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At least 901 records · Page 50

Biochemical and structural controls on the decomposition dynamics of boreal upland forest moss tissues

Mosses contribute an average of 20 % of boreal upland forest net primary productivity and are frequently observed to degrade slowly compared to vascular plants. If this is caused primarily by the chemical complexity of their tissues, moss decomposition could exhibit high temperature sensitivity (measured as Q 10 ) due to high activation energy, which would imply that soil organic carbon (SOC) stocks derived from moss remains are especially vulnerable to decomposition with warming. Alternatively, the physical structure of the moss cell-wall biochemical matrix could inhibit decomposition, resulting in low decay rates and low temperature sensitivity. We tested these hypotheses by incubating mosses collected from two boreal forests in Newfoundland, Canada, for 959 days at 5°C and 18°C, while monitoring changes in the moss tissue composition using total hydrolyzable amino acid (THAA) analysis and 13 C nuclear magnetic resonance (NMR) spectroscopy. Less than 40 % of C was respired in all incubations, revealing a large pool of apparently recalcitrant C. The decay rate of the labile fraction increased in the warmer treatment, but the total amount of C loss increased only slightly, resulting in low Q 10 values (1.23–1.33) compared to L horizon soils collected from the same forests. NMR spectra were dominated by O-alkyl C throughout the experiment, indicating the persistence of potentially labile C. The accumulation of hydroxyproline (derived primarily from plant cell-wall proteins) and aromatic C indicates the selective preservation of biochemicals associated with the moss cell wall. This was supported by scanning electron microscope (SEM) images of the moss tissues, which revealed few changes in the physical structure of the cell wall after incubation. This suggests that the moss cell-wall matrix protected labile C from microbial decomposition, accounting for the low temperature sensitivity of moss decomposition despite low decay rates. Climate drivers of moss biomass and productivity, therefore, represent a potentially important regulator of boreal forest SOC responses to climate change that needs to be assessed to improve our understanding of carbon–climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗

Strong temporal variation in treefall and branchfall rates in a tropical forest is related to extreme rainfall: results from 5 years of monthly drone data for a 50 ha plot

Abstract. A mechanistic understanding of how tropical-tree mortality responds to climate variation is urgently needed to predict how tropical-forest carbon pools will respond to anthropogenic global change, which is altering the frequency and intensity of storms, droughts, and other climate extremes in tropical forests. We used 5 years of approximately monthly drone-acquired RGB (red–green–blue) imagery for 50 ha of mature tropical forest on Barro Colorado Island, Panama, to quantify spatial structure; temporal variation; and climate correlates of canopy disturbances, i.e., sudden and major drops in canopy height due to treefalls, branchfalls, or the collapse of standing dead trees. Canopy disturbance rates varied strongly over time and were higher in the wet season, even though wind speeds were lower in the wet season. The strongest correlate of monthly variation in canopy disturbance rates was the frequency of extreme rainfall events. The size distribution of canopy disturbances was best fit by a Weibull function and was close to a power function for sizes above 25 m2. Treefalls accounted for 74 % of the total area and 52 % of the total number of canopy disturbances in treefalls and branchfalls combined. We hypothesize that extremely high rainfall is a good predictor because it is an indicator of storms having high wind speeds, as well as saturated soils that increase uprooting risk. These results demonstrate the utility of repeat drone-acquired data for quantifying forest canopy disturbance rates at fine temporal and spatial resolutions over large areas, thereby enabling robust tests of how temporal variation in disturbance relates to climate drivers. Further insights could be gained by integrating these canopy observations with high-frequency measurements of wind speed and soil moisture in mechanistic models to better evaluate proximate drivers and with focal tree observations to quantify the links to tree mortality and woody turnover.

54 ENVIRONMENTAL SCIENCES↗

Linking hydraulic traits to tropical forest function in a size-structured and trait-driven model (TFS v.1-Hydro)

Abstract. Forest ecosystem models based on heuristic water stress functions poorly predict tropical forest response to drought partly because they do not capture the diversity of hydraulic traits (including variation in tree size) observed in tropical forests. We developed a continuous porous media approach to modeling plant hydraulics in which all parameters of the constitutive equations are biologically interpretable and measurable plant hydraulic traits (e.g., turgor loss point πtlp, bulk elastic modulus ε, hydraulic capacitance Cft, xylem hydraulic conductivity ks,max, water potential at 50 % loss of conductivity for both xylem (P50,x) and stomata (P50,gs), and the leaf : sapwood area ratio Al : As). We embedded this plant hydraulics model within a trait forest simulator (TFS) that models light environments of individual trees and their upper boundary conditions (transpiration), as well as providing a means for parameterizing variation in hydraulic traits among individuals. We synthesized literature and existing databases to parameterize all hydraulic traits as a function of stem and leaf traits, including wood density (WD), leaf mass per area (LMA), and photosynthetic capacity (Amax), and evaluated the coupled model (called TFS v.1-Hydro) predictions, against observed diurnal and seasonal variability in stem and leaf water potential as well as stand-scaled sap flux. Our hydraulic trait synthesis revealed coordination among leaf and xylem hydraulic traits and statistically significant relationships of most hydraulic traits with more easily measured plant traits. Using the most informative empirical trait–trait relationships derived from this synthesis, TFS v.1-Hydro successfully captured individual variation in leaf and stem water potential due to increasing tree size and light environment, with model representation of hydraulic architecture and plant traits exerting primary and secondary controls, respectively, on the fidelity of model predictions. The plant hydraulics model made substantial improvements to simulations of total ecosystem transpiration. Remaining uncertainties and limitations of the trait paradigm for plant hydraulics modeling are highlighted.

