How to maximize the joint benefits of timber production and carbon sequestration for rural areas? A case study of larch plantations in northeast China.

BACKGROUND: Implementing large-scale carbon sink afforestation may contribute to carbon neutrality targets and increase the economic benefits of forests in rural areas. However, how to manage planted forests in China to maximize the joint benefits of timber production and carbon sequestration is still unclear. Therefore, the present study quantified the effects of different rotation lengths, thinning treatments, site quality (SCI), stand density (SDI), and management costs on the joint benefits of carbon sequestration and timber production based on a stand-level model system developed for larch plantations in northeast China. RESULTS: The performances of the different scenarios on carbon stocks were satisfactory, where the variations in the outcomes of final carbon stocks could be explained by up to 90%. The joint benefits increased significantly with the increases of SDIs and SCIs, regardless of which rotation length and thinning treatments were evaluated. Early thinning treatments decreased the joint benefits significantly by approximately 131.53% and 32.16% of middle- and higher-SDIs, however longer rotations (60 years) could enlarge it by approximately 71.39% and 80.27% in scenarios with and without thinning when compared with a shorter rotation length (40 years). Discount rates and timber prices were the two most important variables affecting joint benefits, while the effects of carbon prices were not as significant as expected in the current trading market in China. CONCLUSIONS: The management plans that promote longer rotations, higher stand densities, and no thinning treatments can maximize the joint benefits of carbon sequestration afforestation and timber production from larch plantations located in northeast China.

The effects of nearby trees on the positional accuracy of GNSS receivers in a forest environment.

Global Navigational Satellite System (GNSS) technologies are actively being developed to address the demand for enhanced positional accuracy. Smartphones are the most prevalent GNSS receiver today and have garnered attention thanks to improved positional accuracy and usability that can be accessed at an affordable price. In a forested environment, multipath error can deteriorate the positional accuracy, depending on the state of nearby vegetation. Therefore, this study was conducted to investigate the impacts of the size and location of vegetation on positional accuracy of GNSS receivers to determine whether the errors observed are systematic. Twenty-six control points within the Whitehall Forest GPS Test site in Athens, Georgia were used to evaluate positional accuracy of three different GNSS receivers (two traditional handheld GNSS receivers (including Garmin and Trimble receivers) and a smartphone). Thirty-five forest variables were developed from information around each control point to conduct a correlation analysis with observed horizontal position error in the positions determined by each device. In this study, we confirmed that the positional error of the smartphone was significantly lower than the Garmin receiver, and similar, but significantly different than the positional error observed by the Trimble receiver. It was confirmed that correlations between forest variables and horizontal position error regardless of the GNSS receiver employed were significant, yet trends were not consistent. The effect of the size of nearby trees on horizontal position error could not be generalized; however, the location of nearby trees on horizontal position error could.

Comparison between graph theory connectivity indices and landscape connectivity metrics for modeling river water quality in the southern Caspian sea basin.

The maintenance of connectivity is critical to the proper functioning of an ecosystem. The present study was conducted with the aim of comparing graph theory connectivity indices and landscape connectivity metrics for the purpose of modeling river water quality. To conduct this study, a forest layer was extracted from land cover map and 25 large watersheds were selected. River water quality was then assessed from the perspective of 8 landscape connectivity metrics and 12 graph theory indices. We developed predictive models using stepwise linear regression, power, exponential, and logarithmic models to locate the best model form for each water quality parameter (dependent variable) we examined. The results indicated that models developed using graph theory connectivity indices resulted in higher coefficients of determination (R2) than models developed using landscape metrics. Only 5 independent variables from a potential set of 13 were significant in explaining the variation in water quality parameters. Also, the models with the highest R2 attempted to explain variations in CO3 (0.818), water discharge (0.733), and Ca levels (0.702). Therefore, the results of this study showed that graph theory connectivity indices had more significant correlation with water quality parameters compared to landscape connectivity metrics. This work also indicates that there exist nonlinear relationships among connectivity indices and water quality parameters.

