Ana Sofia Vaz

The progress of interdisciplinarity in invasion science.

Abstract Interdisciplinarity is needed to gain knowledge of the ecology of invasive species and invaded ecosystems, and of the human dimensions of biological invasions. We combine a quantitative literature review with a qualitative historical narrative to document the progress of interdisciplinarity in invasion science since 1950. Our review shows that 92.4% of interdisciplinary publications (out of 9192) focus on ecological questions, 4.4% on social ones, and 3.2% on social–ecological ones. The emergence of invasion science out of ecology might explain why interdisciplinarity has remained mostly within the natural sciences. Nevertheless, invasion science is attracting social–ecological collaborations to understand ecological challenges, and to develop novel approaches to address new ideas, concepts, and invasion-related questions between scholars and stakeholders. We discuss ways to reframe invasion science as a field centred on interlinked social–ecological dynamics to bring science, governance and society together in a common effort to deal with invasions.

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.

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.

Using the ‘regime shift’ concept in addressing social–ecological change

‘Regime shift’ has emerged as a key concept in the environmental sciences. The concept has roots in complexity science and its ecological applications, and is increasingly applied to intertwined social and ecological phenomena. Yet what exactly is a regime shift? We explore this question at three nested levels. First, we propose a broad, contingent, multi-perspective epistemological basis for the concept, seeking to build bridges between its complexity theory origins and critiques from science studies, political ecology, and environmental history. Second, we define the concept in a way that is consistent with this epistemology, building on previous work on speed, scale, stickiness, and interrelationships, but also emphasising human perceptions and rhetorical uses of the notion. Third, we propose a novel typology of the ways in which the regime shift concept is used in analysing social–environmental phenomena in geography and beyond. These uses are categorised along two axes. On the one side, we distinguish between description of past or present changes and normative prescriptions for the future. On the other side, we distinguish between whether the focus is on material shifts (social and ecological) or conceptual shifts (discourses and ideas). We illustrate the typology with reference to social–environmental changes in landscapes around the world that are dominated by plantations or the widespread naturalisation of Australian Acacia species. We conclude that the regime shift concept is a boundary object with value as both an analytical and communicative tool in addressing social–environmental challenges.

Plant species segregation in dune ecosystems emphasises competition and species sorting over facilitation

Background: Coastal dunes are dynamic ecosystems, with vegetation seen as a key element in the response to a continuously changing environment. Aims: We explored co-occurrence patterns of plant species within dune ecosystems along a regional climatic and a local sea–inland gradient. Methods: Five habitat types were surveyed along a sea–inland transect at seven sites along a climatic gradient in Portugal. A multistep framework, considering the relevant scales and gradients, provided standardised scores of species co-occurrence (based on presence/absence and abundance data) for the whole study area and along the climatic and sea–inland gradients. Results: Species diversity was primarily related to the local sea–inland gradient. Co-occurrence analyses indicated the prevalence of species segregation, suggesting competition and species sorting across sites. Within each site, segregation prevailed, but tendencies for species aggregation were observed in some habitat types. Conclusions: To our knowledge, this is the first study evaluating species co-occurrences considering all habitat types within the whole dune ecosystem, analysing presence/absence and abundance data against regional and local gradients. Results converge with refined theories of community assembly, constituting added values for assessing multiscalar co-occurrence patterns of plant communities, and thus improving reporting of the condition of dune habitats and biodiversity.

Explaining people's perceptions of invasive alien species: A conceptual framework

Human perceptions of nature and the environment are increasingly being recognised as important for environmental management and conservation. Understanding peoples perceptions is crucial for understanding behaviour and developing effective management strategies to maintain, preserve and improve biodiversity, ecosystem services and human well-being. As an interdisciplinary team, we produced a synthesis of the key factors that influence peoples perceptions of invasive alien species, and ordered them in a conceptual framework. In a context of considerable complexity and variation across time and space, we identified six broad-scale dimensions: (1) attributes of the individual perceiving the invasive alien species; (2) characteristics of the invasive alien species itself; (3) effects of the invasion (including negative and positive impacts, i.e. benefits and costs); (4) socio-cultural context; (5) landscape context; and (6) institutional and policy context. A number of underlying and facilitating aspects for each of these six overarching dimensions are also identified and discussed. Synthesising and understanding the main factors that influence peoples perceptions is useful to guide future research, to facilitate dialogue and negotiation between actors, and to aid management and policy formulation and governance of invasive alien species. This can help to circumvent and mitigate conflicts, support prioritisation plans, improve stakeholder engagement platforms, and implement control measures.

Dynamic models in research and management of biological invasions

Invasive species are increasing in number, extent and impact worldwide. Effective invasion management has thus become a core socio-ecological challenge. To tackle this challenge, integrating spatial-temporal dynamics of invasion processes with modelling approaches is a promising approach. The inclusion of dynamic processes in such modelling frameworks (i.e. dynamic or hybrid models, here defined as models that integrate both dynamic and static approaches) adds an explicit temporal dimension to the study and management of invasions, enabling the prediction of invasions and optimisation of multi-scale management and governance. However, the extent to which dynamic approaches have been used for that purpose is under-investigated. Based on a literature review, we examined the extent to which dynamic modelling has been used to address invasions worldwide. We then evaluated how the use of dynamic modelling has evolved through time in the scope of invasive species management. The results suggest that modelling, in particular dynamic modelling, has been increasingly applied to biological invasions, especially to support management decisions at local scales. Also, the combination of dynamic and static modelling approaches (hybrid models with a spatially explicit output) can be especially effective, not only to support management at early invasion stages (from prevention to early detection), but also to improve the monitoring of invasion processes and impact assessment. Further development and testing of such hybrid models may well be regarded as a priority for future research aiming to improve the management of invasions across scales.

