TUESDAY 15 Dec 2009 AGU (SF)
ID# / GC21B-01Location: / 3001 (Moscone West)
Time of Presentation: / Dec 15 8:05 AM - 8:20 AM
Monitoring and Assessment Science to Support Decision-Making by the United Nations Convention to Combat Desertification (UNCCD)
M. Winslow1; M. Akhtar-Schuster2; M. Cherlet3; C. Martius4; S. Sommer3; R. Thomas5; J. Vogt3
1. International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Andhra Pradesh, India.
2. Biocentre Klein Flottbek and Botanical Garden, University of Hamburg, Hamburg, Germany.
3. Institute for Environment and Sustainability-Joint Research Centre, Ispra, Italy.
4. International Center for Agricultural Research in Dry Areas (ICARDA), Aleppo, Syrian Arab Republic.
5. United Nations University International Network on Water, Environment and Health (UNU-INWEH), Hamilton, ON, Canada.
The United Nations Convention to Combat Desertification (UNCCD) is a global treaty that emerged from the Rio Earth Summit and formally took force in 1996. It has now been ratified by 193 countries (known as Parties to the Convention). Yet the UNCCD has gained only modest support from donors, largely due to questions about the science base underlying its target issue (desertification) resulting in ambiguous definitions and quantification of the problem.
The UNCCD recognizes the need to reform itself and commissioned a scientific conference in Buenos Aires, Argentina in September 2009 to discuss ways to improve the scientific underpinning of monitoring and assessment (M&A) of desertification, land degradation and drought (DLDD). Previous attempts by the UNCCD on M&A focused largely on a search for a common, simple, universal set of indicators that could be reported by country Parties to the Convention Secretariat, which would collate them into a global report. However experience found that no single set of indicators is satisfactory to all countries, because DLDD depends strongly on the local environmental and human/social context.
Three preparatory Working Groups analyzed the issue of DLDD M&A and recommended the following.
Parties should recognize that M&A methods must integrate human-environment parameters to capture the complexity of DLDD phenomena as defined in the Convention’s text. Traditional tendencies had been to isolate biophysical from social and economic parameters, leading to unrealistic conclusions.
Parties should take advantage of a much wider range of analytical techniques than just the coarse-scale indicators that had been their main focus to date. Powerful but underutilized techniques include integrated assessment models, remote sensing, geographic information systems and mapping, participatory stakeholder assessment, hierarchical aggregation of related data, knowledge management and many others. Multiple methods could provide validation checks on each other from complementary perspectives.
M&A should also collect information to support benefit/cost analysis because decision-makers require such information in weighing priorities for public investment. Such information should include non-monetary as well as monetary values. Ecosystem services should also be valued, even if they are currently available free to land users.
Parties should recognize the potential utility of knowledge management (KM) methods to overcome knowledge barriers that currently inhibit M&A collaboration between institutions, scientific disciplines, scale levels, formal/informal sectors, development sectors (e.g. water, health, food, infrastructure etc.), and between land users, scientists and policy makers. Improved KM could also build human and institutional capacities, resulting in improved M&A in the future.
http://dsd-consortium.jrc.ec.europa.eu/php/index.php?action=view&id=150
Contact Information
Mark Winslow, Haimhausen, Germany, 85778, click here to send an email
UN Convention to Combat desertification. GOALS:
1. improve living conditions
2. improve ecosystems
3. mitigate climate change & biodiversity losses
Very focused on impacts – want to show their achievements – should also focus on scale, dynamics
European framework from mid-90s on cause-effect understandinf: drivers, pressures, etc – even that hasn’t made it into understanding here.
Dryland Development Paradigm:
1. Coupled Human-Environment systems
2. focus on slow variables …
3. …
UNCCD feels a little overwhelmed with math, but they need more\\Practical attempt to break through thes knowledge barrier: LADA
LADA – Land degradation assessment in drylands. GOALS:
1. develop tools and methods to monitor & asses
2. Carry out …
3. …
Need sustainable land managemenet. WOCAT – World Overview of … (talking too fast)
Ex: Tunisia created detailed map of its land use…
Desertification flow chart – very nice – source: Millenium Ecosystem Assessment (two swirls)
UNCCD has no Science Interface (e.g. IPCC) and no monitoring and assessment framework
· needs to include cause-effect understanding
· needs to include scale dynamics
· needs attention to comabing land degradation through sustainable land management
· needs to improve knowledge flows, horizontally and vertically
· Alap Aman
www.drylandscience.org and www.unccd.int
Location: / 3001 (Moscone West)
Time of Presentation: / Dec 15 8:20 AM - 8:35 AM
Determining Land System Sustainability through a Land Architecture Approach: Example of Southern Yucatán (Invited)
