these programs is to reduce conversion of forests to other, nonforested land uses. We estimate the impact of such a tax program on land conversion in Oregon and find that participation rates do not contribute to land conversion towards low-density residential uses. However, enrollment in the alternative tax program does contribute to such conversion.","PeriodicalId":12749,"journal":{"name":"Forest Science","volume":"46 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87310451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Lumber is one of the most essential forest products in the United States. During the first year of the COVID-19 pandemic, lumber prices almost quadrupled, and fluctuations reached record levels. Although market experts have pointed to various drivers of such high price volatility, no firm conclusions have been drawn yet. Using the generalized autoregressive conditional heteroskedasticity-mixed data sampling (GARCH-MIDAS) framework, this study assesses the potential drivers of lumber price volatility, with predictors including the Google Trends Web Search Index, housing starts, US lumber production quantity, and VIX index, representing public attention, housing demand, lumber supply, and macroeconomic concerns, respectively. We have found that housing demand is the key driver of lumber price volatility, followed by public attention. It is worth noting that US lumber supply and macroeconomic concerns have played a modest role in explaining lumber price volatility. Also, forecasting lumber price by using the housing demand variable substantially outperforms others. Market participants, including lumber mills, wholesalers, and home builders can get valuable information from the housing market to manage lumber price risk. Study Implications: The findings of this study can be used to improve hedging strategies, design option pricing formulas, and setting margin requirements. Critical information for price risk management on the lumber market can be gained by lumber market participants from the housing market. For forest management decisions by landowners, giving close attention to housing market would provide valuable information on the appropriate time for timber harvesting, because changes in the housing market affect lumber price that will indirectly affect the demand for timber, which is the most important factor of production for lumber mills.
{"title":"Price Volatility Modeling for the Lumber Futures Market: A Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling Approach","authors":"Prokash Deb, N. Assogba, Wenying Li","doi":"10.1093/forsci/fxad021","DOIUrl":"https://doi.org/10.1093/forsci/fxad021","url":null,"abstract":"\u0000 Lumber is one of the most essential forest products in the United States. During the first year of the COVID-19 pandemic, lumber prices almost quadrupled, and fluctuations reached record levels. Although market experts have pointed to various drivers of such high price volatility, no firm conclusions have been drawn yet. Using the generalized autoregressive conditional heteroskedasticity-mixed data sampling (GARCH-MIDAS) framework, this study assesses the potential drivers of lumber price volatility, with predictors including the Google Trends Web Search Index, housing starts, US lumber production quantity, and VIX index, representing public attention, housing demand, lumber supply, and macroeconomic concerns, respectively. We have found that housing demand is the key driver of lumber price volatility, followed by public attention. It is worth noting that US lumber supply and macroeconomic concerns have played a modest role in explaining lumber price volatility. Also, forecasting lumber price by using the housing demand variable substantially outperforms others. Market participants, including lumber mills, wholesalers, and home builders can get valuable information from the housing market to manage lumber price risk.\u0000 Study Implications: The findings of this study can be used to improve hedging strategies, design option pricing formulas, and setting margin requirements. Critical information for price risk management on the lumber market can be gained by lumber market participants from the housing market. For forest management decisions by landowners, giving close attention to housing market would provide valuable information on the appropriate time for timber harvesting, because changes in the housing market affect lumber price that will indirectly affect the demand for timber, which is the most important factor of production for lumber mills.","PeriodicalId":12749,"journal":{"name":"Forest Science","volume":"52 1 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86786371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study develops the theory of risk-averse importance sampling and explains its potential application to forest inventory estimation through the use of a heuristic simulation. When the risk-producing elements of the landscape are known, a risk-averse sampling strategy can be created that results in fewer samples in high-risk areas. Our simulation shows that for certain high-risk populations, risk-averse importance sampling can be highly effective at reducing both risk to field crew members (requiring only 10% of the plot visits in the riskiest category) and sample variance relative to simple random sampling. The method is shown to be especially helpful when a population of values of interest decreases with increasing risk, with a reduction in mean square error (MSE) of 84% to 99% in these cases. The simulation also showed the opposite effect on MSE can be expected when values of interest increase with increasing risk. By increasing field crew safety, risk-averse importance sampling should also improve the frequency and accuracy of field observations, potentially leading to even bigger gains in estimate precision. We recommend risk-averse importance sampling any time hazardous conditions can result in a high number of missing observations and reasonably accurate characterizations of landscape risks can be developed. Study Implications: During the collection of forest inventory data, the safety of field personnel is always of primary importance, but never has the safety of personnel been a component of the sample design. This study develops a risk-averse importance sampling strategy that provides a low-risk probability sample of field observations in high-risk areas for interested practitioners. The low-risk probability sample can be created when the risk-producing elements of the forested area are known and can be described in functional form. The method is shown to be especially helpful when a population of values of interest decrease with increasing risk. It is hypothesized that if a probability sample is defined that will reduce the sample in the riskiest areas and increase safety in the field, both response rates and the accuracy of field measurements will increase, and, in turn, will lead to a reduction in the variance of the final estimates. Risk-averse importance sampling is recommended any time it is likely to lead to a higher level of safety and observational success.