Urban land use cover changes in three developed cities of the United States: San Diego, Denver, and Buffalo.

Using imagery available through Google Earth Pro and a point sampling methodology, changes in land cover for three U.S. cities were assessed, beginning during the Great Recession (2007) and extending through to 2018. The cities were Buffalo (New York), Denver (Colorado), and San Diego (California), and 11 land cover classes were used to characterize each. The novel contributions of this work, and the innovative contributions to science include an analysis of urban land cover change in the years since the Great Recession, and the use of point pattern analysis on sample points that changed from non-developed in 2007 to developed in 2018, to determine whether a spatial pattern of land cover class change was evident. An initial assumption was made that forest cover change in these three cities would be minimal since the Great Recession. In fact, forest cover decreased by less than 1% in all three cities with the greatest decrease in Buffalo. Over the post-recession study period, increases in the developed land classes were evident in all three cities at the expense of grasses, tree cover, and other land classes. Some clustering of new development activities was noticed at a relatively small scale in San Diego, while some dispersion of new developed activities was noticed at a larger scale in Denver. Among other factors, changes in population, economics, and land use are factors that influence land cover change with specific impacts on forest cover, and therefore in the provision of urban forest benefits to the environment and society.

The applicability of recreation-grade GNSS receiver (GPS watch, Suunto Ambit Peak 3) in a forested and an open area compared to a mapping-grade receiver (Trimble Juno T41).

Due to developments in global navigation satellite systems (GNSS) and the miniaturization of their components, the usage of Global Positioning System (GPS) is no longer restricted to professional applications, but has become available in various consumer type devices, such as wristwatches. These commercial devices, however, were primarily designed for tracking activities in predominately urban settings and their accuracy has not been tested in forested areas. In this study, we present an assessment of the positional accuracy of a GPS watch (Ambit Peak 3, Suunto, Finland) under different forest cover types, seasons and meteorological conditions within the Whitehall Forest GPS Test Site located in Athens, Georgia, USA. As a standard of comparison, the performance of the GPS watch measurements was juxtaposed to that of a mapping-grade receiver (Juno T41, Trimble Inc., USA). In this study, we analyzed the differences between the determined and control positions using root-mean-square-error (RMSE), along with the distribution of observed positions through the standard deviational ellipse. The results suggest that the seasonal variations contributed to a statistically significant impact on the RMSE values for the GPS watch. However, there were no statistically significant differences in horizontal position accuracy by forest cover-type when using the GPS watch. Furthermore, no significant differences were found in horizontal position accuracy during the leaf-off period between the RMSE values for the GPS watch and those of the mapping-grade receiver. Lastly, the positional accuracies for both types of receivers were found to be weakly, but significantly correlated with fluctuations in air temperature and absolute humidity.

Smartphone GPS accuracy study in an urban environment.

An iPhone 6 using the Avenza software for capturing horizontal positions was employed to understand relative positional accuracy in an urban environment, during two seasons of the year, two times of day, and two perceived WiFi usage periods. On average, time of year did not seem to influence the average error observed in horizontal positions when GPS-only (no WiFi) capability was enabled, nor when WiFi was enabled. Observations of average horizontal position error only seemed to improve with time of day (afternoon) during the leaf-off season. During each season and during each time of day, horizontal position error seemed to improve in general during perceived high WiFi usage periods (when more people were present). Overall average horizontal position accuracy of the iPhone 6 (7-13 m) is consistent with the general accuracy levels observed of recreation-grade GPS receivers in potential high multi-path environments.

How a GNSS Receiver Is Held May Affect Static Horizontal Position Accuracy.

