Artur Gil

The harlequin ladybird, Harmonia axyridis: global perspectives on invasion history and ecology

The harlequin ladybird, Harmonia axyridis (Pallas) (Coleoptera: Coccinellidae), is native to Asia but has been intentionally introduced to many countries as a biological control agent of pest insects. In numerous countries, however, it has been introduced unintentionally. The dramatic spread of H. axyridis within many countries has been met with considerable trepidation. It is a generalist top predator, able to thrive in many habitats and across wide climatic conditions. It poses a threat to biodiversity, particularly aphidophagous insects, through competition and predation, and in many countries adverse effects have been reported on other species, particularly coccinellids. However, the patterns are not consistent around the world and seem to be affected by many factors including landscape and climate. Research on H. axyridis has provided detailed insights into invasion biology from broad patterns and processes to approaches in surveillance and monitoring. An impressive number of studies on this alien species have provided mechanistic evidence alongside models explaining large-scale patterns and processes. The involvement of citizens in monitoring this species in a number of countries around the world is inspiring and has provided data on scales that would be otherwise unachievable. Harmonia axyridis has successfully been used as a model invasive alien species and has been the inspiration for global collaborations at various scales. There is considerable scope to expand the research and associated collaborations, particularly to increase the breadth of parallel studies conducted in the native and invaded regions. Indeed a qualitative comparison of biological traits across the native and invaded range suggests that there are differences which ultimately could influence the population dynamics of this invader. Here we provide an overview of the invasion history and ecology of H. axyridis globally with consideration of future research perspectives. We reflect broadly on the contributions of such research to our understanding of invasion biology while also informing policy and people.

Remote sensing to map influence of light pollution on Cory’s shearwater in São Miguel Island, Azores Archipelago

Global economic and population growth increase the extent and intensity of artificial night lighting. From an ecological perspective, this is light pollution, which causes changes in reproductive physiology, migration and foraging of many species and ultimately leads to loss of biodiversity. Some seabirds are intimately linked with the light features of their environments because they are nocturnally active. We report light-induced groundings of Cory’s shearwater (Calonectris diomedea) during a 2-year study (2008 and 2009) in São Miguel Island, in the Azores archipelago, and investigate the spatial correlation of locations of grounded birds with an annual composite of remotely sensed stable lights. Results indicate that 16.7% of fledglings are attracted to lights. The exposure of shearwater colonies in the study area to artificial night lighting is low overall. Four colonies account for 87% of the grounded birds. The distance each bird was found from the closest colony was best explained by the ratio of the satellite-measured light levels at the grounding spot to the light levels at the assigned colony of origin. These results demonstrate that satellite-observed nighttime lights are sufficient to assess risk to marine birds at the scale of oceanic islands and indicate their utility for monitoring the effectiveness of programs to manage lighting to reduce risk for these species and conducting global assessments of species vulnerability. To minimize the impact on Cory’s shearwater and other marine birds, we recommend measures such as reduction and control of lighting intensity near colony locations, while continuing and re-enforcing rescue campaigns.

Mapping invasive woody plants in Azores Protected Areas by using very high-resolution multispectral imagery

Abstract We assessed the effectiveness of very high spatial resolution IKONOS imagery for mapping a top invasive woody plant, Pittosporum undulatum, in a Protected Area in S.Miguel Island. We developed a segmentation-based classification scheme. A strong separability between most important land cover classes and a high accuracy in supervised classification maps was achieved. Overall separability improved significantly after the training data depuration process. Support Vector Machine and Maximum Likelihoods supervised classifiers showed a strong agreement and a good accuracy at land-cover class level, especially with P. undulatum. This approach was confirmed as a cost-effective method to map woody plant invaders in Azores Protected Areas.

