Fire suppression and land-use strategies drive future dynamics of an invasive plant in a fire-prone mountain area under climate change.

Woody invasive alien species can have profound impacts on ecosystem processes and functions, including fire regulation, which can significantly affect landscape resilience. Acacia dealbata, a widespread invasive alien plant in the Iberian Peninsula, holds well-known fire-adaptation traits (e.g., massive soil seed banks and heat-stimulated seed germination). In this study, we assess to what extent fire suppression and land-use strategies could affect the potential distribution of A. dealbata in a fire-prone transboundary protected mountain area of Portugal and Spain, using Habitat Suitability Models. Specifically, we predicted changes in habitat suitability for A. dealbata between years 2010 and 2050. We explored the potential impacts of two land-use strategies ('Business-as-usual' or 'High Nature Value farmlands') combined with three levels of fire suppression effectiveness using the biomod2 package in R. We also considered the potential effects of two climate change scenarios (RCP4.5 and RCP8.5). Our modeling approach demonstrated a strong capacity to predict habitat suitability using either climate or land-cover information alone (AUC climate = 0.947; AUC LC = 0.957). According to climate-based models, A. dealbata thrives under conditions characterized by higher precipitation seasonality, higher precipitation in the warmest month, and higher minimum temperature in the coldest month. Regarding land cover, A. dealbata thrives mainly in landscapes dominated by urban areas and evergreen forest plantations. Our models forecasted that habitat suitability by 2050 could either increase or decrease depending on the specific combinations of fire suppression, land-use, and climate scenarios. Thus, a combination of business-as-usual and fire-exclusion strategies would enhance habitat suitability for the species. Conversely, management promoting High Nature Value farmlands would decrease the available suitable habitat, particularly under low fire suppression efforts. These findings suggest that promoting sustainable farming activities could impede the spread of A. dealbata by reducing habitat availability, while strategies aiming at fire-exclusion could facilitate its expansion, likely by enabling establishment and large seed production. This study highlights the complex interplay between fire-prone invasive species, fire and land-use strategies, and climate change; and thus the need to consider the interactions between land-use and fire management to promote invasive species control and landscape resilience.

Climate- and fire-smart landscape scenarios call for redesigning protection regimes to achieve multiple management goals.

Integrated management of biodiversity and ecosystem services (ES) in heterogeneous landscapes requires considering the potential trade-offs between conflicting objectives. The UNESCO's Biosphere Reserve zoning scheme is a suitable context to address these trade-offs by considering multiple management zones that aim to minimise conflicts between management objectives. Moreover, in Mediterranean ecosystems, management and planning also needs to consider drivers of landscape dynamics such as wildfires and traditional farming and forestry practices that have historically shaped landscapes and the biodiversity they host. In this study, we applied a conservation planning approach to prioritise the allocation of management zones under future landscape and climate scenarios. We tested different landscape management scenarios reflecting the outcomes of climate-smart and fire-smart policies. We projected the expected landscape dynamics and associated changes on the distribution of 207 vertebrate species, 4 ES and fire hazard under each scenario. We used Marxan with Zones to allocate three management zones, replicating the Biosphere Reserves zoning scheme ("Core area", "Buffer zone" and "Transition area") to address the various management objectives within the Biosphere Reserve. Our results show that to promote ES supply and biodiversity conservation, while also minimising fire hazard, the reserve will need to: i) Redefine its zoning, especially regarding Core Areas, which need a considerable expansion to help mitigate changes in biodiversity and accommodate ES supply under expected changes in climate and species distribution. ii) Revisit current management policies that will result in encroached landscapes prone to high intensity, uncontrollable wildfires with the potential to heavily damage ecosystems and compromise the supply of ES. Our results support that both climate- and fire-smart policies in the Meseta Ibérica can help develop multifunctional landscapes that help mitigate and adapt to climate change and ensure the best possible maintenance of biodiversity and ES supply under uncertain future climate conditions.