The static horizontal position accuracy of a mapping-grade GNSS receiver was tested in two forest types over two seasons, and subsequently was tested in one forest type against open sky conditions in the winter season. The main objective was to determine whether the holding position during data collection would result in significantly different static horizontal position accuracy. Additionally, we wanted to determine whether the time of year (season), forest type, or environmental variables had an influence on accuracy. In general, the F4Devices Flint GNSS receiver was found to have mean static horizontal position accuracy levels within the ranges typically expected for this general type of receiver (3 to 5 m) when differential correction was not employed. When used under forest cover, in some cases the GNSS receiver provided a higher level of static horizontal position accuracy when held vertically, as opposed to held at an angle or horizontally (the more natural positions), perhaps due to the orientation of the antenna within the receiver, or in part due to multipath or the inability to use certain satellite signals. Therefore, due to the fact that numerous variables may affect static horizontal position accuracy, we only conclude that there is weak to moderate evidence that the results of holding position are significant. Statistical test results also suggest that the season of data collection had no significant effect on static horizontal position accuracy, and results suggest that atmospheric variables had weak correlation with horizontal position accuracy. Forest type was found to have a significant effect on static horizontal position accuracy in one aspect of one test, yet otherwise there was little evidence that forest type affected horizontal position accuracy. Since the holding position was found in some cases to be significant with regard to the static horizontal position accuracy of positions collected in forests, it may be beneficial to have an understanding of antenna positioning within the receiver to achieve the greatest accuracy during data collection.

Cumulative ecological and socioeconomic effects of forest policies in coastal Oregon.

Forest biodiversity policies in multi-ownership landscapes are typically developed in an uncoordinated fashion with little consideration of their interactions or possible unintended cumulative effects. We conducted an assessment of some of the ecological and socioeconomic effects of recently enacted forest management policies in the 2.3-million-ha Coast Range Physiographic Province of Oregon. This mountainous area of conifer and hardwood forests includes a mosaic of landowners with a wide range of goals, from wilderness protection to high-yield timber production. We projected forest changes over 100 years in response to logging and development using models that integrate land use change and forest stand and landscape processes. We then assessed responses to those management activities using GIS models of stand structure and composition, landscape structure, habitat models for focal terrestrial and aquatic species, timber production, employment, and willingness to pay for biodiversity protection. Many of the potential outcomes of recently enacted policies are consistent with intended goals. For example, we project the area of structurally diverse older conifer forest and habitat for late successional wildlife species to strongly increase. 'Other outcomes might not be consistent with current policies: for example, hardwoods and vegetation diversity strongly decline within and across owners. Some elements of biodiversity, including streams with high potential habitat for coho salmon (Oncorhynchus kisutch) and sites of potential oak woodland, occur predominately outside federal lands and thus were not affected by the strongest biodiversity policies. Except for federal lands, biodiversity policies were not generally characterized in sufficient detail to provide clear benchmarks against which to measure the progress or success. We conclude that land management institutions and policies are not well configured to deal effectively with ecological issues that span broad spatial and temporal scales and that alternative policies could be constructed that more effectively provide for a mix of forest values from this region.

Simulating forest structure, timber production, and socioeconomic effects in a multi-owner province.

Protecting biodiversity has become a major goal in managing coastal forests in the Pacific Northwest--an area in which human activities have had a significant influence on landscape change. A complex pattern of public and private forest ownership, combined with new regulations for each owner group, raises questions about how well and how efficiently these policies achieve their biodiversity goals. To develop a deeper understanding of the aggregate effect of forest policies, we simulated forest structures, timber production, and socioeconomic conditions over time for the mixture of private and public lands in the 2.3-million-ha Coast Range Physiographic Province of Oregon. To make these projections, we recognized both vegetative complexity at the stand level and spatial complexity at the landscape level. We focused on the two major factors influencing landscape change in the forests of the Coast Range: (1) land use, especially development for houses and cities, and (2) forest management, especially clearcutting. Our simulations of current policy suggest major changes in land use on the margins of the Coast Range, a divergence in forest structure among the different owners, an increase in old-growth forests, and a continuing loss of the structural elements associated with diverse young forests. Our simulations also suggest that current harvest levels can be approximately maintained, with the harvest coming almost entirely from private lands. A policy alternative that retained live trees for wildlife would increase remnant structures but at a cost to landowners (5-7% reduction in timber production). Another alternative that precluded thinning of plantations on federal land would significantly reduce the area of very large diameter (>75 cm dbh) conifer forests 100 years into the future