Linking GMES Space Component to the development of land policies in Outermost Regions - the Azores (Portugal) case-study

Abstract The aim of this study is to assess the potential effectiveness of GMES Space Component Sentinel Missions for land-based environmental policy support in the Azores Autonomous Region (Portugal). Sixteen different types of legal and spatial instruments are currently being applied in this region. Most of them require detailed and accurate Land-use/Land-cover cartography in order to deliver reliable outputs at municipal, island and archipelagic scales. Sentinel-2 Mission products can fulfill these requirements in a cost-effective way. A Spatial Data Infrastructure-based Regional GMES framework is proposed in order to process, assess, validate and integrate this GMES data into the decision support system of Azorean regional land policies.

Invasive Alien Plants in the Azorean Protected Areas: Invasion Status and Mitigation Actions

This chapter addresses plant invasions in the protected areas of the Azores (Northern Atlantic), whose flora encompasses a considerable proportion of alien species (about 70 %). The chapter includes (i) a general characterization of the Azores, with particular reference to their Island Natural Parks covering 24 % of the inland surface; (ii) an assessment of the plant invasion status of the Island Natural Parks (based on distribution data and expert evaluation of potential impacts and possibility of control of invasive alien plants); and (iii) a report about on-going and recent management initiatives embracing the control of invasive alien plants. The results show that the Island Natural Parks of Santa Maria Island is potentially the most threatened by invasive alien plants, followed in decreasing order by the Island Natural Parks of the islands of Graciosa, Sao Jorge, Corvo, Faial, Sao Miguel, Terceira, Flores and Pico. Some of the most threatening species are highlighted. Due to the innovative assessment methodology, the results do not fully corroborate previous studies, showing that just species listing may not provide a full understanding of the potential effects of invasive alien plants on native biodiversity, thus bringing new insights that may assist management initiatives. Several invasive alien plants management projects run by the Azorean Government and the Portuguese Society for the Study of Birds are described, with reference to those supported by the LIFE programme and PRECEFIAS (an Azorean project devoted to control of invasive alien plants in protected areas). Finally, a holistic discussion is provided stressing strengths and weaknesses of all topics covered in the chapter so that more effective invasive alien plant management strategies can be achieved in the future.

Assessing the effectiveness of RapidEye multispectral imagery for vegetation mapping in Madeira Island (Portugal)

Abstract Madeira Island is a biodiversity hotspot due to its high number of endemic/native plant species. In this work we developed and assessed a methodological framework to produce a RapidEye-based vegetation map. Reasonable accuracies were achieved for a 26 categories classification scheme in two different seasons. We tested pixel and object based approaches and the inclusion of a vegetation index band on top of the pre-processed RapidEye bands stack. Object based generally showed to outperform pixel based classification approaches except for linear or highly scattered classes. The addition of a vegetation index to the workflow increased the separability of the Jeffrey-Matusita least separable class pairs, but not necessarily the overall accuracy. The Pontius accuracy assessment highlighted class specific accuracy tradeoffs related to different combinations of the inputs and methods. The approach to be used, in conclusion, should be carefully considered on the basis of the desired result.

Global Island Monitoring Scheme (GIMS): a proposal for the long-term coordinated survey and monitoring of native island forest biota

Islands harbour evolutionary and ecologically unique biota, which are currently disproportionately threatened by a multitude of anthropogenic factors, including habitat loss, invasive species and climate change. Native forests on oceanic islands are important refugia for endemic species, many of which are rare and highly threatened. Long-term monitoring schemes for those biota and ecosystems are urgently needed: (i) to provide quantitative baselines for detecting changes within island ecosystems, (ii) to evaluate the effectiveness of conservation and management actions, and (iii) to identify general ecological patterns and processes using multiple island systems as repeated ‘natural experiments’. In this contribution, we call for a Global Island Monitoring Scheme (GIMS) for monitoring the remaining native island forests, using bryophytes, vascular plants, selected groups of arthropods and vertebrates as model taxa. As a basis for the GIMS, we also present new, optimized monitoring protocols for bryophytes and arthropods that were developed based on former standardized inventory protocols. Effective inventorying and monitoring of native island forests will require: (i) permanent plots covering diverse ecological gradients (e.g. elevation, age of terrain, anthropogenic disturbance); (ii) a multiple-taxa approach that is based on standardized and replicable protocols; (iii) a common set of indicator taxa and community properties that are indicative of native island forests’ welfare, building on, and harmonized with existing sampling and monitoring efforts; (iv) capacity building and training of local researchers, collaboration and continuous dialogue with local stakeholders; and (v) long-term commitment by funding agencies to maintain a global network of native island forest monitoring plots.