On the development of a regional climate change adaptation plan: Integrating model-assisted projections and stakeholders' perceptions.

Climate change is expected to have strong social-ecological implications, with global but especially regional and local challenges. To assess the climatic vulnerability of a given territory, it is necessary to evaluate its exposure to climate change and its adaptive capacity. This study describes the development of an Action Plan for Adapting to Climate Change in the Tâmega and Sousa Region, a mountainous inter-municipal community in the North of Portugal. The goals were to identify the main impacts of climate change on water resources, agriculture, forests, biodiversity, and socioeconomic sectors, as well as to develop a plan, merging local and scientific knowledge through a transdisciplinary lens. This study describes an approach that combines modelling methods, applied in the different sectors, and participatory methods, based on the analysis of the perceptions of local actors. Results indicate that the target region will experience a generalized increase in temperature and a decrease in precipitation, which will negatively impact all studied social-ecological dimensions. Overall, local business and institutional agents perceive the primary and tourism sectors as the most vulnerable in the region. The described framework demonstrates the engagement process between relevant scientific experts and local practitioners, as well as how it is critical to understand the impacts of climate change and to support the co-design of an adaptation plan, which in turn can guide political and economic decision-making towards effective implementation of the plan. In addition, the difficulties and challenges encountered during this process are discussed to support future plans and strategies for local adaptation.

Climatic variables and ecological modelling data for birds, amphibians and reptiles in the Transboundary Biosphere Reserve of Meseta Ibérica (Portugal-Spain).

BACKGROUND: Climate change has been widely accepted as one of the major threats for global biodiversity and understanding its potential effects on species distribution is crucial to optimise conservation planning in future scenarios under global change. Integrating detailed climatic data across spatial and temporal scales into species distribution modelling can help to predict potential changes in biodiversity. Consequently, this type of data can be useful for developing efficient biodiversity management and conservation planning. The provision of such data becomes even more important in highly biodiverse regions, currently suffering from climatic and landscape changes. The Transboundary Biosphere Reserve of Meseta Ibérica (BRMI; Portugal-Spain) is one of the most relevant reserves for wildlife in Europe. This highly diverse region is of great ecological and socio-economical interest, suffering from synergistic processes of rural land abandonment and climatic instabilities that currently threaten local biodiversity.Aiming to optimise conservation planning in the Reserve, we provide a complete dataset of historical and future climate models (1 x 1 km) for the BRMI, used to build a series of distribution models for 207 vertebrate species. These models are projected for 2050 under two climate change scenarios. The climatic suitability of 52% and 57% of the species are predicted to decrease under the intermediate and extreme climatic scenarios, respectively. These models constitute framework data for improving local conservation planning in the Reserve, which should be further supported by implementing climate and land-use change factors to increase the accuracy of future predictions of species distributions in the study area. NEW INFORMATION: Herein, we provide a complete dataset of state-of-the-art historical and future climate model simulations, generated by global-regional climate model chains, with climatic variables resolved at a high spatial resolution (1 × 1 km) over the Transboundary Biosphere Reserve of Meseta Ibérica. Additionally, a complete series of distribution models for 207 species (168 birds, 24 reptiles and 15 amphibians) under future (2050) climate change scenarios is delivered, which constitute framework data for improving local conservation planning in the reserve.

Using fire to enhance rewilding when agricultural policies fail.