B. L. Turner II1
1. Arizona State University, Tempe, AZ, United States.
Sustainable land systems involve an array of tradeoffs, not only among ecosystem services, but between those services and human outcomes. These tradeoffs are affected by the architecture of the land system—the kind, size, pattern, and distribution of land uses and covers. Working towards a model capable of handling a full array of ecosystem services and human outcomes, the concept of land architecture is illustrated through a simplified land system in the seasonal tropical forests of the southern Yucatán where sustainability is sought through the competing goals of forest conservation-preservation and agricultural development, both cultivation and ranching. Land architecture and tradeoff impacts are compared between two communities emphasizing, respectfully, forest conservation-preservation and agriculture. The role of spatial scale is also illustrated. Vulnerability and resilience assessments of land systems should be enhanced through a land architecture approach.
Contact Information
Billie L. Turner II, Tempe, Arizona, USA, 85287-5302, click here to send an email
Three Pivots to Sustainability Science
1.
2. Natural capital expanded to include all ecosystem services
3. Tradeoffs (physical and economic) among ecosystem services and between those sersvices and human outcomes
Absent tradeoff assessment, cannot determine vulnerabiolity and resilience of any coupled system
Design or architecture of land system is critical but overlooked facet of tradeoffs
Simple example fro southern yucatan: govt has put in a lot of farmers on small connunal farmers – farmers are not cutting stocks but saving biodiversity
Land Unit #1 (in the middle) – wants to err on the side of biodiversity – farm income low – look at ecosystem services – canopy captures phosphorus, stores carbon, emits water vapor
Land Unit #2 (adjacent) errs on the side of family farm income – high forest disturbance (mostly secondary forest) low biodiversity (less habitat) – low P capture, less evapotranspiration – increased use of pesticides and fertilizers – investment in pasture
Note – Land Unit #1 is embedded in others. Bio-goals of Land Unit #1 likely not met, given disturbances of other land units favoring farming over forest preservation.
What’s needed:
· real world land architecture (LA) -> multiple land classes
· multiple ecosystem tradeoffs
· multiple human outcomes
· combine in spatially explicit & dynamic models
· test robustness of modeling outcomes
Location: / 3001 (Moscone West)
Time of Presentation: / Dec 15 8:35 AM - 8:50 AM
Implications of a New Global Picture of Land Degradation (Invited)
L. Olsson1; D. Dent1
1. LUCSUS, Lund University, Lund, Sweden.
Effective responses to desertification have always been hampered by a lack of a scientific understanding and reliable data on the extent and severity of land degradation. We also argue that the poor scientific understanding of desertification is partly a consequence of the lack of reliable data. Policy development has to a large extent relied upon data from the 1990 GLASOD assessment that was compiled from expert judgements. This is a map of perceptions, not measurements, that doesn't stand scrutiny and lent itself to selective interpretations. Based on the GLASOD assessment, land degradation in arid and semi-arid regions have been emphasised over other regions as hotspots of land degradation.
A recent analysis of consistent, remotely-sensed data and climatic observations, using clearly-defined methods, makes allowance for droughts and global warming. It indicates that 24 per cent of land has suffered declining net primary productivity over the last 25 years; this area is home to a quarter of the world's people. When adjusted for climatic variations, the loss of primary productivity is interpreted as land degradation. In contrast to received wisdom, dry lands don't feature strongly. Forests and croplands are most affected by land degradation and protected areas fare no better than anywhere else.
Unprecedented land use change is being driven not only by local processes but also by external pressures related to burgeoning population, economic & technology developments and globalisation; and unsustainable land use is causing land degradation. This suggests a need for a policy shift from desertification in dry lands to land degradation globally, and from environmental protection to developmental initiatives.
The paper will discuss potential responses to land degradation that are informed by the new insights into the extent and severity of land degradation globally.
