Joaquim Alonso

Can we predict habitat quality from space? A multi-indicator assessment based on an automated knowledge-driven system

Abstract There is an increasing need of effective monitoring systems for habitat quality assessment. Methods based on remote sensing (RS) features, such as vegetation indices, have been proposed as promising approaches, complementing methods based on categorical data to support decision making. Here, we evaluate the ability of Earth observation (EO) data, based on a new automated, knowledge-driven system, to predict several indicators for oak woodland habitat quality in a Portuguese Natura 2000 site. We collected in-field data on five habitat quality indicators in vegetation plots from woodland habitats of a landscape undergoing agricultural abandonment. Forty-three predictors were calculated, and a multi-model inference framework was applied to evaluate the predictive strength of each data set for the several quality indicators. Three indicators were mainly explained by predictors related to landscape and neighbourhood structure. Overall, competing models based on the products of the automated knowledge-driven system had the best performance to explain quality indicators, compared to models based on manually classified land cover data. The system outputs in terms of both land cover classes and spectral/landscape indices were considered in the study, which highlights the advantages of combining EO data with RS techniques and improved modelling based on sound ecological hypotheses. Our findings strongly suggest that some features of habitat quality, such as structure and habitat composition, can be effectively monitored from EO data combined with in-field campaigns as part of an integrative monitoring framework for habitat status assessment.

Evaluating the fitness for use of spatial data sets to promote quality in ecological assessment and monitoring

This article proposes and illustrates a practical methodological framework to evaluate the fitness for use of spatial data sets for environmental and ecological applications, focusing on user requirements for specified application contexts. The methodology is based on the use of metadata to analyze similarity between the data characteristics and the user’s needs or expectations for several quality indicators. Additionally, the concept of ‘critical factors’ is introduced in this framework, allowing users to define which quality indicators have greater importance given their own requirements or expectations and the specified application contexts. The proposed methodology further allows integrating and interconnecting the spatial data quality (SDQ) evaluation methodology with metadata geoportals in WebGIS platforms, facilitating its operation by users from non-spatial disciplines and with often limited expertise on this subject. Examples of the evaluation of fitness for use for specific application contexts within the project BIO_SOS (‘Biodiversity Multi-SOurce Monitoring System: From Space To Species’ FP7 project) are presented. By providing a prompt and straightforward evaluation tool, the proposed methodology can encourage the implementation of SDQ evaluation routines in ecological assessment and monitoring programs, promoting a more adequate use of geospatial data and ultimately contributing to well-supported policy and management decisions.

Cost‐effective monitoring of biological invasions under global change: a model‐based framework

1. Ecological monitoring programmes are designed to detect and measure changes in biodiversity and ecosystems. In the case of biological invasions, they can contribute to anticipating risks and adaptively managing invaders. However, monitoring is often expensive because large amounts of data might be needed to draw inferences. Thus, careful planning is required to ensure that monitoring goals are realistically achieved. 2. Species distribution models (SDMs) can provide estimates of suitable areas to invasion. Predictions from these models can be applied as inputs in optimization strategies seeking to identify the optimal extent of the networks of areas required for monitoring risk of invasion under current and future environmental conditions. A hierarchical framework is proposed herein that combines SDMs, scenario analysis and cost analyses to improve invasion assessments at regional and local scales. We illustrate the framework with Acacia dealbata Link. (Silver-wattle) in northern Portugal. The framework is general and applicable to any species. 3. We defined two types of monitoring networks focusing either on the regional-scale management of an invasion, or management focus within and around protected areas. For each one of these two schemes, we designed a hierarchical framework of spatial prioritization using different information layers (e.g. SDMs, habitat connectivity, protected areas). We compared the performance of each monitoring scheme against 100 randomly generated models. 4. In our case study, we found that protected areas will be increasingly exposed to invasion by A. dealbata due to climate change. Moreover, connectivity between suitable areas for A. dealbata is predicted to increase. Monitoring networks that we identify were more effective in detecting new invasions and less costly to management than randomly generated models. The most cost-efficient monitoring schemes require 18% less effort than the average networks across all of the 100 tested options. 5. Synthesis and applications. The proposed framework achieves cost-effective monitoring networks, enabling the interactive exploration of different solutions and the combination of quantitative information on network performance with orientations that are rarely incorporated in a decision support system. The framework brings invasion monitoring closer to European legislation and management needs while ensuring adaptability under rapid climate and environmental change.

Analysing carbon sequestration and storage dynamics in a changing mountain landscape in Portugal: insights for management and planning

ABSTRACT We assessed the effects of landscape change on the climate regulation ecosystem service in a mountain river basin of Portugal, through the quantification, valuation and mapping of carbon sequestration and storage. The analyses were based on land use and land cover (LULC) changes that took place between 1990 and 2006 and on expected changes defined by three LULC change scenarios for 2020. We used the Integrated Valuation of Ecosystem Services and Tradeoffs model for scenario building and carbon assessment and valuation, and several modelling tools to assess past, current and future carbon in four different pools. Soil organic carbon data was obtained through an extensive sampling scheme across the entire study area. Recent (1990–2006) and expected landscape changes (2006–2020) affected considerably carbon sequestration and storage. Observed landscape changes generally promoted carbon sequestration and storage, and had a positive effect on the climate regulation ecosystem service, both biophysically and economically. Expected LULC changes further extend the capability of the landscape to increase carbon sequestration and storage in the near future. The carbon sequestered and stored in vegetation and soil contributes to avoid socio-economic damages from climate change, while increasing the economic value of particular LULC classes and the whole landscape. These results are essential to inform land planning, especially on how, where and when changes in landscapes may affect the provision of the climate regulation ecosystem service. EDITED BY Sandra Luque