{"title":"Risk-Averse Importance Sampling of Tree Attributes in High-Risk Forested Areas","authors":"Francis A. Roesch, T. A. Schroeder, J. McCollum","doi":"10.1093/forsci/fxad022","DOIUrl":"https://doi.org/10.1093/forsci/fxad022","url":null,"abstract":"\u0000 This study develops the theory of risk-averse importance sampling and explains its potential application to forest inventory estimation through the use of a heuristic simulation. When the risk-producing elements of the landscape are known, a risk-averse sampling strategy can be created that results in fewer samples in high-risk areas. Our simulation shows that for certain high-risk populations, risk-averse importance sampling can be highly effective at reducing both risk to field crew members (requiring only 10% of the plot visits in the riskiest category) and sample variance relative to simple random sampling. The method is shown to be especially helpful when a population of values of interest decreases with increasing risk, with a reduction in mean square error (MSE) of 84% to 99% in these cases. The simulation also showed the opposite effect on MSE can be expected when values of interest increase with increasing risk. By increasing field crew safety, risk-averse importance sampling should also improve the frequency and accuracy of field observations, potentially leading to even bigger gains in estimate precision. We recommend risk-averse importance sampling any time hazardous conditions can result in a high number of missing observations and reasonably accurate characterizations of landscape risks can be developed.\u0000 Study Implications: During the collection of forest inventory data, the safety of field personnel is always of primary importance, but never has the safety of personnel been a component of the sample design. This study develops a risk-averse importance sampling strategy that provides a low-risk probability sample of field observations in high-risk areas for interested practitioners. The low-risk probability sample can be created when the risk-producing elements of the forested area are known and can be described in functional form. The method is shown to be especially helpful when a population of values of interest decrease with increasing risk. It is hypothesized that if a probability sample is defined that will reduce the sample in the riskiest areas and increase safety in the field, both response rates and the accuracy of field measurements will increase, and, in turn, will lead to a reduction in the variance of the final estimates. Risk-averse importance sampling is recommended any time it is likely to lead to a higher level of safety and observational success.","PeriodicalId":12749,"journal":{"name":"Forest Science","volume":"370 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75510559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chemical site preparation is a critical management practice for southern pine plantation establishment. Imazapyr and ester triclopyr are frequently used for chemical site preparation in the Lower Coastal Plain to control waxy leaf shrub species, yet limited information is available on optimal imazapyr and triclopyr tank mixes and individual herbicide application timing(s) to achieve maximum loblolly pine (Pinus taeda L.) growth. The objectives of this study were to determine the survival, growth, and stem defect response of 6-year-old loblolly pine to four chemical site preparation treatments plus an untreated control, three application timings, and first year herbaceous weed control (hwc) on a poorly drained flatwoods site. Treatments included two imazapyr and triclopyr rates applied as tank mixes, triclopyr and imazapyr alone, and an untreated control with hwc applied to half of each treatment plot. Results showed no treatment had superior survival or growth, whereas September-applied imazapyr and triclopyr tank mixes tended to result in improved growth. Triclopyr alone along with first year, banded hwc resulted in similar growth to imazapyr and triclopyr tank mixes. First-year hwc significantly enhanced survival and growth. Stem defects were more common in the chemical site preparation treatments than the control. Study Implications: Age-6-year results from this study indicate that loblolly pine (Pinus taeda L.) growth following application of chemical site preparation tank mixes containing imazapyr and triclopyr applied during September or October tended to be superior to July applications. Triclopyr applied alone with first growing season herbaceous weed control (hwc) may offer satisfactory near- and long-term loblolly pine growth as imazapyr and triclopyr tank mixtures on sites with similar competing vegetation. These findings may allow for less herbicide use on sites previously managed for pine production and show the importance of first year hwc for Coastal Plain flatwoods sites.