58 GEOSCIENCES↗

Canopy structure modulates the sensitivity of subalpine forest stands to interannual snowpack and precipitation variability

A declining spring snowpack is expected to have widespread effects on montane and subalpine forests in western North America and across the globe. The way that tree water demands respond to this change will have important impacts on forest health and downstream water subsidies. Here, we present data from a network of sap velocity sensors and xylem water isotope measurements from three common tree species (Picea engelmannii, Abies lasiocarpa and Populus tremuloides) across a hillslope transect in a subalpine watershed in the Upper Colorado River basin. We use these data to compare tree- and stand-level responses to the historically high spring snowpack but low summer rainfall of 2019 against the low spring snowpack but high summer rainfall amounts of 2021 and 2022. From the sap velocity data, we found that only 40 % of the trees showed an increase in cumulative transpiration in response to the large snowpack year (2019), illustrating the absence of a common response to interannual spring snowpack variability. The trees that increased water use during the year with the large spring snowpack were all found in dense canopy stands – irrespective of species – while trees in open-canopy stands were more reliant on summer rains and, thus, more active during the years with modest snow and higher summer rain amounts. Using the sap velocity data along with supporting measurements of soil moisture and snow depth, we propose three mechanisms that lead to stand density modulating the tree-level response to changing seasonality of precipitation: Topographically mediated convergence zones have consistent access to recharge from snowmelt which supports denser stands with high water demands that are more reliant and sensitive to changing snow. Interception of summer rain in dense stands reduces the throughfall of summer rain to surface soils, limiting the sensitivity of the dense stands to changes in summer rain. Shading in dense stands allows the snowpack to persist deeper into the growing season, providing high local reliance on snow during the fore-summer (early-summer) drought period. Combining data generated from natural gradients in stand density, like this experiment, with results from controlled forest-thinning experiments can be used to develop a better understanding of the responses of forested ecosystems to futures with reduced spring snowpack.

54 ENVIRONMENTAL SCIENCES↗

Heavy snow loads in Finnish forests respond regionally asymmetrically to projected climate change

This study examined the impacts of projected climate change on heavy snow loads on Finnish forests, where snow-induced forest damage occurs frequently. For snow-load calculations, we used daily data from five global climate models under representative concentration pathway (RCP) scenarios RCP4.5 and RCP8.5, statistically downscaled onto a high-resolution grid using a quantile-mapping method. Our results suggest that projected climate warming results in regionally asymmetric response on heavy snow loads in Finnish forests. In eastern and northern Finland, the annual maximum snow loads on tree crowns were projected to increase during the present century, as opposed to southern and western parts of the country. The change was rather similar both for heavy rime loads and wet snow loads, as well as for frozen snow loads. Only the heaviest dry snow loads were projected to decrease over almost the whole of Finland. Our results are aligned with previous snowfall projections, typically indicating increasing heavy snowfalls over the areas with mean temperature below -8 °C. In spite of some uncertainties related to our results, we conclude that the risk for snow-induced forest damage is likely to increase in the future in the eastern and northern parts of Finland, i.e. in the areas experiencing the coldest winters in the country. In conclusion, the increase is partly due to the increase in wet snow hazards but also due to more favourable conditions for rime accumulation in a future climate that is more humid but still cold enough.

54 ENVIRONMENTAL SCIENCES↗

A meteorology and snow dataset from adjacent forested and meadow sites at Crested Butte, CO, USA

This dataset contains meteorology and snow observation data collected at sites in the southwestern Colorado Rocky Mountains during water years 2019-2021. Data collection had an emphasis on paired open-forest sites and included three forested elevations. In total, we present 270 snow pit observations, 4,019 snow depth measurements, and three years of meteorological forcing from two weather stations (one in a meadow, the other in an adjacent forest). The dataset is described in a forthcoming publication of the same name: A meteorology and snow dataset from adjacent forested and meadow sites at Crested Butte, CO, USA (Bonner et al., 2022).

