Preprints

Filtering by Subject: Forest Sciences

Bridging knowledge gaps with hybrid machine-learning forest ecosystem models (ML-FEMs): inferential simulation of past understory light regimes

Adam Michael Erickson, Craig Nistchke

Published: 2021-10-29
Subjects: Artificial Intelligence and Robotics, Biodiversity, Biogeochemistry, Computer Sciences, Earth Sciences, Ecology and Evolutionary Biology, Forest Sciences, Life Sciences, Physical Sciences and Mathematics, Plant Sciences

Soil moisture is a key limiting factor of plant productivity in boreal and montane regions, producing additional climate feedbacks through evaporation, regeneration, mortality, and respiration. Understory solar irradiation – the primary driver of surface temperature and evaporative demand – remains poorly represented in vegetation models due to a lack of 3-D canopy geometry. Existing models are [...]

Simulated decline of a northern forest due to anthropogenic controls on the regeneration-mortality balance

Adam Michael Erickson, Craig Nistchke, Gordon Stenhouse

Published: 2021-10-29
Subjects: Biodiversity, Biogeochemistry, Earth Sciences, Ecology and Evolutionary Biology, Environmental Sciences, Forest Sciences, Life Sciences, Physical Sciences and Mathematics, Plant Sciences

The population structure of forests is shaped by balancing the opposing forces of regeneration and mortality, each of which influence C turnover rates and are sensitive to climate. Regeneration underlies the migrational potential of forests to climatic change and remains underserved in modeling studies. Our objective was to test the hypothesis that warming may reduce tree regeneration rates while [...]

Emergence of anthropogenic fire regimes in the southern boreal of Canada

Adam Michael Erickson

Published: 2021-10-29
Subjects: Biogeochemistry, Earth Sciences, Ecology and Evolutionary Biology, Environmental Sciences, Forest Sciences, Life Sciences, Plant Sciences

While radiative forcing and thus land surface temperatures have been shown to positively correlate with fire severity, precipitation, and lightning strike frequency, the effects of human activity on fire regimes remain difficult to disentangle from geophysical drivers given co-variation between these factors. Here, I analyze fire regimes in the 1919-2012 period across Canada and compare national [...]

The carbon cycle of southeast Australia during 2019-2020: Drought, fires and subsequent recovery

Brendan Byrne, Junjie Liu, Meemong Lee, et al.

Published: 2021-05-13
Subjects: Atmospheric Sciences, Environmental Monitoring, Environmental Sciences, Forest Sciences, Physical Sciences and Mathematics

2019 was the hottest and driest year on record for southeast Australia leading to bushfires of unprecedented extent. Ecosystem carbon losses due to drought and fire are believed to have been substantial, but have not been well quantified. Here, we utilize space-based measurements of trace gases (TROPOspheric Monitoring Instrument XCO, Orbiting Carbon Observatory 2 XCO2) and up-scaled GPP (FluxSat [...]

Impacts of a regional multi-year insect defoliation event on seasonal runoff ratios and instantaneous streamflow characteristics

Sarah Smith-Tripp, Alden Griffith, Valerie Pasquarella, et al.

Published: 2020-10-26
Subjects: Forest Sciences, Hydrology, Terrestrial and Aquatic Ecology, Water Resource Management

Repeated moderate severity forest disturbances can cause short- and long-term shifts in ecosystem processes. Prior work has found that stand-replacing disturbances (e.g., clear-cutting) increases streamflow in temperate forests, but streamflow responses to repeated moderate severity disturbances are more equivocal. This study examined a moderate disturbance caused by an unexpected population [...]

Transitioning Machine Learning from Theory to Practice in Natural Resources Management

Sheila M. Saia, Natalie G. Nelson, Anders S. Huseth, et al.

Published: 2020-10-22
Subjects: Agriculture, Computer Sciences, Environmental Education, Environmental Sciences, Environmental Studies, Forest Management, Forest Sciences, Natural Resources and Conservation, Natural Resources Management and Policy, Water Resource Management

Advances in sensing and computation have accelerated at unprecedented rates and scales, in turn creating new opportunities for natural resources managers to improve adaptive and predictive management practices by coupling large environmental datasets with machine learning (ML). Yet, to date, ML models often remain inaccessible to managers working outside of academic research. To identify [...]

Range-based intensity normalization of ALS data over forested areas using a sensor tracking method from multiple returns

Jean-Romain Roussel, Jean-François Bourdon, Alexis Achim

Published: 2020-07-10
Subjects: Education, Engineering, Environmental Monitoring, Environmental Sciences, Forest Management, Forest Sciences, Life Sciences, Natural Resources Management and Policy, Other Forestry and Forest Sciences, Physical Sciences and Mathematics

Airborne laser scanning (ALS) point-clouds are used in forest inventory to map properties of the resource. In most cases, only the (x,y,z) coordinates of the point cloud are used to build predictive models of forest structure. Despite being recorded and provided by data suppliers, the intensity values associated with each point are rarely used as an input to such models because raw intensity [...]

Probabilistic soil moisture dynamics of water- and energy-limited ecosystems

Estefanía Muñoz, Andrés Ochoa, Germán Poveda, et al.