{"title":"Chemical Site Preparation Mixtures, Application Timing, and Herbaceous Weed Control Impacts on Loblolly Pine Development Through Six Years","authors":"D. Clabo, E. David Dickens","doi":"10.1093/forsci/fxad012","DOIUrl":"https://doi.org/10.1093/forsci/fxad012","url":null,"abstract":"\u0000 Chemical site preparation is a critical management practice for southern pine plantation establishment. Imazapyr and ester triclopyr are frequently used for chemical site preparation in the Lower Coastal Plain to control waxy leaf shrub species, yet limited information is available on optimal imazapyr and triclopyr tank mixes and individual herbicide application timing(s) to achieve maximum loblolly pine (Pinus taeda L.) growth. The objectives of this study were to determine the survival, growth, and stem defect response of 6-year-old loblolly pine to four chemical site preparation treatments plus an untreated control, three application timings, and first year herbaceous weed control (hwc) on a poorly drained flatwoods site. Treatments included two imazapyr and triclopyr rates applied as tank mixes, triclopyr and imazapyr alone, and an untreated control with hwc applied to half of each treatment plot. Results showed no treatment had superior survival or growth, whereas September-applied imazapyr and triclopyr tank mixes tended to result in improved growth. Triclopyr alone along with first year, banded hwc resulted in similar growth to imazapyr and triclopyr tank mixes. First-year hwc significantly enhanced survival and growth. Stem defects were more common in the chemical site preparation treatments than the control.\u0000 Study Implications: Age-6-year results from this study indicate that loblolly pine (Pinus taeda L.) growth following application of chemical site preparation tank mixes containing imazapyr and triclopyr applied during September or October tended to be superior to July applications. Triclopyr applied alone with first growing season herbaceous weed control (hwc) may offer satisfactory near- and long-term loblolly pine growth as imazapyr and triclopyr tank mixtures on sites with similar competing vegetation. These findings may allow for less herbicide use on sites previously managed for pine production and show the importance of first year hwc for Coastal Plain flatwoods sites.","PeriodicalId":12749,"journal":{"name":"Forest Science","volume":"6 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79719201","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yuan Tian, Xuan Liu, Xin Zhang, Sa Rula, Z. Wan, Hanqing Zhao, Qiuliang Zhang
Vapor pressure deficit (VPD) shows a gradually increasing trend that forces trees to produce ecological memory with time-delay characteristics to drought year by year. The reversible stem diameter variation of trees can serve as an indicator for tree water status. In the context of global warming, these variations can dynamically monitor the response of stem water to the change of environmental water, especially to VPD. In this study, stem diameter variations of Larix gmelinii Rupr. and environmental factors were measured at high temporal resolution. We analyzed the tree water deficit–induced stem shrinkage (TWD) response to VPD variations. The results showed that variation of TWD lagged behind that of VPD to a certain extent, by about 3–5.5 h. Environmental water supply of trees under natural conditions can be divided into water deficit and adequate water supply. The division of the two water conditions was helpful to study the correlation between TWD and VPD. Observing the response of changes of stem diameter to the time lag of VPD is helpful to accurately represent the relationship of changes between moisture in the tree body and moisture in the air and to identify the stress effect of the lag in a short period of time. Study Implications: Stem diameter changes with change in moisture in the environment and usually reversibly shrinks under water deficits. Such reversible change in stem diameter is closely related to change in vapor pressure deficit, which is an environmental factor. Tree water deficit–induced trunk shrinkage, an index reflecting the change in stem diameter affected by moisture, had a time lag correlation with vapor pressure deficit in terms of variation characteristics. The time lag of the tree water deficit–induced trunk shrinkage response to vapor pressure deficit was 3–5.5 h. Just as the phenomenon of ecological memory cannot be ignored in an observational study with the year as the time scale, the phenomenon of time lag should not be ignored during an observational study of moisture stress at small time scales.
