Conservation of an Ant-plant Mutualism in Native Forests and Ecologically-managed Tree Monocultures

The aim of this work was to assess the soil erosion process in native forest by the 137Cs methodology. The mass balance model was applied to assess the rates of soil loss in three native forests around of Londrina city, Paraná, Brazil. 137Cs distribution depth was of exponential type for the three forests and 137Cs inventory was 241 Bq m-2 for Mata 1, 338 Bq m-2 for Mata 2 and 325 Bq m-2 for Mata UEL. The soil loss value calculated for three native forests was: 6,684 kg ha-1 yr-1 for Mata 1, 1,788 kg ha-1 yr-1 for Mata 2 and 4,524 kg ha-1 yr-1 for Mata UEL.

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Diversity and Ecology of Edible Mushrooms from Patagonia Native Forests, Argentina

Mushrooms, Humans and Nature in a Changing World ◽

10.1007/978-3-030-37378-8_11 ◽

2020 ◽

pp. 297-318

Author(s):

Carolina Barroetaveña ◽

Carolina V. Toledo

Keyword(s):

Edible Mushrooms ◽

Native Forests

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Forest Governance in Brazil and Chile: Institutions and Practices in the Implementation of Sustainable Management of Native Forests

Ecological Economic and Socio Ecological Strategies for Forest Conservation ◽

10.1007/978-3-030-35379-7_11 ◽

2020 ◽

pp. 213-226

Author(s):

Liviam Elizabeth Cordeiro-Beduschi

Keyword(s):

Sustainable Management ◽

Forest Governance ◽

Native Forests

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How to Become a Mushroom: A New Nature Ethnography of Fungi in Aotearoa

10.26686/wgtn.17143925 ◽

2021 ◽

Author(s):

◽

Alice Nicholls

Keyword(s):

New Zealand ◽

West Coast ◽

Nature Writing ◽

The West ◽

Multispecies Ethnography ◽

Ethnographic Fieldwork ◽

Native Forests ◽

Transformative Potential ◽

The Moment

This thesis proposes that the moment of interaction between a person and a fungus is transformative of both subjects. Using new nature writing techniques in tandem with multispecies ethnography, this thesis seeks to present a rich, autoethnographic account of my encounters with fungi in the native forests of the West Coast of Aotearoa. Drawing on five days of ethnographic fieldwork spent at the Fungal Network of New Zealand (FUNNZ) annual Fungal Foray in the township of Moana, I explore the affective, emotional, sensory, intellectual, and corporeal experiences of interacting with fungi. Using new nature writing as an ethnographic medium, I suggest that narratives that pertain to the researcher’s experiences can render new understandings of nonhuman subjects. In doing so, I explore both the transformative potential of multispecies encounters for the researcher and the researched, and the literary potential of multispecies ethnography to illustrate the encounters themselves.

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Identifying woody vegetation on coal surface mines using phenological indicators with multitemporal Landsat imagery

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-1-339-2014 ◽

2014 ◽

Vol XL-1 ◽

pp. 339-345 ◽

Cited By ~ 3

Author(s):

A. J. Oliphant ◽

J. Li ◽

R. H. Wynne ◽

P. F. Donovan ◽

C. E. Zipper

Keyword(s):

Land Cover ◽

Growing Season ◽

Forest Recovery ◽

Support Vector ◽

Landsat 8 ◽

Coal Surface ◽

Ecosystem Recovery ◽

Surface Mines ◽

Autumn Olive ◽

Native Forests

Surface mining for coal has disturbed large land areas in the Appalachian Mountains. Better information on mined lands' ecosystem recovery status is necessary for effective environmental management in mining-impacted regions. Because record quality varies between state mining agencies and much mining occurred prior to widespread use of geospatial technologies, accurate maps of mining extents, durations, and land cover effects are often not available. Landsat data are well suited to mapping and characterizing land cover and forest recovery on former coal surface mines. Past mine reclamation techniques have often failed to restore premining forest vegetation but natural processes may enable native forests to re-establish on mined areas with time. However, the invasive species autumn olive (Elaeagnus umbellate) is proliferating widely on former coal surface mines, often inhibiting reestablishment of native forests. Autumn olive outcompetes native vegetation because it fixes atmospheric nitrogen and benefits from a longer growing season than native deciduous trees. This longer growing season, along with Landsat 8's high signal to noise ratio, has enabled species-level classification of autumn olive using multitemporal Landsat 8 data at accuracy levels usually only obtainable using higher spatial or spectral resolution sensors. We have used classification and regression tree (CART®) and support vector machine (SVM) to classify five counties in the coal mining region of Virginia for presence and absence of autumn olive. The best model found was a CART® model with 36 nodes which had an overall accuracy of 84% and kappa of 0.68. Autumn olive had conditional kappa of 0.65 and a producers and users accuracy of 86% and 83% respectively. The best SVM model used a second order polynomial kernel and had an overall accuracy of 77%, an overall kappa of 0.54 and a producers and users accuracy of 60% and 90% respectively.

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