João Alexandre Cabral

Molecular sexing of birds: A comparative review of polymerase chain reaction (PCR)-based methods.

Accurate identification of sex in birds is important for the management and conservation of avian wildlife in several ways, namely in the development of population, behavioral and ecological studies, as well as in the improvement of ex situ captive breeding programs. In general, nestlings, juveniles and adult birds of a wide number of sexually monomorphic species cannot be sexed based on phenotypic traits. The development of molecular methodologies for avian sexing overcame these difficulties, allowing a reliable gender differentiation for these species. The polymerase chain reaction (PCR)-based methods have been widely applied in molecular sexing of birds, using a large diversity of sex-linked markers. During the last 15 yrs, there was a continuous improvement in the PCR-based protocols for bird sexing, increasing the accuracy, speed and high-throughput applicability of these techniques. The recent advances in real-time PCR platforms and whole genome analysis methods provided new resources for the detection and analysis of novel specific markers and protocols. This review presents a comparative guide of classical and recent advances in PCR-based methods for avian molecular sexing, highlighting its strengths and limitations. Future research opportunities in this field are also addressed.

Predicting trends of invasive plants richness using local socio-economic data: An application in North Portugal

This study assesses the potential of an integrated methodology for predicting local trends in invasive exotic plant species (invasive richness) using indirect, regional information on human disturbance. The distribution of invasive plants was assessed in North Portugal using herbarium collections and local environmental, geophysical and socio-economic characteristics. Invasive richness response to anthropogenic disturbance was predicted using a dynamic model based on a sequential modeling process (stochastic dynamic methodology-StDM). Derived scenarios showed that invasive richness trends were clearly associated with ongoing socio-economic change. Simulations including scenarios of growing urbanization showed an increase in invasive richness while simulations in municipalities with decreasing populations showed stable or decreasing levels of invasive richness. The model simulations demonstrate the interest and feasibility of using this methodology in disturbance ecology.

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.

Differential mortality of birds killed at wind farms in Northern Portugal

Capsule The Skylark Alauda arvensis had the highest overall mortality in ten Northern Portuguese wind farms surveyed between 2006 and 2011. Analysis from the integration of conventional and molecular techniques suggest a sex and age biased mortality affecting mainly adult males (90.9%), which may be related to their characteristic breeding male song-flights making them highly vulnerable to collision with wind turbines. The results highlight the added value of more complete population impact assessments that go beyond simple carcass identification at wind farms.

High-resolution melting analysis for bird sexing: a successful approach to molecular sex identification using different biological samples.

High‐resolution melting (HRM) analysis is a very attractive and flexible advanced post‐PCR method with high sensitivity/specificity for simple, fast and cost‐effective genotyping based on the detection of specific melting profiles of PCR products. Next generation real‐time PCR systems, along with improved saturating DNA‐binding dyes, enable the direct acquisition of HRM data after quantitative PCR. Melting behaviour is particularly influenced by the length, nucleotide sequence and GC content of the amplicons. This method is expanding rapidly in several research areas such as human genetics, reproductive biology, microbiology and ecology/conservation of wild populations. Here we have developed a successful HRM protocol for avian sex identification based on the amplification of sex‐specific CHD1 fragments. The melting curve patterns allowed efficient sexual differentiation of 111 samples analysed (plucked feathers, muscle tissues, blood and oral cavity epithelial cells) of 14 bird species. In addition, we sequenced the amplified regions of the CHD1 gene and demonstrated the usefulness of this strategy for the genotype discrimination of various amplicons (CHD1Z and CHD1W), which have small size differences, ranging from 2 bp to 44 bp. The established methodology clearly revealed the advantages (e.g. closed‐tube system, high sensitivity and rapidity) of a simple HRM assay for accurate sex differentiation of the species under study. The requirements, strengths and limitations of the method are addressed to provide a simple guide for its application in the field of molecular sexing of birds. The high sensitivity and resolution relative to previous real‐time PCR methods makes HRM analysis an excellent approach for improving advanced molecular methods for bird sexing.

