Joana R. Vicente

Where will conflicts between alien and rare species occur after climate and land-use change? A test with a novel combined modelling approach

Protecting native biodiversity against alien invasive species requires powerful methods to anticipate these invasions and to protect native species assumed to be at risk. Here, we describe how species distribution models (SDMs) can be used to identify areas predicted as both suitable for rare native species and highly susceptible to invasion by alien species, at present and under future climate and land-use scenarios. To assess the condition and dynamics of such conflicts, we developed a combined predictive modelling (CPM) approach, which predicts species distributions by combining two SDMs fitted using subsets of predictors classified as acting at either regional or local scales. We illustrate the CPM approach for an alien invader and a rare species associated with similar habitats in northwest Portugal. Combined models predict a wider variety of potential species responses, providing more informative projections of species distributions and future dynamics than traditional, non-combined models. They also provide more informative insight regarding current and future rare-invasive conflict areas. For our studied species, conflict areas of highest conservation relevance are predicted to decrease over the next decade, supporting previous reports that some invasive species may contract their geographic range and impact due to climate change. More generally, our results highlight the more informative character of the combined approach to address practical issues in conservation and management programs, especially those aimed at mitigating the impact of invasive plants, land-use and climate changes in sensitive regions.

Will climate change drive alien invasive plants into areas of high protection value? An improved model-based regional assessment to prioritise the management of invasions

Species distribution models (SDMs) studies suggest that, without control measures, the distribution of many alien invasive plant species (AIS) will increase under climate and land-use changes. Due to limited resources and large areas colonised by invaders, management and monitoring resources must be prioritised. Choices depend on the conservation value of the invaded areas and can be guided by SDM predictions. Here, we use a hierarchical SDM framework, complemented by connectivity analysis of AIS distributions, to evaluate current and future conflicts between AIS and high conservation value areas. We illustrate the framework with three Australian wattle (Acacia) species and patterns of conservation value in Northern Portugal. Results show that protected areas will likely suffer higher pressure from all three Acacia species under future climatic conditions. Due to this higher predicted conflict in protected areas, management might be prioritised for Acacia dealbata and Acacia melanoxylon. Connectivity of AIS suitable areas inside protected areas is currently lower than across the full study area, but this would change under future environmental conditions. Coupled SDM and connectivity analysis can support resource prioritisation for anticipation and monitoring of AIS impacts. However, further tests of this framework over a wide range of regions and organisms are still required before wide application.

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.

Using life strategies to explore the vulnerability of ecosystem services to invasion by alien plants

Invasive plants can have different effects on ecosystem functioning and on the provision of ecosystem services, with the direction and magnitude of such effects depending on the service and ecosystem being considered, but also on the life strategies of the invaders. Strategies can influence invasiveness, but also key processes of host ecosystems. To address the combined effects of these various factors, we developed a methodological framework to identify areas of possible conflict between ecosystem services and alien invasive plants, considering interactions between landscape invasibility and species invasiveness. Our framework combines multi-model inference, efficient techniques to map ecosystem services, and life strategies. The latter provides a functional link between invasion, functional changes, and potential provision of services by invaded ecosystems. The framework was applied to a region in Portugal, for which we could successfully predict current patterns of plant invasion, of ecosystem service provision, and of potential conflict between alien species richness and the potential provision of selected services. Potential conflicts were identified for all combinations of plant strategy and ecosystem service, with an emphasis on carbon sequestration, water regulation, and wood production. Lower levels of conflict were obtained between invasive plant strategies and the habitat for biodiversity supporting service. The value of the proposed framework for landscape management and planning is discussed with emphasis on anticipation of conflicts, mitigation of negative impacts, and facilitation of positive effects of plant invasions on ecosystems and their services.

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.

On the interest of plant functional classifications to study community—level effects of increased disturbance on coastal dune vegetation

Abstract Coastal zones are suffering from severe changes. Dune systems are forecasted to be impacted severely by such changes. Since shifts in coastal dynamics may drive modifications in the floristic composition of plant communities, effective indicators of such changes are needed to support adaptive measures. We performe here an assessment of the relative efficiency of functional and phytosociological classifications in the analysis of structure and dynamics in foredune vegetation. Our results identified common signals but also highlighted some differences among results from different classifications with potential consequences for the monitoring of changes in dune ecosystems. The coincident signals provided by the analysed classification systems suggest that they are effective in capturing the major rules involved in the structure and dynamics of foredune vegetation. Since the disturbance regime in foredunes is mostly related to prevailing coastal dynamics, compositional shifts in phytosociological or functional spectra are thus useful in the establishment of reliable indicators and protocols to monitor changes in coastal zones.

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.

Ecological and Cultural Consequences of Agricultural Abandonment in the Peneda-Gerês National Park (Portugal)

The socioeconomic and technological development of human societies has been driving profound changes in the classic relationships between cities and the countryside (Gutman, 2007). In the context of such changes, the abandonment of agricultural land is a growing concern throughout much of Europe’s rural mountain areas. Migration and aging population are the main reasons behind the collapse of traditional farming systems and the increase in land abandonment. Together with an intrinsic resistance to adopting modern market-oriented farming practices, these processes induce consequences (still poorly evaluated) to the environment as well as numerous socio-economic impacts. Many of the most traditional types of agricultural landscapes in Europe are dramatically decreasing due to this partial or complete abandonment of farmland (EEA, 2005).

Community structure informs species geographic distributions

Understanding what determines species’ geographic distributions is crucial for assessing global change threats to biodiversity. Measuring limits on distributions is usually, and necessarily, done with data at large geographic extents and coarse spatial resolution. However, survival of individuals is determined by processes that happen at small spatial scales. The relative abundance of coexisting species (i.e. ‘community structure’) reflects assembly processes occurring at small scales, and are often available for relatively extensive areas, so could be useful for explaining species distributions. We demonstrate that Bayesian Network Inference (BNI) can overcome several challenges to including community structure into studies of species distributions, despite having been little used to date. We hypothesized that the relative abundance of coexisting species can improve predictions of species distributions. In 1570 assemblages of 68 Mediterranean woody plant species we used BNI to incorporate community structure into Species Distribution Models (SDMs), alongside environmental information. Information on species associations improved SDM predictions of community structure and species distributions moderately, though for some habitat specialists the deviance explained increased by up to 15%. We demonstrate that most species associations (95%) were positive and occurred between species with ecologically similar traits. This suggests that SDM improvement could be because species co-occurrences are a proxy for local ecological processes. Our study shows that Bayesian Networks, when interpreted carefully, can be used to include local conditions into measurements of species’ large-scale distributions, and this information can improve the predictions of species distributions.