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8. Monitoring forest cover and land use change in the Congo Basin under IPCC climate change scenarios.

Author

Yuh, Yisa Ginath, N'Goran, Kouamé Paul, Kross, Angela, Heurich, Marco, Matthews, H. Damon, and Turner, Sarah E.

Abstract

The Congo Basin tropical forests are home to many endemic and endangered species, and a global hotspot for forest fragmentation and loss. Yet, little has been done to document the region's rapid deforestation, assess its effects and consequences, or project future forest cover loss to aid in effective planning. Here we applied the Random Forest (RF) supervised classification algorithm in Google Earth Engine (GEE) to map and quantify decadal changes in forest cover and land use (LCLU) in the Congo Basin between 1990 and 2020. We cross-validated our LCLU maps with existing global land cover products, and projected our validated results to 2050 under three climate change scenarios, using the Multiperceptron Artificial Neural Network and Markov chain algorithms of the Idrissi Land Change modeller from TerrSet. We found that, over 5.2% (215,938 km2), 1.2% (50,046 km2), and a 2.1% (86,658 km2) of dense forest cover were lost in the Congo Basin between 1990–2000, 2000–2010, and 2010–2020, totaling approximately 8.5% (352,642 km2) loss estimated between 1990–2020. For the period 2020–2050, we estimated a projected 3.7–4.0% (174,860–204,161 km2) loss in dense forest cover under all three climate change scenarios (i.e., 174,860 km2 loss projected for SSP1-2.6, 199,608 km2 for SSP2-4.5, and 204,161 km2 for SSP5-8.5), suggesting that approximately 12.3–12.6% (527,502 km2–556,803 km2) of dense forest cover could be lost over a 60-year period (1990–2050). Our study represents a novel application of spatial modeling tools and Machine Learning algorithms for assessing long-term deforestation and forest degradation within the Congo Basin, under human population growth and IPCC climate change scenarios. We provide spatial and quantitative results required for supporting long-term deforestation and forest degradation monitoring within Congo Basin countries, especially under the United Nations Framework Convention on Climate Change (UNFCCC) REDD+ (Reduce Emissions from Deforestation and Forest Degradation) program. [ABSTRACT FROM AUTHOR]

Published
2024
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18. Phenology and its role in carbon dioxide exchange processes in northern peatlands

Author

Kross, Angela S.E., Roulet, Nigel T., Moore, Tim R., Lafleur, Peter M., Humphreys, Elyn R., Seaquist, Jonathan W., Flanagan, Larry B., Aurela, Mike, Kross, Angela S.E., Roulet, Nigel T., Moore, Tim R., Lafleur, Peter M., Humphreys, Elyn R., Seaquist, Jonathan W., Flanagan, Larry B., and Aurela, Mike

Abstract

Ecosystem phenology plays an important role in carbon exchange processes and can be derived from continuous records of carbon dioxide (CO2) exchange data. In this study we examined the potential use of phenological indices for characterizing cumulative annual CO2 exchange in four contrasting northern peatland ecosystems. We used the approach of Jonsson and Eklundh (2004) to derive a set of phenological indices based on the daily time series of gross primary production (GPP), ecosystem respiration (Re), and net ecosystem production (NEP) measured in the four peatland sites. The main objectives of this study were (a) to examine the variation in phenological indices across sites and (b) to determine the relationships among phenological indices, environmental conditions, and cumulative annual CO2 exchange. The phenological index used to define the “start of the growing season” showed good potential for differentiation among sites based on their average annual site GPP. Sites with earlier growing seasons had the highest average annual site GPP. The “peak CO2 exchange rate” phenological index performed best in reflecting variations among sites and for estimating annual values of GPP, Re, and NEP (Pearson correlation coefficients ranged between 0.77 and 0.99, p<0.05forall.). The phenological indices and annual GPP, Re, and NEP were sensitive to winter (January–March) and summer (July–September) temperature and precipitation, but correlations, though significant, were weak.

Published
2014

20. Einfluss des Vorwissens auf Intensität und Qualität des Selbsterklärens beim Lernen mit biologischen Beispielaufgaben

Author

Kroß, Angela and Lind, Gunter

Subjects
School, Schule, Erziehung, Schul- und Bildungswesen, Lehrmethode, Schulpädagogik, Pupil, Lernen, 370 Erziehung, Schul- und Bildungswesen, Wissen, Pupils, Education, Knowledge, ddc:370, Teaching method, Schüler, Learning, Individualized instruction, Male student, Individualisierender Unterricht, Merkmal, 370 Education, Pädagogischer Transfer, Student
Abstract

Unterrichtswissenschaft 29 (2001) 1, S. 5-25, Die Elaborationsprozesse von Experten beim Lernen mit biologischen Beispielaufgaben stehen im Mittelpunkt der Studie. Es wurde das Selbsterklären von insgesamt 28 lernerfahrenen Schülern untersucht, die aufgrund ihrer unterschiedlichen Lerngeschichten teils über ein sehr hohes und teils über ein sehr geringes Vorwissen in der untersuchten Domäne verfügten. Das unterschiedliche Vorwissen wirkte sich in unterschiedlichen Elaborationsprofilen aus, die auf zwei Ebenen nachgewiesen werden konnten: auf der Ebene der beim Selbsterklären benutzten Fachbegriffe und auf der Ebene der Selbsterklärungsstatements, die nach der Art der beim Selbsterklären eingesetzten Inferenzen klassifiziert wurden. Es konnte gezeigt werden, dass Selbsterklären mit hohem Lernerfolg durch eine aktive Lernhaltung und den Einsatz umfangreichen Vorwissens gekennzeichnet ist. Erfolgreiche Selbsterklärer versuchen die Beispielaufgaben antizipierend zu lösen und nehmen die Beispiele zum Anlass für weiterführende Überlegungen. Wenn das entsprechende Vorwissen nicht zur Verfügung steht, sind der Elaboration engere Grenzen gesetzt und der Lernerfolg fällt dementsprechend geringer aus. In Bezug auf den Gebrauch der Fachsprache nutzen erfolgreiche Lerner abstrakte biologische Fachbegriffe in ihren Statements, die weniger erfolgreichen dagegen eher Begriffe aus der Alltagssprache. (ZPID)

Published
2001
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38. Evolving Mental Models of Electric Circuits

Author

Steinberg, Melvin S., Clement, John J., Behrendt, Helga, editor, Dahncke, Helmut, editor, Duit, Reinders, editor, Gräber, Wolfgang, editor, Komorek, Michael, editor, Kross, Angela, editor, and Reiska, Priit, editor

Published
2001
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40. Concept Mapping as a Tool for Research in Science Education

Author

Fischler, Helmut, Peuckert, Jochen, Dahncke, Helmut, Behrendt, Helga, Reiska, Priit, Pushkin, David B., Bandiera, Milena, Vicentini, Matilde, Fischer, Hans E., Hucke, Lorenz, Gerull, Kristin, Frost, Jenny, Behrendt, Helga, editor, Dahncke, Helmut, editor, Duit, Reinders, editor, Gräber, Wolfgang, editor, Komorek, Michael, editor, Kross, Angela, editor, and Reiska, Priit, editor

Published
2001
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43. Rhetoric and Science Education

Author

Martins, Isabel, Mortimer, Eduardo, Osborne, Jonathan, Tsatsarelis, Charalampos, Aleixandre, Maria Pilar Jiménez, Behrendt, Helga, editor, Dahncke, Helmut, editor, Duit, Reinders, editor, Gräber, Wolfgang, editor, Komorek, Michael, editor, Kross, Angela, editor, and Reiska, Priit, editor

Published
2001
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