Browsing by Subject "litter"

Now showing 1 - 4 of 4
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    Do evergreen and deciduous tree differ in their effects on soil nitrogen availability
    (Ecological Society of America, 2012) Mueller, Kevin E; Hobbie, Sarah E; Oleksyn, Jacek; Reich, Peter B; Eissenstat, David M
    Evergreen and deciduous plants are widely expected to have different impacts on soil nitrogen (N) availability because of differences in leaf litter chemistry and ensuing effects on net N mineralization (Nmin). We evaluated this hypothesis by compiling published data on net Nmin rates beneath co-occurring stands of evergreen and deciduous trees. The compiled data included 35 sets of co-occurring stands in temperate and boreal forests. Evergreen and deciduous stands did not have consistently divergent effects on net Nmin rates; net Nmin beneath deciduous trees was higher when comparing natural stands (19 contrasts), but equivalent to evergreens in plantations (16 contrasts). We also compared net Nmin rates beneath pairs of co-occurring genera. Most pairs of genera did not differ consistently, i.e., tree species from one genus had higher net Nmin at some sites and lower net Nmin at other sites. Moreover, several common deciduous genera (Acer, Betula, Populus) and deciduous Quercus spp. did not typically have higher net Nmin rates than common evergreen genera (Pinus, Picea). There are several reasons why tree effects on net Nmin are poorly predicted by leaf habit and phylogeny. For example, the amount of N mineralized from decomposing leaves might be less than the amount of N mineralized from organic matter pools that are less affected by leaf litter traits, such as dead roots and soil organic matter. Also, effects of plant traits and plant groups on net Nmin probably depend on site-specific factors such as stand age and soil type.
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    Trash-ICRA19: A Bounding Box Labeled Dataset of Underwater Trash
    (2020-07-21) Fulton, Michael S; Hong, Jungseok; Sattar, Junaed; irvlab@umn.edu; Sattar, Junaed; Interactive Robotics and Vision Lab
    This data was sourced from the J-EDI dataset of marine debris. The videos that comprise that dataset vary greatly in quality, depth, objects in scenes, and the cameras used. They contain images of many different types of marine debris, captured from real-world environments, providing a variety of objects in different states of decay, occlusion, and overgrowth. Additionally, the clarity of the water and quality of the light vary significantly from video to video. These videos were processed to extract 5,700 images, which comprise this dataset, all labeled with bounding boxes on instances of trash, biological objects such as plants and animals, and ROVs. The eventual goal is to develop efficient and accurate trash detection methods suitable for onboard robot deployment. It is our hope that the release of this dataset will facilitate further research on this challenging problem, bringing the marine robotics community closer to a solution for the urgent problem of autonomous trash detection and removal.
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    TrashCan 1.0 An Instance-Segmentation Labeled Dataset of Trash Observations
    (2020-07-23) Hong, Jungseok; Fulton, Michael S; Sattar, Junaed; irvlab@umn.edu; Sattar, Junaed; Interactive Robotics and Vision Lab
    The TrashCan dataset is comprised of annotated images (7,212 images currently) which contain observations of trash, ROVs, and a wide variety of undersea flora and fauna. The annotations in this dataset take the format of instance segmentation annotations: bitmaps containing a mask marking which pixels in the image contain each object. The imagery in TrashCan is sourced from the J-EDI (JAMSTEC E-Library of Deep-sea Images) dataset, curated by the Japan Agency of Marine Earth Science and Technology (JAMSTEC). This dataset contains videos from ROVs operated by JAMSTEC since 1982, largely in the sea of Japan. The dataset has two versions, TrashCan-Material and TrashCan-Instance, corresponding to different object class configurations. The eventual goal is to develop efficient and accurate trash detection methods suitable for onboard robot deployment. While datasets have previously been created containing bounding box level annotations of trash in marine environments, TrashCan is, to the best of our knowledge, the first instance-segmentation annotated dataset of underwater trash. It is our hope that the release of this dataset will facilitate further research on this challenging problem, bringing the marine robotics community closer to a solution for the urgent problem of autonomous trash detection and removal.
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    Tree species effects on decomposition and forest floor dynamics in a common garden
    (Ecological Society of America, 2006) Hobbie, Sarah E; Reich, Peter B; Oleksyn, Jacek; Ogdahl, Megan; Zytkowiak, Roma; Hale, Cynthia; Karolewski, Piotr
    We studied the effects of tree species on leaf litter decomposition and forest floor dynamics in a common garden experiment of 14 tree species (Abies alba, Acer platanoides, Acer pseudoplatanus, Betula pendula, Carpinus betulus, Fagus sylvatica, Larix decidua, Picea abies, Pinus nigra, Pinus sylvestris, Pseudotsuga menziesii, Quercus robur, Quercus rubra, and Tilia cordata) in southwestern Poland. We used three simultaneous litter bag experiments to tease apart species effects on decomposition via leaf litter chemistry vs. effects on the decomposition environment. Decomposition rates of litter in its plot of origin were negatively correlated with litter lignin and positively correlated with mean annual soil temperature (MATsoil) across species. Likewise, decomposition of a common litter type across all plots was positively associated with MATsoil, and decomposition of litter from all plots in a common plot was negatively related to litter lignin but positively related to litter Ca. Taken together, these results indicate that tree species influenced microbial decomposition primarily via differences in litter lignin (and secondarily, via differences in litter Ca), with high-lignin (and low-Ca) species decomposing most slowly, and by affecting MATsoil, with warmer plots exhibiting more rapid decomposition. In addition to litter bag experiments, we examined forest floor dynamics in each plot by mass balance, since earthworms were a known component of these forest stands and their access to litter in litter bags was limited. Forest floor removal rates estimated from mass balance were positively related to leaf litter Ca (and unrelated to decay rates obtained using litter bags). Litter Ca, in turn, was positively related to the abundance of earthworms, particularly Lumbricus terrestris. Thus, while species influence microbially mediated decomposition primarily through differences in litter lignin, differences among species in litter Ca are most important in determining species effects on forest floor leaf litter dynamics among these 14 tree species, apparently because of the influence of litter Ca on earthworm activity. The overall influence of these tree species on leaf litter decomposition via effects on both microbial and faunal processing will only become clear when we can quantify the decay dynamics of litter that is translocated belowground by earthworms.