Published: 2020-05-17
Subjects: Agriculture, Agronomy and Crop Sciences Life Sciences, Civil and Environmental Engineering, Earth Sciences, Engineering, Environmental Engineering, Environmental Sciences, Forest Sciences, Hydrology, Life Sciences, Physical Sciences and Mathematics, Plant Sciences, Statistical Models, Statistics and Probability

This paper presents an extension of the stochastic ecohydrological model for soil moisture dynamics at a point of Rodriguez-Iturbe et al. (1999) and Laio et al. (2001). In the original model, evapotranspiration is a function of soil moisture and vegetation parameters, so that the model is suitable for water-limited environments. Our extension introduces a dependence on maximum evapotranspiration [...]

Concepts of space, time and scale

Mikko Vastaranta, Ninni Saarinen, Tuomas Yrttimaa, et al.

Published: 2020-04-11
Subjects: Forest Sciences, Geographic Information Sciences, Geography, Life Sciences, Social and Behavioral Sciences

Concepts of space, time and scale as well as their underpinning theories are crucial for understanding geospatial data. Space can be defined as a boundless, three-dimensional (3D) extent in which objects and events occur and have relative position and direction. Space has been considered to be absolute, meaning that it exists permanently and independently regardless of any matter in space. [...]

Fundamental laws and principles in geoinformation science

Mikko Vastaranta, Ninni Saarinen, Tuomas Yrttimaa, et al.

Published: 2020-04-11
Subjects: Forest Sciences, Geographic Information Sciences, Geography, Life Sciences, Social and Behavioral Sciences

Scientific laws are empirical statements, based on repeated experiments or observations, that describe or predict a range of natural phenomena. There are scientific laws and law-like statements also in the field of geoinformation sciences. Based on the Tobler’s first law of geography, “everything is related to everything else, but near things are more related than distant things”. This first law [...]

Individual tree detection and characterization using 3D remote sensing

Mikko Vastaranta, Ninni Saarinen, Tuomas Yrttimaa, et al.

Published: 2020-04-11
Subjects: Forest Sciences, Geographic Information Sciences, Geography, Life Sciences, Remote Sensing, Social and Behavioral Sciences

Here, we will cover individual tree detection and characterization using 3D remote sensing. Simply, it means that point clouds are collected over a forested area using airborne laser scanning (ALS) or created using photogrammetric image interpretation and further used to detect individual trees using different algorithms. After the tree detection, the attributes of interest are predicted for each [...]

Introduction to geoinformation science

Mikko Vastaranta, Ninni Saarinen, Tuomas Yrttimaa, et al.

Published: 2020-04-11
Subjects: Forest Sciences, Geographic Information Sciences, Geography, Life Sciences, Social and Behavioral Sciences

Here, we define a geoinformation system (GIS) as a system, which is designed to capture, store, manipulate, analyze, manage, and present geospatial data. In university education, we study geoinformation science that is the science underlying geographic concepts, applications, and systems. Geoinformation science is dedicated to advancing our understanding of geographic processes and spatial [...]

POSSIBILITIES OF CHANGE DETECTION OF TREE AND FOREST ATTRIBUTES BY COMBINING TERRESTRIAL LASER SCANNING BASED 3D POINT CLOUDS WITH UAV DATA

Ville Luoma, Tuomas Yrttimaa, Ville Kankare, et al.

Published: 2020-04-01
Subjects: Forest Management, Forest Sciences, Geography, Life Sciences, Remote Sensing, Social and Behavioral Sciences

Exact and up-to-date information about forest resources is needed for decision makers when planning the use of forests. Knowledge about changes in forest environment and tree growth is a key factor for example when predicting the effects of climate change and estimating the amount of biomass and sequestered carbon in forests. New technologies, such as unmanned aerial vehicles (UAVs), allow one to [...]

Performance of terrestrial laser scanning to characterize managed Scots pine (Pinus sylvestris L.) stands is dependent on forest structural variation

Tuomas Yrttimaa, Ninni Saarinen, Ville Kankare, et al.

Published: 2020-03-05
Subjects: Forest Sciences, Life Sciences

There is a limited understanding of how forest structure affects the performance of methods based on terrestrial laser scanning (TLS) in characterizing trees and forest environments. We aim to improve this understanding by studying how different forest management activities that shape tree size distributions affect the TLS-based forest characterization accuracy in managed Scots pine (Pinus [...]

Integrating UAV photogrammetry with terrestrial laser scanning to characterize managed forest stands

Tuomas Yrttimaa, Ninni Saarinen, Ville Kankare, et al.

Published: 2020-03-04
Subjects: Forest Sciences, Geography, Life Sciences, Remote Sensing, Social and Behavioral Sciences

Terrestrial laser scanning (TLS) provides detailed three-dimensional representation of the surrounding forest structure. However, due to close-range hemispherical scanning geometry the ability of TLS technique to comprehensively characterize the upper parts of forest canopy is often limited. To overcome challenges in upper canopy characterization, TLS point cloud were complemented with a point [...]

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