Rewilding has been proposed as an opportunity for biodiversity conservation in abandoned landscapes. However, rewilding is challenged by the increasing fire risk associated with more flammable landscapes, and the loss of open-habitat specialist species. Contrastingly, supporting High Nature Value farmlands (HNVf) has been also highlighted as a valuable option, but the effective implementation of agricultural policies often fails leading to uncertain scenarios wherein the effects of wildfire management remain largely unexplored. Herein, we simulated fire-landscape dynamics to evaluate how fire suppression scenarios affect fire regime and biodiversity (102 species of vertebrates) under rewilding and HNVf policies in the future (2050), in a transnational biosphere reserve (Gerês-Xurés Mountains, Portugal-Spain). Rewilding and HNVf scenarios were modulated by three different levels of fire suppression effectiveness. Then, we quantified scenario effects on fire regime (burned and suppressed areas) and biodiversity (habitat suitability change for 2050). Simulations confirm HNVf as a long-term opportunity for fire suppression (up to 30,000 ha of additional suppressed areas between 2031 and 2050 in comparison to rewilding scenario) and for conservation (benefiting around 60% of species). Rewilding benefits some species (20%), including critically endangered, vulnerable and endemic taxa, while several species (33%) also profit from open habitats created by fire. Although HNVf remains the best scenario, rewilding reinforced by low fire suppression management may provide a nature-based solution when societal support through agricultural policies fails.

Effects of species traits and environmental predictors on performance and transferability of ecological niche models.

The ability of ecological niche models (ENMs) to produce robust predictions for different time frames (i.e. temporal transferability) may be hindered by a lack of ecologically relevant predictors. Model performance may also be affected by species traits, which may reflect different responses to processes controlling species distribution. In this study, we tested four primary hypotheses involving the role of species traits and environmental predictors in ENM performance and transferability. We compared the predictive accuracy of ENMs based upon (1) climate, (2) land-use/cover (LULC) and (3) ecosystem functional attributes (EFAs), and (4) the combination of these factors for 27 bird species within and beyond the time frame of model calibration. The combination of these factors significantly increased both model performance and transferability, highlighting the need to integrate climate, LULC and EFAs to improve biodiversity projections. However, the overall model transferability was low (being only acceptable for less than 25% of species), even under a hierarchical modelling approach, which calls for great caution in the use of ENMs to predict bird distributions under global change scenarios. Our findings also indicate that positive effects of species traits on predictive accuracy within model calibration are not necessarily translated into higher temporal transferability.

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.

Correction: Community structure informs species geographic distributions.

[This corrects the article DOI: 10.1371/journal.pone.0197877.].

Assessing the multi-scale predictive ability of ecosystem functional attributes for species distribution modelling.

Global environmental changes are rapidly affecting species' distributions and habitat suitability worldwide, requiring a continuous update of biodiversity status to support effective decisions on conservation policy and management. In this regard, satellite-derived Ecosystem Functional Attributes (EFAs) offer a more integrative and quicker evaluation of ecosystem responses to environmental drivers and changes than climate and structural or compositional landscape attributes. Thus, EFAs may hold advantages as predictors in Species Distribution Models (SDMs) and for implementing multi-scale species monitoring programs. Here we describe a modelling framework to assess the predictive ability of EFAs as Essential Biodiversity Variables (EBVs) against traditional datasets (climate, land-cover) at several scales. We test the framework with a multi-scale assessment of habitat suitability for two plant species of conservation concern, both protected under the EU Habitats Directive, differing in terms of life history, range and distribution pattern (Iris boissieri and Taxus baccata). We fitted four sets of SDMs for the two test species, calibrated with: interpolated climate variables; landscape variables; EFAs; and a combination of climate and landscape variables. EFA-based models performed very well at the several scales (AUCmedian from 0.881±0.072 to 0.983±0.125), and similarly to traditional climate-based models, individually or in combination with land-cover predictors (AUCmedian from 0.882±0.059 to 0.995±0.083). Moreover, EFA-based models identified additional suitable areas and provided valuable information on functional features of habitat suitability for both test species (narrowly vs. widely distributed), for both coarse and fine scales. Our results suggest a relatively small scale-dependence of the predictive ability of satellite-derived EFAs, supporting their use as meaningful EBVs in SDMs from regional and broader scales to more local and finer scales. Since the evaluation of species' conservation status and habitat quality should as far as possible be performed based on scalable indicators linking to meaningful processes, our framework may guide conservation managers in decision-making related to biodiversity monitoring and reporting schemes.

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.

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.

The progress of interdisciplinarity in invasion science.

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.