C ARLOS B RITO 1,

1 - CIBIO/InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos da Universidade do Porto, R. Padre Armando Quintas, 7, 4485-661 Vairão, Portugal. 2 - Departamento de Biologia da Faculdade de Ciências da Universidade do Porto. Rua Campo Alegre, 4169-007 Porto, Portugal.

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Content: Habitat loss and fragmentation negatively affect ecological and biological

patterns of populations. Assessing structural connectivity between populations across the landscape is crucial to better understand the effects of fragmentation and to implement effective conservation measures. The number of methodological tools to assess structural connectivity has being growing and previous reviews on the subject have provided the basis for general understanding of particular methods. Still, integrative overviews about their constraints and ecological applications are missing. New approaches have also arisen during the last years, urging the need of updating knowledge about available connectivity methods.

Objectives: We aim updating previous reviews by including more structural

connectivity methods and reviewing their most recent advances. We synthesise major advantages/disadvantages underlying each method, and provide insights concerning research priorities that should be addressed in future studies.

Methods: We revised peer-reviewed literature published up to September, 2016. Results: We summarised the primordial and the most recent methods that have been

used to estimate structural connectivity, providing a synthetic guide to help researchers efficiently evaluate the relationship between landscapes and organisms.

Conclusions: Future research should focus on the development of integrative

frameworks combining complementary methods to better understand the relationship between landscape structure and species behaviour at structural and functional levels. The increasing computational resources and feasibility in gathering genetic and movement data is allowing the employment of sophisticated methods to evaluate population connectivity. Focusing on these subjects will benefit landscape connectivity and the preservation of overall landscape patterns crucial for population stability and conservation.

Keywords: Circuit theory; Connectivity; Corridors; Cost surface; Dispersal; Graph

theory; Individual-based models; Landscape genetics; Least-cost paths; Network theory.

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Successful movement of biological material (e.g., genes, pollen, seeds, individuals) between populations is critical for their ecological (mating, foraging, dispersal) and evolutionary (population effective size, genetic diversity and adaptation) stability (Baguette et al. 2013; Richardson et al. 2016). The pronounced acceleration of habitat loss and fragmentation rates since the twentieth century has been largely disrupting this process. Natural habitats have been transformed into smaller and isolated habitat patches embedded in human-dominated landscapes, hindering the movement of organisms and leading to abrupt local population declines and increased extinction risks (Lindenmayer and Fischer 2013). To contribute for an improved understanding of the relationship between heterogeneous landscapes and organisms, Taylor et al. (1993) coined the term “landscape connectivity” – the degree to which landscape facilitates or hampers movements of an entity between resource patches. Over time, a growing interest in landscape connectivity by researchers and conservation practitioners prompted conceptual (e.g., Driscoll et al. 2013) and methodological advances (e.g., Adriaensen et al. 2003; McRae 2006; Panzacchi et al. 2016). Particularly, the need to objectively describe and quantify functional (biological and ecological responses of species to landscape features) and structural connectivity (physical properties among habitat patches, such as patch configuration and matrix of movement resistance) has stimulated researchers to develop increasingly sophisticated analytical tools.

Structural connectivity partly addresses the functional connectivity in the landscape, a current and relevant challenge for landscape connectivity. However, most structural connectivity methods have a major limitation related with the oversimplification of species responses to fragmentation (Spear et al. 2010; Baguette et al. 2013). This issue is exacerbated on complex landscapes where individuals may react differently to dissimilar types of landscape configuration and composition (LaPoint et al. 2013; Vasudev et al. 2015). Structural connectivity is influenced by the research questions and study species, which demands a carefully planned experimental design and the use of suitable methodologies that properly captures species life history traits and habitat heterogeneity across temporal and spatial scales. The accelerate pace of research in landscape connectivity during the last years prompted the development of numerous methods for assessing structural connectivity, which urged the need of

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Landscape connectivity and Remote Sensing applications for assessing biodiversity patterns in desert environments

synthetic overviews for assembling and providing general understanding of the available methods (Kindlmann and Burel 2008; Dale and Fortin 2010; Sawyer et al. 2011; Rudnick et al. 2012; Kool et al. 2013; Dyer 2015; Etherington 2016).

Most available studies reviewing structural connectivity methods are focused on particular connectivity methods (e.g., Dale and Fortin 2010; Sawyer et al. 2011; Dyer 2015; Etherington 2016). Recently, Kool et al. (2013) performed an exhaustive review on structural connectivity methods and included the largest spectrum of connectivity methods ever analysed. The authors also addressed functional and structural connectivity, including the discussion of conceptual issues, the challenges associated with landscape connectivity, and possible management applications. However, the strong developments in landscape connectivity methods over the recent last years yielded crucial improvements to existent methodologies and the development of new ones (e.g., Bocedi et al. 2014; Kivimäki et al. 2014; Pelletier et al. 2014; Evans and Murphy 2015; Loro et al. 2015; Panzacchi et al. 2016). Accordingly, a review complementing the work done by Kool et al. (2013) summarizing methods descriptions and recent developments, and providing explicit recommendations concerning their applicability in empirical studies is timely and valuable for researchers interested in landscape connectivity. Here, our main goal is to provide an updated structural connectivity guide for researchers working in landscape connectivity that could help them choosing the most suited method for their own case studies. In particular, we aim to: 1) provide a brief theoretical background behind structural connectivity methods; 2) deliver a brief synthesis of current strengths and weaknesses of structural connectivity methods; 3) update the previous work of Kool et al. (2013) by reviewing additional structural connectivity methods; 4) review recent advances in connectivity methods; and 5) identify research priorities that should be addressed in future studies.