Drafting Authors: Neil Adger, Pramod Aggarwal, Shardul Agrawala, Joseph Alcamo, Abdelkader Allali, Oleg Anisimov, Nigel Arnell, Michel Boko, Osvaldo Canziani, Timothy Carter, Gino Casassa, Ulisses Confalonieri, Rex Victor Cruz, Edmundo de Alba Alcaraz, William Easterling, Christopher Field, Andreas Fischlin, Blair Fitzharris, Carlos Gay García, Clair Hanson, Hideo Harasawa, Kevin Hennessy, Saleemul Huq, Roger Jones, Lucka Kajfež Bogataj, David Karoly, Richard Klein, Zbigniew Kundzewicz, Murari Lal, Rodel Lasco, Geoff Love, Xianfu Lu, Graciela Magrín, Luis José Mata, Roger McLean, Bettina Menne, Guy Midgley, Nobuo Mimura, Monirul Qader Mirza, José Moreno, Linda Mortsch, Isabelle Niang-Diop, Robert Nicholls, Béla Nováky, Leonard Nurse, Anthony Nyong, Michael Oppenheimer, Jean Palutikof, Martin Parry, Anand Patwardhan, Patricia Romero Lankao, Cynthia Rosenzweig, Stephen Schneider, Serguei Semenov, Joel Smith, John Stone, Jean-Pascal van Ypersele, David Vaughan, Coleen Vogel, Thomas Wilbanks, Poh Poh Wong, Shaohong Wu, Gary Yohe

Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change

Connectivity among populations and habitats is important for a wide range of ecological processes. Understanding, preserving, and restoring connectivity in complex landscapes requires connectivity models and metrics that are reliable, efficient, and process based. We introduce a new class of ecological connectivity models based in electrical circuit theory. Although they have been applied in other disciplines, circuit-theoretic connectivity models are new to ecology. They offer distinct advantages over common analytic connectivity models, including a theoretical basis in random walk theory and an ability to evaluate contributions of multiple dispersal pathways. Resistance, current, and voltage calculated across graphs or raster grids can be related to ecological processes (such as individual movement and gene flow) that occur across large population networks or landscapes. Efficient algorithms can quickly solve networks with millions of nodes, or landscapes with millions of raster cells. Here we review basic circuit theory, discuss relationships between circuit and random walk theories, and describe applications in ecology, evolution, and conservation. We provide examples of how circuit models can be used to predict movement patterns and fates of random walkers in complex landscapes and to identify important habitat patches and movement corridors for conservation planning.

https://www.jstor.org/stable/pdfplus/27650817.pdf

Using circuit theory to model connectivity in ecology, evolution, and conservation.

Resistance surfaces are often used to fill gaps in our knowledge surrounding animal movement and are frequently the basis for modeling connectivity associated with conservation initiatives. However, the methods for quantifying resistance surfaces are varied and there is no general consensus on the appropriate choice of environmental data or analytical approaches. We provide a comprehensive review of the literature on this topic to highlight methods used and identify knowledge gaps. Our review includes 96 papers that parameterized resistance surfaces (sometimes using multiple approaches) for a variety of taxa. Data types used included expert opinion (n = 76), detection (n = 23), relocation (n = 8), pathway (n = 2), and genetic (n = 28). We organized the papers into three main analytical approaches; one-stage expert opinion, one-stage empirical, and two-stage empirical, each of which was represented by 43, 22, and 36 papers, respectively. We further organized the empir- ical approaches into five main resource selection functions; point (n = 16), matrix (n = 38), home range (n = 3), step (n = 1), and pathway (n = 1). We found a general lack of justification for choice of environmental variables and their thematic and spatial representation, a heavy reliance on expert opinion and detection data, and a tendency to confound movement behavior and resource use. Future research needs include comparative analyses on the choice of envi- ronmental variables and their spatial and thematic scales, and on the various biological data types used to estimate resistance. Comparative analyses amongst analytical processes is also needed, as well as trans- parency in reporting on uncertainty in parameter estimates and sensitivity of final resistance surfaces, especially if the resistance surfaces are to be used for conservation and planning purposes.

Estimating landscape resistance to movement: a review

Measures of genetic structure among individuals or populations collected at different spatial locations across a landscape are commonly used as surrogate measures of functional (i.e. demographic or genetic) connectivity. In order to understand how landscape characteristics influence functional connectivity, resistance surfaces are typically created in a raster GIS environment. These resistance surfaces represent hypothesized relationships between landscape features and gene flow, and are based on underlying biological functions such as relative abundance or movement probabilities in different land cover types. The biggest challenge for calculating resistance surfaces is assignment of resistance values to different landscape features. Here, we first identify study objectives that are consistent with the use of resistance surfaces and critically review the various approaches that have been used to parameterize resistance surfaces and select optimal models in landscape genetics. We then discuss the biological assumptions and considerations that influence analyses using resistance surfaces, such as the relationship between gene flow and dispersal, how habitat suitability may influence animal movement, and how resistance surfaces can be translated into estimates of functional landscape connectivity. Finally, we outline novel approaches for creating optimal resistance surfaces using either simulation or computational methods, as well as alternatives to resistance surfaces (e.g. network and buffered paths). These approaches have the potential to improve landscape genetic analyses, but they also create new challenges. We conclude that no single way of using resistance surfaces is appropriate for every situation. We suggest that researchers carefully consider objectives, important biological assumptions and available parameterization and validation techniques when planning landscape genetic studies.