Using modeling tools for implementing feasible land use and nature conservation governance systems in small islands – The Pico Island (Azores) case-study

The present study deals with the development of systematic conservation planning as management instrument in small oceanic islands, ensuring open systems of governance, and able to integrate an informed and involved participation of the stakeholders. Marxan software was used to define management areas according a set of alternative land use scenarios considering different conservation and management paradigms. Modeled conservation zones were interpreted and compared with the existing protected areas allowing more fused information for future trade-outs and stakeholders involvement. The results, allowing the identification of Target Management Units (TMU) based on the consideration of different development scenarios proved to be consistent with a feasible development of evaluation approaches able to support sound governance systems. Moreover, the detailed geographic identification of TMU seems to be able to support participated policies towards a more sustainable management of the entire island.

Spatial planning and resource use in the Azores

This paper examines spatial energy consumption patterns under the Green Islands Massachusetts Institute of Technology-Portugal Program. The project consisted of the elaboration of a Global Scenario: the assembly of all different land use scenarios established among different Spatial Plans, to understand the future demand for energy in the Azores. To achieve this, all Spatial Plans were assessed and the pattern of land use/energy consumption presented. Based on foreseen land use, future demand for energy was determined. Measures to minimize the effects of production and consumption were also assessed and presented. This study demonstrates that demand for energy in the Azores will increase in the future, with the urban and agricultural sectors being mostly responsible for that growth. Reducing emissions from deforestation and forest degradation (REDD) mechanisms and tools associated with effective forest management seem to be a possible solution to decrease the negative effects of demand for energy growth. The development of a new research area based on Strategic Spatial Planning for Energy Consumption Reduction and REDD strategies is recommended.

Estimating tree canopy cover percentage in a mediterranean silvopastoral systems using Sentinel-2A imagery and the stochastic gradient boosting algorithm

ABSTRACT The availability of accurate and updated spatial information of tree cover in semi-arid and arid silvopastoral systems (SPSs) is crucial to understand their spatial patterns and trends. Although remote-sensing techniques have been proved useful in estimating tree canopy cover in general, more research is required to investigate the capabilities of new high spectral and spatial resolution satellites, such as Sentinel-2A, in predicting tree canopy cover in semi-arid environments. The objective of this study was to explore the capabilities of Sentinel-2A multispectral data, in combination with a stochastic modelling technique, for mapping montado tree canopy cover percentage (CCP) at pixel level. The stochastic gradient boosting algorithm was used to predict tree CCP using Sentinel-2A spectral data, vegetation indices, and textural information as predictor variables. The results of the study showed that the combination of multispectral bands with the selected vegetation indices and grey-level co-occurrence matrix (GLCM) texture features performs well, presenting a coefficient of determination (R2) of 82.8% and an error prediction of 8.68%. The analysis also showed that normalized difference vegetation index (NDVI) and Plant Senescence Reflectance Index (PSRI), as well as homogeneity texture feature, were the most important predictor variables to undertake the complex montado tree canopy cover estimation. In addition, this study demonstrated the usefulness of narrow spectral bands provided by the Sentinel-2A sensor for accurately estimating tree CCP (e.g. Red Edge1 – B5 – for PSRI and NIR2 – B8a – for NDVI computation). The modelling procedure used here emphasizes the effectiveness of stochastic models for predicting tree canopy cover from a complex semi-arid silvopastoral system by using Sentinel-2A multispectral data.