54 ENVIRONMENTAL SCIENCES↗

Land use, forest density, soil mapping, erosion, drainage, salinity limitations

The author has identified the following significant results. The results of analyses show that it is possible to obtain information of practical significance as follows: (1) A quick and accurate estimate of the proper use of the valuable land can be made on the basis of temporal and spectral characteristics of the land features. (2) A rather accurate delineation of the major forest formations in the test areas was achieved on the basis of spatial and spectral characteristics of the studied areas. The forest stands were separated into two density classes; dense forest, and broken forest. On the basis of ERTS-1 data and the existing ground truth information a rather accurate mapping of the major vegetational forms of the mountain ranges can be made. (3) Major soil formations are mapable from ERTS-1 data: recent alluvial soils; soil on quarternary deposits; severely eroded soil and lithosol; and wet soils. (4) An estimation of cost benefits cannot be made accurately at this stage of the investigation. However, a rough estimate of the ratio of the cost for obtaining the same amount information from ERTS-1 data and from conventional operations would be approximately 1:6 to 1:10, in favor of the ERTS-1.

Yassoglou, N. J.↗

Detecting Disturbances in a Forest Environment

The interchange between forest and nonforest land and most man-made and natural forest disturbances can be detected on 1:120,000-scale color-infrared film. Bulk multispectral scanner imagery from the Earth Resources Technology Satellite combined and enhanced at a scale of 1:1,000,000 shows major changes in forest and nonforest land-use categories, many timber harvested areas, and some natural disturbances. Late fall to late spring is the best period of the year for detecting forest disturbances. In a study in Georgia, 79 percent of the disturbances in one county were detected on an ERTS color composite for April 1973 with only 12 percent commission error.

Aldrich, R. C.↗

Evaluation of Skylab (EREP) data for forest and rangeland surveys

The author has identified the following significant results. Four widely separated sites (near Augusta, Georgia; Lead, South Dakota; Manitou, Colorado; and Redding, California) were selected as typical sites for forest inventory, forest stress, rangeland inventory, and atmospheric and solar measurements, respectively. Results indicated that Skylab S190B color photography is good for classification of Level 1 forest and nonforest land (90 to 95 percent correct) and could be used as a data base for sampling by small and medium scale photography using regression techniques. The accuracy of Level 2 forest and nonforest classes, however, varied from fair to poor. Results of plant community classification tests indicate that both visual and microdensitometric techniques can separate deciduous, conifirous, and grassland classes to the region level in the Ecoclass hierarchical classification system. There was no consistency in classifying tree categories at the series level by visual photointerpretation. The relationship between ground measurements and large scale photo measurements of foliar cover had a correlation coefficient of greater than 0.75. Some of the relationships, however, were site dependent.

Aldrich, R. C.↗

Use of multiple-stage remote sensing techniques to develop forest stocking equations

Portions of a forest supporting density levels that affect natural resource yields must be quantified to estimate the operational feasibility of a proposed management system. Estimates of average parameters do not necessarily provide complete knowledge, particularly with frequently skewed forest parameters. Instead, another statistic, the portion of a forest supporting minimum density levels would be useful to set realistic limits to the implementation of management systems and to establish priorities for operational programs. Such a statistic can be obtained from solutions of forest stocking equations generated by applications of multiple-stage remote sensing techniques.

Bisson, H. R.↗

Forest type mapping with satellite data

Computer classification of data from Landsat, an earth-orbiting satellite, has resulted in measurements and maps of forest types for two New Hampshire counties. The acreages of hardwood and softwood types and total forested areas compare favorably with Forest Service figures for the same areas. These techniques have advantages for field application, particularly in states having forest taxation laws based on general productivity.

Dodge, A. G., Jr.↗

Inventory of forest resources (including water) by multi-level sampling

The author has identified the following significant results. A stratified random sample using LANDSAT band 5 and 7 panchromatic prints resulted in estimates of water in counties with sampling errors less than + or - 9% (67% probability level). A forest inventory using a four band LANDSAT color composite resulted in estimates of forest area by counties that were within + or - 6.7% and + or - 3.7% respectively (67% probability level). Estimates of forest area for counties by computer assisted techniques were within + or - 21% of operational forest survey figures and for all counties the difference was only one percent. Correlations of airborne terrain reflectance measurements with LANDSAT radiance verified a linear atmospheric model with an additive (path radiance) term and multiplicative (transmittance) term. Coefficients of determination for 28 of the 32 modeling attempts, not adverseley affected by rain shower occurring between the times of LANDSAT passage and aircraft overflights, exceeded 0.83.

