Browsing by Subject "tree cover"

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    Data supporting: Century-scale wood nitrogen isotope trajectories from an oak savanna with variable fire frequencies
    (2020-09-09) Trumper, Matthew L; Griffin, Daniel; Hobbie, Sarah E; Howard, Ian M; Nelson, David M; Reich, Peter B; McLauchlan, Kendra K; trump022@umn.edu; Trumper, Matthew L; University of Minnesota Griffin Research Lab
    Fire frequency exerts a fundamental control on productivity and nutrient cycling in savanna ecosystems. A single fire event often increases short-term nitrogen (N) availability to individual plants, but repeated burning causes ecosystem carbon and N losses and can ultimately decrease soil organic matter and N availability. However, these effects remain poorly understood due to limited long-term biogeochemical data. Here, we leveraged one of the longest running prescribed burn experiments (established in 1964) to evaluate how fire frequency and changing vegetation composition influenced wood stable N isotopes (δ15N) across space and time. We developed multiple δ15N records across a burn frequency gradient from precisely dated Quercus macrocarpa tree-rings in an oak savanna at Cedar Creek Ecosystem Science Reserve, Minnesota, USA. Sixteen trees were sampled across four treatment stands that varied in temporal onset of burning and burn frequency, but were consistent in overstory species representation, soil characteristics, and topography. Burn frequency ranged from an unburned control stand to a high fire-frequency stand that burned in four of every five years during the past 55 years. Because N stocks and net N mineralization rates are currently lowest in frequently burned stands, we hypothesized that wood δ15N trajectories would have declined over time in all burned stands, but at a rate proportional to fire frequency. We found that wood δ15N records within each stand were remarkably coherent in their mean state and trend through time. A gradual, temporally synchronous decline in wood δ15N occurred in the mid 20th century in the no-, low-, and medium-fire stands, whereas there was no trend in the high-fire stand. The decline in the three stands did not systematically coincide with the onset of prescribed burning. Thus, we found limited evidence for variation in wood δ15N that could be attributed directly to long-term fire frequency in this prescribed burn experiment in temperate oak savanna. Our wood δ15N results may instead reflect decadal-scale changes in vegetation composition and abundance due to early to mid 20th century fire suppression.
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    Remote sensing-based approaches for large-scale comprehensive assessments of tree cover and windbreaks in the Great Plains region of the United States
    (2020-08) Meneguzzo, Dacia
    Trees are an important resource in the Great Plains region of the United States yet little information describing their extent and location is readily available in formats that are convenient for resource professionals and decision makers. National forest inventory and natural resource monitoring programs seldom account for these non-traditional forests in their official statistics. In addition, most satellite-derived datasets are too coarse to accurately depict small or narrow groupings of trees common in the Great Plains. As a result, there is a lack of scale-appropriate data for inventory and monitoring of these tree resources. Methods are needed to conduct large-scale comprehensive assessments of tree cover in the Great Plains. Remote sensing-based approaches offer several advantages over ground based inventories because they are often cost effective, they alleviate access issues, and they provide wall-to-wall spatial coverage. The research presented here will demonstrate that tree cover can be mapped at a statewide level using an object-based image analysis (OBIA) approach and high-resolution (i.e., 1 m) digital aerial photography from the National Agriculture Imagery Program (NAIP) as the sole data source. Initial results indicated that the OBIA method was more accurate in terms of describing the actual observed spatial pattern of tree cover and produced a more realistic output product compared to a pixel-based classification method. Next, technological improvements were made to the OBIA method to make it more robust for operational land cover mapping at a regional level. Lastly, a shape-based classification approach was developed for positively identifying various configurations of windbreaks (both single and multiple-leg) from the output land cover maps, which is an improvement over existing methods that only map single-leg windbreaks. This is important for management purposes since windbreaks provide many ecological and economic benefits on the landscape, from conserving topsoil to protecting crops, livestock, and farmsteads from the harsh effects of wind. The outcomes of this research are actual published (or in the process of) high-resolution geospatial data products that are publicly available for download. These datasets identify and provide detailed spatial information about mapped tree cover and windbreaks that can be summarized at a variety of scales, from individual farms to the state or regional level. In addition, they are valuable for many different types of research studies and on-the-ground management activities. In a region of climate extremes, the hope is that these datasets will support informed decision making for placing trees in the right place on the landscape to maximize the benefits they can provide. For example, one of the goals in this region is windbreak establishment in areas with highly erodible soils that lack trees arranged as windbreaks. These maps will assist with such planting efforts as stated by Darci Paull, a GIS technician with Kansas Forest Service, “If we know where windbreaks are, then we know where they aren’t. Combining this information with other spatial information, for example, highly erodible soils data, we can identify at-risk soils that would benefit from the protection of a windbreak.”