Trade-offs and Synergies Between Provisioning and Regulating Ecosystem Services in a Mountain Area in Portugal Affected by Landscape Change

This study explored the effects of landscape change on the provision of ecosystem services in a mountain area in northern Portugal, in particular the trade-offs and synergies between services in 2 categories: provisioning and regulating. Services were assessed for 1990 and 2006 and projected for 2020 under 3 scenarios, both biophysically and economically, based on modeling and published and unpublished statistics. We found that landscape changes in the 16-year period under study increased the total supply of ecosystem services, measured both biophysically and monetarily, but that agriculture production dropped dramatically. Both regulating and provisioning services increased in value, but only regulating services increased in biophysical units. Projections under 2 of our 3 scenarios indicated that both types of ecosystem services will continue to increase in both amount and monetary value and will function in synergy, whereas the third scenario predicted a decrease in services and trade-offs between the 2 categories. Because land use has a major impact on ecosystem service supply, an understanding of the changes and trade-offs described in this article can support planning and management, in particular in mountain areas and other regions with limited alternatives for income generation. Our findings suggest that regional development plans should include incentives to maximize regulating and provisioning ecosystem services.

A spatially explicit methodology for a priori estimation of field survey effort in environmental observation networks

When establishing environmental monitoring programmes, it crucial to make reliable cost estimates, especially where a field survey is involved. This paper presents a methodology for creating a spatial measure of a field survey effort (SE). A set of relevant variables affecting a SE (e.g. areas with rough terrain, or distant from the main road network) was classified using fuzzy sets and then combined to produce spatially explicit effort indicators, which were integrated to a single measure using an analytic hierarchy process (AHP). To evaluate this approach and identify the limits for its application, three spatially nested case studies were used to test the spatial expression of SE and the scalable capacity of the method itself. The presented methodology could cope with variations in the scale and data resolution, retrieving a coherent estimate of SE across the different case studies. The presented methodology is therefore useful for (i) testing the network designs for sampling bias related to SE, (ii) comparing alternative sampling designs, (iii) assessing the sampling costs and (iv) supporting the human and logistical resource management.

Risco de cheia e inundação: exposição na área ribeirinha de Ponte de Lima

The hydrological regime modeling, flood risk assessment and flooded areas mapping become essential in local and regional planning, as well as in technical and political action-decision making. This study aims to examine the functioning of the river Lima basin, the historical incidence of flooding in the historic town of Ponte de Lima and the potential impacts, vulnerabilityand exposure on the human and natural environment as well as human adaptation to floods patterns.

GIS based land use planning and watershed monitoring as tools for sustainable development

The development of GIS based methodologies supports a program for monitoring the territorial dynamics that are occurring in the Estoraos rural watershed (NW Portugal). GIS integrates spatial databases from different research and development projects, with the purpose of understanding: (i) the relationships between land use processes and changes, and environmental management policies; (ii) the extent of environmental impacts due to forest fire as well as extending and intensifying agriculture; and (iii) the influences of natural conditions and human activities on water quality and ecosystem sustainability. The diversity of natural conditions and population dynamics, the (de)forestation, the expansion, density and typology of road networks, the processes of urbanization in the flood plain, and the rising turistic search from external actors, fundament the importance of a GIS based watershed monitoring program. These conditions and processes increase watershed management complexity, namely at a protected wetland in the bottom valley (regional protected landscape, site PTCON00020 of Natura Network 2000, and international RAMSAR site 1613) related to the structure of the landscape, and the quantity and quality of the water resources and the associated biodiversity. The challenges of sustainable land use and the growing quantity and quality of the available spatial databases, allow greater modelling capacity and data accessibility, facilitating public participation, and also aiding and better guiding political and technical actions.

Spatial Multicriteria GIS-Based Analysis to Anaerobic Biogas Plant Location for Dairy Waste and Wastewater Treatment and Energy Recovery (Barcelos, NW Portugal)

Intensification, concentration and specialization of dairy cow farms originate many activity by-products, such as wastewater and slurry which implies treatment costs, reduce environmental quality and promote social conflicts between the urban and rural population. These (by)products present a high potential for energy recovery from biogas produced in anaerobic digestion processes, thus contributing to sustainable development. This study is focused on the development of a GIS-based spatial support decision system that supports Multicriteria Analysis and Weighted Hierarchical Analysis (AHP) models aiming to identify site locations with appropriate conditions for the implementation of biogas production units, using waste and wastewater produced by the dairy cow farms in Barcelos municipality (NW Portugal). This spatially explicit model considers environmental, social and economic factors, as well as, legal location constraints tested with a consistent sensitivity analysis of the modelling processes and results. The results indicate sites with appropriate conditions for the location of biogas production units, considering the minimal distance to the dairy cow farms, electric and road networks, in higher areas with forest land cover and maximizing the distance from the urban spaces, as well as, from the river/ground water surfaces and agricultural/ecological reserves. In the next studies it´s relevant to explore biogas units dimensioning concerns, explore other complementary biomass sources in anaerobic (co)digestion solutions and expand collected spatial data to spatial decision support system during future biogas units operation phase.

An Integrated Approach for Efficient Energy Recovery Production from Livestock and Agro-Industrial Wastes

The supply and food safety needs of the growing population, particularly in (peri) urban areas, promote the intensification, concentration, and specialization of human, agricultural, livestock, and agro-industrial activities. As a result, important quantities of waste and wastewater, with significant organic and nutrient loads, are generated and need to be managed properly in order to protect the soil quality and fertility, as well as to prevent water and air pollution. Among the models, processes, treatment, and recovery technologies, anaerobic digestion can be highlighted due to the production of biogas, a renewable energy source.