Miroslav Honzák

A Methodology for Adaptable and Robust Ecosystem Services Assessment

Ecosystem Services (ES) are an established conceptual framework for attributing value to the benefits that nature provides to humans. As the promise of robust ES-driven management is put to the test, shortcomings in our ability to accurately measure, map, and value ES have surfaced. On the research side, mainstream methods for ES assessment still fall short of addressing the complex, multi-scale biophysical and socioeconomic dynamics inherent in ES provision, flow, and use. On the practitioner side, application of methods remains onerous due to data and model parameterization requirements. Further, it is increasingly clear that the dominant “one model fits all” paradigm is often ill-suited to address the diversity of real-world management situations that exist across the broad spectrum of coupled human-natural systems. This article introduces an integrated ES modeling methodology, named ARIES (ARtificial Intelligence for Ecosystem Services), which aims to introduce improvements on these fronts. To improve conceptual detail and representation of ES dynamics, it adopts a uniform conceptualization of ES that gives equal emphasis to their production, flow and use by society, while keeping model complexity low enough to enable rapid and inexpensive assessment in many contexts and for multiple services. To improve fit to diverse application contexts, the methodology is assisted by model integration technologies that allow assembly of customized models from a growing model base. By using computer learning and reasoning, model structure may be specialized for each application context without requiring costly expertise. In this article we discuss the founding principles of ARIES - both its innovative aspects for ES science and as an example of a new strategy to support more accurate decision making in diverse application contexts.

Mapping the regional extent of tropical forest regeneration stages in the Brazilian Legal Amazon using NOAA AVHRR data.

The study aimed to map several stages of tropical forest regeneration across the Brazilian Legal Amazon using 1.1 km NOAA AVHRR data. Regenerating forest extent was defined using an unsupervised classification of AVHRR channels 1, 2 and 3 and the Global Environment Monitoring Index (GEMI). A method for discriminating four forest regeneration stages was then developed, based on relationships between AVHRR channels 1, 2 and 3 and forest age. This method was applied to AVHRR data to map forests associated with Stages I (early colonization phase, open canopy, < 5 years), II (closed, singlelayered canopy, 5-9 years), III (closed canopy with structural development, 9-20 years) and IV (closed multilayered canopy, > 20 years). The maps provided new regional estimates of regenerating forest for the Legal Amazon and indicated that, over the period 1991 to 1994, approximately 35.8% (157 973 km2) of the total deforested area of 440 186 km2 (estimated for 1992) supported regenerating forest, with 48% of these forests aged at less than 5 years. The study concluded that AVHRR data has an important role in mapping and monitoring tropical forest regeneration. The datasets generated provide valuable input to models of regional carbon flux. For example, Grace et al . (1995a, b) reported net annual CO2 absorption 8.5 2.0 moles m 2 for mature forests in south-west Amazonia suggesting

Forest regeneration on abandoned clearances in central Amazonia

A time-series of Landsat and SPOT sensor data was used to approximate the age of tropical forests regenerating on abandoned agricultural land north of Manaus, Brazil, and to estimate the period of active land use prior to abandonment. Based on field data, two distinct regeneration pathways, dominated by the pioneer genera Cecropia and Vismia, respectively, were described, with the former regenerating on the least intensively used sites. Forests of mixed species composition and lacking numerical dominance by pioneer species were also observed. Transformed Divergence Analysis of Landsat Thematic Mapper (TM) radiance data revealed that forests of varying age and following different regeneration pathways were best discriminated using mid infrared (1.55-1.74 w m) wavelengths. As rates of carbon sequestration by forests vary with age and regeneration pathway, the potential exists for refining spatial estimates of the carbon balance of tropical forests regenerating on abandoned agricultural lands.

Landsat-7 ETM+ as an observatory for land cover: Initial radiometric and geometric comparisons with Landsat-5 Thematic Mapper

Abstract The Landsat-7 ETM+ sensor offers several enhancements over the Landsat-4,5 Thematic Mapper (TM) sensor, including increased spectral information content, improved geodetic accuracy, reduced noise, reliable calibration, the addition of a panchromatic band, and improved spatial resolution of the thermal band. In this paper, we present some initial comparisons between Landsat-5 TM and Landsat-7 ETM+ imagery in order to quantify these improvements. We find that the ETM+ continues the record of TM observations, and, in many respects, substantially improves upon the earlier sensor. Specific improvements include lower spatial noise levels, improved information content, and geodetic accuracy of systematically corrected products to 50–100 m. These improvements are likely to have significant benefits for land-cover mapping and change detection applications.

Food security in a perfect storm: using the ecosystem services framework to increase understanding

Achieving food security in a ‘perfect storm’ scenario is a grand challenge for society. Climate change and an expanding global population act in concert to make global food security even more complex and demanding. As achieving food security and the millennium development goal (MDG) to eradicate hunger influences the attainment of other MDGs, it is imperative that we offer solutions which are complementary and do not oppose one another. Sustainable intensification of agriculture has been proposed as a way to address hunger while also minimizing further environmental impact. However, the desire to raise productivity and yields has historically led to a degraded environment, reduced biodiversity and a reduction in ecosystem services (ES), with the greatest impacts affecting the poor. This paper proposes that the ES framework coupled with a policy response framework, for example Driver-Pressure-State-Impact-Response (DPSIR), can allow food security to be delivered alongside healthy ecosystems, which provide many other valuable services to humankind. Too often, agro-ecosystems have been considered as separate from other natural ecosystems and insufficient attention has been paid to the way in which services can flow to and from the agro-ecosystem to surrounding ecosystems. Highlighting recent research in a large multi-disciplinary project (ASSETS), we illustrate the ES approach to food security using a case study from the Zomba district of Malawi.