Contact Information
Lennart Olsson, Lund, Sweden, 22100, click here to send an email
MISSING
Location: / 3001 (Moscone West)
Time of Presentation: / Dec 15 8:50 AM - 9:05 AM
Coupled Human-Ecological Dynamics and Land Degradation in Global Drylands-A modelling approach (Invited)
U. Helldén1
1. Physical Geography and Ecosystems Analysis, Lund university, Lund, Scania, Sweden.
Drylands comprise one-third of the Earth’s land area. They pose research, management, and policy challenges impacting the livelihoods of 2.5 billion people. Desertification is said to affect some 10-20% of the drylands and is assumed to expand with climate change and population growth. Recent paradigms stress the importance of understanding linkages between human-ecological (H-E) systems in order to achieve sustainable management policies. Understanding coupled H-E systems is difficult at local levels. It represents an even greater challenge at regional scales to guide priorities and policy decisions at national and international levels. System dynamic modelling may help facilitating the probblem.
Desertification and land degradation are often modelled and mathematically defined in terms of soil erosion. The soil erosion process is usually described as a function of vegetation ground cover, rainfall characteristics, topography, soil characteristics and land management.
On-going research based on system dynamic modelling, focussing on elucidating the inherent complexity of H-E systems across multiple scales, enables an assessment of the relative roles that climate, policy, management, land condition, vulnerability and human adaptation may play in desertification and dryland development.
An early approach (1995) to study desertification through an H-E coupled model considered desertification to be stress beyond resilience, i.e. irreversible, using a predator-prey system approach. As most predator-prey models, it was based on two linked differential equations describing the evolution of both a human population (predator) and natural resources (prey) in terms of gains, losses and interaction.
A recent effort used a model approach to assess desertification risk through system stability condition analysis. It is based on the assumption that soil erosion and the soil sub-system play an overriding final role in the desertification processes. It is stressing the role and importance of economic units, production costs, investments and profitability in natural resources exploitation.
This paper presents a recently developed coupled H-E system dynamic model to simulate and analyse desertification syndromes. The model integrates socio-economic drivers with bio-physical drivers of biomass production and land degradation. It is based on the UN and GEF definitions of desertification. It analyses and simulates dryland dynamics and desertification through differential equations and numeric simulation.
The model relates population pressure and dynamics over time to the growth and availability of biomass resources. The human population stock is described as a function of growth rate, death rate and resources dependent migration of people. The relative growth rate of the stock of resources is modelled as a function of climate and human exploitation pressure affecting the removal of resources, soil erosion and water availability over time.
The model is applied, demonstrated and discussed for combinations of time series of simulated and observed data referring to “desertification” cases in the Sahel, the Mediterranean and Inner Mongolia, China. The results are compared to existing land and population related statistics and remotely sensed observations opening for land system “carrying capacity” analysis and discussions.
Contact Information
Ulf Helldén, Lund, Sweden, S-223 62, click here to send an email
8:00 AM-10:00 AM, 301 (Moscone South)
SH21C. Solar Flares I
Location: / 301 (Moscone South)
Time of Presentation: / Dec 15 9:15 AM - 9:30 AM
Using subsurface helicity measurements to predict flare occurrence
A. A. Reinard1, 2; J. Henthorn3; R. Komm4; F. Hill4
1. NOAA/SWPC, Boulder, CO, United States.
2. University of Colorado, Boulder, CO, United States.
3. Ohio University, Athens, OH, United States.
4. National Solar Observatory, Tuscon, NM, United States.
Solar flares are responsible for a number of hazardous effects including disabling high-frequency radio communications, interfering with GPS measurements, and disrupting satellites. Forecasting flare occurrence is very difficult, giving little advanced notice of these events. One possible means for predicting flare occurrence lies in helioseismology, i.e. analysis of the region below the active region for signs of an impending flare. Time series helioseismic data collected by the Global Oscillation Network Group (GONG) have been analyzed for a subset of active regions that produce large flares and a subset with very high magnetic field strength that produce no flares. A predictive parameter has been developed and analyzed using discriminant analysis as well as traditional forecasting tools such as the Heidke skill score. Preliminary results indicate this parameter predicts flare occurrence with a high success rate.
Contact Information
Alysha A. Reinard, Boulder, Colorado, USA, 80305-0000, click here to send an email
Drop in helicity signals flare? (over up to 6 days) NHGV = nmormalized helicity gradient variance
Clear separation between C, M, and X-class flares. Separation increases as time to flare decreases
(If you predict there won’t be a flare, you can usually be right. NHGV ~ 1)