A Minimal Invasive Method to Forecast the Effects of Anthropogenic Disturbance on Tropical Cave Beetle Communities

Many tropical landscapes are changing rapidly, with uncertain outcomes for biodiversity, landscape function, and the corresponding landscape services. Therefore, monitoring and adaptively managing the drivers and consequences of landscape change while sustaining the production of essential resources have become research and policy priorities. In this perspective, we have applied a recent framework, the stochastic dynamic methodology (StDM), with the purpose of understanding the effects of natural and anthropogenic disturbances on caves’ integrity using cave beetle communities (Coleoptera) as ecological indicators. The proposed method was preceeded by a generalized linear model for discriminating significant relationships between the selected indicators, the structural changes in the caves, and the epigean habitats associated. The obtained results showed different ecological trends in response to the environmental changes. Overall, the simulation results seem to demonstrate the StDM reliability in determining the effects of habitat dynamics, that is, the expansion of agricultural activities, in areas near the caves in the structure of cave beetle communities. The applied method, based on universal information-theoretic principles, can be easily implemented and interpreted by environmental managers and decision makers, enabling anticipating impacts and supporting the development of measures aimed at minimizing the identified problems.

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.

Integrating land cover structure and functioning to predict biodiversity patterns: a hierarchical modelling framework designed for ecosystem management

ContextLand-use/land-cover (LU/LC) dynamics is one of the main drivers of global environmental change. In the last years, aerial and satellite imagery have been increasingly used to monitor the spatial extent of changes in LU/LC, deriving relevant biophysical parameters (i.e. primary productivity, climate and habitat structure) that have clear implications in determining spatial and temporal patterns of biodiversity, landscape composition and ecosystem services.ObjectivesAn innovative hierarchical modelling framework was developed in order to address the influence of nested attributes of LU/LC on community-based ecological indicators.MethodsFounded in the principles of the spatially explicit stochastic dynamic methodology (StDM), the proposed methodological advances are supported by the added value of integrating bottom-up interactions between multi-scaled drivers.ResultsThe dynamics of biophysical multi-attributes of fine-scale subsystem properties are incorporated to inform dynamic patterns at upper hierarchical levels. Since the most relevant trends associated with LU/LC changes are explicitly modelled within the StDM framework, the ecological indicators’ response can be predicted under different social-economic scenarios and site-specific management actions. A demonstrative application is described to illustrate the framework methodological steps, supporting the theoretic principles previously presented.ConclusionsWe outline the proposed multi-model framework as a promising tool to integrate relevant biophysical information to support ecosystem management and decision-making.

First Detection of Borrelia burgdorferi sensu lato DNA in Serum of the Wild Boar (Sus scrofa) in Northern Portugal by Nested-PCR

Lyme borreliosis is the most common tick-borne zoonosis in the northern hemisphere. Several vertebrates are crucial in the epidemiological cycle of Borrelia burgdorferi sensu lato, but the role of wild boar as a reservoir is still unknown. Sera were collected from 90 wild boars shot in the Trás-os-Montes region, Northern Portugal (hunting season 2011/2012). In this study, Borrelia DNA was detected for the first time by nested-PCR in three different sera, suggesting that the wild boar may be a potential reservoir for this spirochete. Sequencing results show 100% similarity with Borrelia afzelii. Further studies are needed to evaluate the public health risks associated with boar hunting.

Ecological relationships between phytoplankton communities and different spatial scales in European reservoirs: implications at catchment level monitoring programmes

Phytoplankton communities are structured by factors acting over temporal and spatial scales. Identifying which factors are driving spatial patterns in aquatic communities is the central aim of ecology. In this study, data sets of phytoplankton communities and environmental data of two Portuguese reservoirs types (lowland “riverine reservoirs” and higher altitude “artificial lake reservoirs”) were used to determine the importance of environmental variables at different spatial (geographical, regional and local) and time scales (seasons, years) on the community structure. In all the data sets, the multivariate ordination technique Canonical Correspondence Analysis (CCA) showed that regional and local scales explained the majority (9–18% and 13–19%, respectively) of the taxa variance. However, for “riverine reservoirs”, time variables were more important, explaining 27% of the variability in phytoplankton assemblages. Variance partitioning was used to assess the individual importance of the three spatial scales and time for the community structure of the two reservoir types. The majority of among-site variability (5.9–21.4%) was accounted for by time variables, with local, regional, and geographical scale variables accounting for 3.3–5.6%, 3.7–4.5% and 2.6–2.9%, respectively. The effects of different spatial scales on phytoplankton communities were clearly interrelated; thus, implying that phytoplankton assemblages are capable of detecting stress from catchment to site scales.