Viable Reserve Networks Arise From Individual Landholder Responses To Conservation Incentives

Conservation in densely settled biodiversity hotspots often requires setting up reserve networks that maintain sufficient contiguous habitat to support viable species populations. Because it is difficult to secure landholder compliance with a tightly constrained reserve network design, attention has shifted to voluntary incentive mechanisms, such as purchase of conservation easements by reverse auction or through a fixed-price offer. These mechanisms carry potential advantages of transparency, simplicity, and low cost. However, uncoordinated individual response to these incentives has been assumed incompatible with the conservation goal of viability, which depends on contiguous habitat and biodiversity representation. We model such incentives for southern Bahia in the Brazilian Atlantic Forest, one of the biologically richest and most threatened global biodiversity hotspots. Here, forest cover is spatially autocorrelated and associated with depressed land values, a situation that may be characteristic of long- settled areas with forests fragmented by agriculture. We find that in this situation, a voluntary incentive system can yield a reserve network characterized by large, viable patches of contiguous forest, and representation of subregions with distinct vegetation types and biotic assemblages, without explicit planning for those outcomes.

Characterizing tropical forest regeneration in Cameroon using NOAA AVHRR data

To facilitate estimation of the carbon sink associated with tropical forests in Cameroon, regenerating and mature forests were mapped using an unsupervised classification of AVHRR channels 1, 2 and 3. Stages of regeneration were defined using nonlinear relationships between AVHRR channel 3 radiance and basal area, estimated using data collected from 183 plots (1 ha in size) in an area south-east of the capital, Yaounde. The overall extent and patterns of regenerating forest were comparable to those generated in previous studies. Older stages of regeneration could not, however, be discriminated adequately from mature forest, suggesting that areas of tropical forest disturbance may be underestimated when mapped using AVHRR data. closed tropical forests were regenerating and that their rate of expansion million ha y 1. These regenerating forests accumulate biomass more rapidly

Exploring the Association Between People and Deforestation in Madagascar

An island widely recognized for remarkably high biological diversity, Madagascar continues to experience considerable deforestation. This study explores possible causes of forest loss between 1990 and 2000. Applying a multivariate probit model, the study considers a range of human geographic, physical geographic, and infrastructure data to identify likely reasons for deforestation during the final decade of the twentieth century. Results indicate that protected areas substantially slow forest loss. They also show that access via roads and footpaths were important prerequisites for deforestation during the 1990s. Neither population density nor poverty seemed to be related to forest loss, though data shortcomings may help explain this lack of relationship. The issues that appear to be linked to deforestation in Madagascar are sensitive to policy decisions, suggesting that development strategies can help stem forest loss in this important repository of biological diversity.

Rapid Assessment of Ecosystem Service Co-Benefits of Biodiversity Priority Areas in Madagascar

The importance of ecosystems for supporting human well-being is increasingly recognized by both the conservation and development sectors. Our ability to conserve ecosystems that people rely on is often limited by a lack of spatially explicit data on the location and distribution of ecosystem services (ES), the benefits provided by nature to people. Thus there is a need to map ES to guide conservation investments, to ensure these co-benefits are maintained. To target conservation investments most effectively, ES assessments must be rigorous enough to support conservation planning, rapid enough to respond to decision-making timelines, and often must rely on existing data. We developed a framework for rapid spatial assessment of ES that relies on expert and stakeholder consultation, available data, and spatial analyses in order to rapidly identify sites providing multiple benefits. We applied the framework in Madagascar, a country with globally significant biodiversity and a high level of human dependence on ecosystems. Our objective was to identify the ES co-benefits of biodiversity priority areas in order to guide the investment strategy of a global conservation fund. We assessed key provisioning (fisheries, hunting and non-timber forest products, and water for domestic use, agriculture, and hydropower), regulating (climate mitigation, flood risk reduction and coastal protection), and cultural (nature tourism) ES. We also conducted multi-criteria analyses to identify sites providing multiple benefits. While our approach has limitations, including the reliance on proximity-based indicators for several ES, the results were useful for targeting conservation investments by the Critical Ecosystem Partnership Fund (CEPF). Because our approach relies on available data, standardized methods for linking ES provision to ES use, and expert validation, it has the potential to quickly guide conservation planning and investment decisions in other data-poor regions.

Towards an Operational Forest Monitoring System for Central Africa

Characterizing and mapping land cover and land use change in the rain forests of Central African is a complex process. This complexity is marked by the diversity of land use practices across six different countries (Cameroon, Central African Republic, Democratic Republic of Congo, Equatorial Guinea, Gabon, and Republic of Congo), the lack of full and continuous cloud-free coverage by any single optical remote sensing instrument, and the limited institutional capacity to implement mapping and monitoring activities.