Aldrich, R. C.↗

Multistage variable probability forest volume inventory

The net board foot volume (Scribner log rule) of the standing Ponderosa pine timber on the Defiance Unit of the Navajo Nation's forested land was estimated using a multistage forest volume inventory scheme with variable sample selection probabilities. The inventory designed to accomplish this task required that both LANDSAT MSS digital data and aircraft acquired data be used to locate one acre ground splits, which were subsequently visited by ground teams conducting detailed tree measurements using an optical dendrometer. The dendrometer measurements were then punched on computer input cards and were entered in a computer program developed by the U.S. Forest Service. The resulting individual tree volume estimates were then expanded through the use of a statistically defined equation to produce the volume estimate for the entire area which includes 192,026 acres and is approximately a 44% the total forested area of the Navajo Nation.

Anderson, J. E.↗

New State Forest Practice Laws. A review of state laws and their natural resource data requirements

Forest practice regulations can be established by being specified in state law or by being promulgated by some other official body delegated the authority to do so. At the state level, public regulation of private forest practices resulted in many cases, in the enactment of state forest practice laws regulating both private, and in some cases, public landowner activities. These laws aim not only to protect natural environments, but also to encourage continuous productivity of forest lands, to maintain or enhance aesthetic values, and to serve as an implementing mechanism to control water pollution. Profiles of regulations in California, Idaho, Maine, Nevada, New Hampshire, Oregon, and Washington are examined and assessed. Voluntary guidelines in use in 18 states are summarized.

Klein, S. B.↗

Landsat for practical forest type mapping - A test case

Computer classified Landsat maps are compared with a recent conventional inventory of forest lands in northern Maine. Over the 196,000 hectare area mapped, estimates of the areas of softwood, mixed wood and hardwood forest obtained by a supervised classification of the Landsat data and a standard inventory based on aerial photointerpretation, probability proportional to prediction, field sampling and a standard forest measurement program are found to agree to within 5%. The cost of the Landsat maps is estimated to be $0.065/hectare. It is concluded that satellite techniques are worth developing for forest inventories, although they are not yet refined enough to be incorporated into current practical inventories.

Bryant, E.↗

An evaluation of ISOCLS and CLASSY clustering algorithms for forest classification in northern Idaho

Both the iterative self-organizing clustering system (ISOCLS) and the CLASSY algorithms were applied to forest and nonforest classes for one 1:24,000 quadrangle map of northern Idaho and the classification and mapping accuracies were evaluated with 1:30,000 color infrared aerial photography. Confusion matrices for the two clustering algorithms were generated and studied to determine which is most applicable to forest and rangeland inventories in future projects. In an unsupervised mode, ISOCLS requires many trial-and-error runs to find the proper parameters to separate desired information classes. CLASSY tells more in a single run concerning the classes that can be separated, shows more promise for forest stratification than ISOCLS, and shows more promise for consistency. One major drawback to CLASSY is that important forest and range classes that are smaller than a minimum cluster size will be combined with other classes. The algorithm requires so much computer storage that only data sets as small as a quadrangle can be used at one time.

Werth, L. F.↗

Radar imagery for forest cover mapping

Dual-polarized, X-band Synthetic Aperture Radar (SAR) imagery was obtained from an altitude of 60,000 feet over a test area near Camden, SC on June 30, 1980. The objective of this study was to determine, qualitatively, the value of the SAR imagery for identifying various forest cover types. In analyzing the HH and HV polarization images, particular attention was given to the tonal and textural characteristics of the cover types involved. The analysis of the dual-polarized SAR imagery has shown that certain forest cover features are more easily identified in one polarization than the other, while some features look very similar in both polarizations. In general, the results for this data set have shown that the overall tonal contrast between features was greater on the HH image. Neither polarization was consistently better for identifying the various forest cover types examined. These results suggest the usefulness of a dual-polarized SAR system for mapping forest cover.

Knowlton, D. J.↗

Development and testing of LANDSAT-assisted procedures for cost-effective forest management

The capability of LANDSAT data to make certain forest management activities on the Clearwater National Forest in Idaho more efficient and/or more effective was examined. One task was designed to evaluate the utility of single-date categorized LANDSAT data as a source of land cover information for use in assessing elk habitat quality. LANDSAT data was used to categorize conifer forest on the basis of the percentage crown closure. This information was used to evaluate elk habitat quality on the basis of the ratio of cover to forage. A preliminary conclusion is that categorized LANDSAT data can be helpful for assessing current elk habitat quality if the relationships between crown closure and hiding cover can be adequately defined. Another task was designed to evaluate the utility of merged two-date LANDSAT data for updating the existing (1972) Clearwater Forest land cover information. LANDSAT data from 1972 and 1981 were merged, and change images were created. These products indicated where major changes were taking place. These areas could then be examined on aerial photography or in the field to further characterize the nature and magnitude of the change. The 1972 land cover information could be subsequently altered in these changed areas, whereas areas with no change would not have to be re-examined.

Colwell, J. E.↗