Effect of antenatal corticosteroids on morbidity and mortality of preterm singletons and twins

Abstract Purpose: To compare the effect of antenatal corticosteroids (ACS) on neonatal outcomes among singleton and twin pregnancies and the impact of completeness and timing of ministration. Materials and methods: Retrospective cohort study involving 951 preterm deliveries (25+0–34+6 weeks), between 2006 and 2015. Neonatal outcomes were evaluated according to completeness of ACS (“Complete” n = 441; “Rescue” n = 38; “Incomplete” n = 175; “No ACS” n = 98) and timing of therapy related to delivery (“Before 7 days” n = 260; “After 7 days” n = 181). Results: On respiratory distress syndrome (RDS), odds ratio (OR) for twins was 0.172, 95% confidence interval (CI) was 0.047; 0.591 and for singletons 0.390 (95%CI 0.214; 0.703) for complete or rescue courses, and 0.280 (95%CI 0.069; 1.066) for twins and 0.906 (95%CI 0.482; 1.698) for singletons for incomplete courses. About the need for mechanical ventilation (MV), twins had an OR of 0.189 (95%CI 0.052; 0.642) and singletons of 0.404 (95%CI 0.222; 0.727) for complete or rescue courses and twins had OR = 0.225 (95%CI 0.053; 0.874) and singletons of 0.404 (95%CI 0.222; 0.727) for incomplete courses. About timing, group “After 7 days” had OR = 2.00 for RDS (95%CI 1.21; 3.30) and 2.32 (95%CI 1.42; 3.78) for MV. Conclusions: ACS improves neonatal outcomes both in singleton and twins. Delivering 7 days after a complete course decreased neonatal morbidity.

Managing plant invasions through the lens of remote sensing: A review of progress and the way forward

Biological invasions are a challenging driver of global environmental change and a fingerprint of the Anthropocene. Remote sensing has gradually become a fundamental tool for understanding invasion patterns, processes and impacts. Nevertheless, a quantitative overview of the progress and extent of remote sensing applications to the management of plant invasions is lacking. This overview is particularly necessary to support the development of more operational frameworks based on remote sensing that can effectively improve the management of invasions. Here, we evaluate and discuss the progress, current state and future opportunities of remote sensing for the research and management of plant invasions. Supported on a systematic literature review, our study shows that, since the 1970s, remote sensing was mainly used to map and identify invasive plants, evolving, around the mid-2000s, towards a tool for assessing invasion impacts. Although remote sensing studies often focus on detecting plant invaders at advanced invasion stages, they can also contribute to the prediction of early invasion stages and to the assessment of their impacts. Despite the growing awareness of technical limitations, remote sensing offers many opportunities to further improve the management of plant invasions. These opportunities relate to the capacity of remote sensing to: (a) detect and evaluate the extent of invasions, assisting on any management option aiming at mitigating plant invasions and their impacts; (b) consider modelling frameworks that anticipate future invasions, supporting the prevention and eradication at early invasion stages and protecting ecosystems and the services they provide; and (c) monitor changes in invasion dominance, as well as the resulting impacts, supporting mitigation, restoration and adaptation actions. Finally, we discuss the way forward to make remote sensing more effective in the scope of invasion management, considering current and future Earth observation missions.

Neonatal outcome in preterm deliveries before 34-week gestation – the influence of the mechanism of labor onset

Abstract Purpose: To evaluate neonatal outcomes in preterm infants with less than 34 weeks after spontaneous labor, preterm premature rupture of membranes (PPROM) or iatrogenic delivery and to clarify whether the mechanism of labor onset is a risk factor for adverse short-term neonatal outcome. Methods: We performed a retrospective case-control study, which included 266 preterm newborns with less than 34-week gestation, between 2011 and 2015. Neonatal outcomes were compared according to the mechanism of labor onset. Our primary outcomes were neonatal death, sequelae on hospital discharge and a composite of these two variables (combined neonatal outcome). Results: Compared to spontaneous preterm labor, iatrogenic preterm newborns were at increased risk of respiratory distress syndrome (RDS) [Odds Ratio (OR) 3.05 (95%CI 1.31; 7.12)], and need of exogenous surfactant administration [OR 3.87 (95%CI 1.60; 9.35)]. PPROM was associated with higher risk of neonatal sepsis [OR 12.96 (95%CI 1.18; 142.67)]. There were no differences regarding the combined outcome for iatrogenic [OR 0.94 (95%CI 0.33; 2.71)] or PPROM [OR 1.11 (95%CI 0.35; 3.49)] groups. Conclusions: In our study, the different mechanisms of labor onset are associated with different neonatal outcomes. Iatrogenic preterm birth was associated with an increased risk of RDS and a higher need of exogenous surfactant administration than spontaneous group. The rate of neonatal sepsis was significantly higher in PPROM group along with a higher prevalence of histological chorioamnionitis.