{"title":"Time Lag of Stem Water Deficit in Response to Increased Vapor Pressure Deficit","authors":"Yuan Tian, Xuan Liu, Xin Zhang, Sa Rula, Z. Wan, Hanqing Zhao, Qiuliang Zhang","doi":"10.1093/forsci/fxad005","DOIUrl":"https://doi.org/10.1093/forsci/fxad005","url":null,"abstract":"\u0000 Vapor pressure deficit (VPD) shows a gradually increasing trend that forces trees to produce ecological memory with time-delay characteristics to drought year by year. The reversible stem diameter variation of trees can serve as an indicator for tree water status. In the context of global warming, these variations can dynamically monitor the response of stem water to the change of environmental water, especially to VPD. In this study, stem diameter variations of Larix gmelinii Rupr. and environmental factors were measured at high temporal resolution. We analyzed the tree water deficit–induced stem shrinkage (TWD) response to VPD variations. The results showed that variation of TWD lagged behind that of VPD to a certain extent, by about 3–5.5 h. Environmental water supply of trees under natural conditions can be divided into water deficit and adequate water supply. The division of the two water conditions was helpful to study the correlation between TWD and VPD. Observing the response of changes of stem diameter to the time lag of VPD is helpful to accurately represent the relationship of changes between moisture in the tree body and moisture in the air and to identify the stress effect of the lag in a short period of time.\u0000 Study Implications: Stem diameter changes with change in moisture in the environment and usually reversibly shrinks under water deficits. Such reversible change in stem diameter is closely related to change in vapor pressure deficit, which is an environmental factor. Tree water deficit–induced trunk shrinkage, an index reflecting the change in stem diameter affected by moisture, had a time lag correlation with vapor pressure deficit in terms of variation characteristics. The time lag of the tree water deficit–induced trunk shrinkage response to vapor pressure deficit was 3–5.5 h. Just as the phenomenon of ecological memory cannot be ignored in an observational study with the year as the time scale, the phenomenon of time lag should not be ignored during an observational study of moisture stress at small time scales.","PeriodicalId":12749,"journal":{"name":"Forest Science","volume":"35 3 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78427168","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Based on the Greenhouse Gas Reduction and Management Act passed in 2015 and the carbon neutral target in 2050, Taiwan will most likely follow international trends by imposing carbon taxes and establishing carbon offset markets. The positive and negative effects of carbon taxes and carbon offset markets on the economy and the environment merit further investigation. Accordingly, this study adopted a carbon emission reduction (CER) cost prediction model to assess the carbon abatement costs under three scenarios: (1) a carbon offset market exists, and forest carbon sequestration can be used as carbon offsets; (2) a carbon offset market exists, but forest carbon sequestration cannot be used as carbon offsets; and (3) a carbon offset market does not exist. Forests in Taipei (with low carbon emissions) and Kaohsiung (with high carbon emissions) were selected as research sites to explore the benefits of carbon emissions trading and forest carbon sequestration. The results show that CER costs are the lowest in scenario 1 and are the highest in scenario 3. The CER costs of Kaohsiung are higher than those of Taipei. The higher the carbon price, the greater the difference in CER costs between the two cities. Study Implications: The objective of this study was to identify the optimal policy for Taiwan to effectively slow climate change. This study showed that the opening of carbon offset markets and the use of forest carbon sequestration as carbon offsets may prompt regions to increase their forest stock to lower their emission reduction costs. However, achieving 2050 carbon neutral target by solely using forest carbon sequestration is not sufficient in Taiwan.
{"title":"Assessing Carbon Abatement Costs Considering Forest Carbon Sequestration and Carbon Offset Mechanism: Evidence from Taiwan","authors":"Wan-Yu Liu, Yingjie Lu, Chun-Cheng Lin","doi":"10.1093/forsci/fxad011","DOIUrl":"https://doi.org/10.1093/forsci/fxad011","url":null,"abstract":"\u0000 Based on the Greenhouse Gas Reduction and Management Act passed in 2015 and the carbon neutral target in 2050, Taiwan will most likely follow international trends by imposing carbon taxes and establishing carbon offset markets. The positive and negative effects of carbon taxes and carbon offset markets on the economy and the environment merit further investigation. Accordingly, this study adopted a carbon emission reduction (CER) cost prediction model to assess the carbon abatement costs under three scenarios: (1) a carbon offset market exists, and forest carbon sequestration can be used as carbon offsets; (2) a carbon offset market exists, but forest carbon sequestration cannot be used as carbon offsets; and (3) a carbon offset market does not exist. Forests in Taipei (with low carbon emissions) and Kaohsiung (with high carbon emissions) were selected as research sites to explore the benefits of carbon emissions trading and forest carbon sequestration. The results show that CER costs are the lowest in scenario 1 and are the highest in scenario 3. The CER costs of Kaohsiung are higher than those of Taipei. The higher the carbon price, the greater the difference in CER costs between the two cities.\u0000 Study Implications: The objective of this study was to identify the optimal policy for Taiwan to effectively slow climate change. This study showed that the opening of carbon offset markets and the use of forest carbon sequestration as carbon offsets may prompt regions to increase their forest stock to lower their emission reduction costs. However, achieving 2050 carbon neutral target by solely using forest carbon sequestration is not sufficient in Taiwan.","PeriodicalId":12749,"journal":{"name":"Forest Science","volume":"22 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86337427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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