https://www.oriannesociety.org/sites/default/files/Spear_et_al_2010.pdf

Use of resistance surfaces for landscape genetic studies: considerations for parameterization and analysis

Graph theory is a body of mathematics dealing with problems of connectivity, flow, and routing in networks ranging from social groups to computer networks. Recently, network applications have erupted in many fields, and graph models are now being applied in landscape ecology and conservation biology, particularly for applications couched in metapopulation theory. In these applications, graph nodes represent habitat patches or local populations and links indicate functional connections among populations (i.e. via dispersal). Graphs are models of more complicated real systems, and so it is appropriate to review these applications from the perspective of modelling in general. Here we review recent applications of network theory to habitat patches in landscape mosaics. We consider (1) the conceptual model underlying these applications; (2) formalization and implementation of the graph model; (3) model parameterization; (4) model testing, insights, and predictions available through graph analyses; and (5) potential implications for conservation biology and related applications. In general, and for a variety of ecological systems, we find the graph model a remarkably robust framework for applications concerned with habitat connectivity. We close with suggestions for further work on the parameterization and validation of graph models, and point to some promising analytic insights.

https://www.onlinelibrary.wiley.com/doi/pdf/10.1111/j.1461-0248.2008.01271.x

Graph models of habitat mosaics

Models are commonly used to identify lands that will best maintain the ability of wildlife to move between wildland blocks through matrix lands after the remaining matrix has become incompatible with wildlife movement. We offer a roadmap of 16 choices and assumptions that arise in designing linkages to facilitate movement or gene flow of focal species between 2 or more predefined wildland blocks. We recommend designing linkages to serve multiple (rather than one) focal species likely to serve as a collective umbrella for all native species and ecological processes, explicitly acknowledging untested assumptions, and using uncertainty analysis to illustrate potential effects of model uncertainty. Such uncertainty is best displayed to stakeholders as maps of modeled linkages under different assumptions. We also recommend modeling corridor dwellers (species that require more than one generation to move their genes between wildland blocks) differently from passage species (for which an individual can move between wildland blocks within a few weeks). We identify a problem, which we call the subjective translation problem, that arises because the analyst must subjectively decide how to translate measurements of resource selection into resistance. This problem can be overcome by estimating resistance from observations of animal movement, genetic distances, or interpatch movements. There is room for substantial improvement in the procedures used to design linkages robust to climate change and in tools that allow stakeholders to compare an optimal linkage design to alternative designs that minimize costs or achieve other conservation goals.

http://corridordesign.org/dl/docs/Beier.Majka.Spencer.2008.ConsBiol.LinkageDesigns.pdf

Forks in the Road: Choices in Procedures for Designing Wildland Linkages

Least-cost models for focal species are widely used to design wildlife corridors. To evaluate the least-cost modeling approach used to develop 15 linkage designs in southern California, USA, we assessed robustness of the largest and least constrained linkage. Species experts parameterized models for eight species with weights for four habitat factors (land cover, topographic position, elevation, road density) and resistance values for each class within a factor (e.g., each class of land cover). Each model produced a proposed corridor for that species. We examined the extent to which uncertainty in factor weights and class resistance values affected two key conservation-relevant outputs, namely, the location and modeled resistance to movement of each proposed corridor. To do so, we compared the proposed corridor to 13 alternative corridors created with parameter sets that spanned the plausible ranges of biological uncertainty in these parameters. Models for five species were highly robust (mean overlap 88%, little or no increase in resistance). Although the proposed corridors for the other three focal species overlapped as little as 0% (mean 58%) of the alternative corridors, resistance in the proposed corridors for these three species was rarely higher than resistance in the alternative corridors (mean difference was 0.025 on a scale of 1- 10; worst difference was 0.39). As long as the model had the correct rank order of resistance values and factor weights, our results suggest that the predicted corridor is robust to uncertainty. The three carnivore focal species, alone or in combination, were not effective umbrellas for the other focal species. The carnivore corridors failed to overlap the predicted corridors of most other focal species and provided relatively high resistance for the other focal species (mean increase of 2.7 resistance units). Least-cost modelers should conduct uncertainty analysis so that decision-makers can appreciate the potential impact of model uncertainty on conservation decisions. Our approach to uncertainty analysis (which can be called a worst-case scenario approach) is appropriate for complex models in which distribution of the input parameters cannot be specified.

Uncertainty analysis of least-cost modeling for designing wildlife linkages

Background: While freshwater sustainability is generally defined as the provisioning of water for both people and the environment, in practice it is largely focused only on supplying water to furnish human population growth. Symptomatic of this is the state of Arizona, where rapid growth outside of the metropolitan Phoenix-Tucson corridor relies on the same groundwater that supplies year-round flow in rivers. Using Arizona as a case study, we present the first study in the southwestern United States that evaluates the potential impact of future population growth and water demand on streamflow depletion across multiple watersheds. Methodology/Principal Findings: We modeled population growth and water demand through 2050 and used four scenarios to explore the potential effects of alternative growth and water management strategies on river flows. Under the base population projection, we found that rivers in seven of the 18 study watersheds could be dewatered due to municipal demand. Implementing alternative growth and water management strategies, however, could prevent four of these rivers from being dewatered. Conclusions/Significance: The window of opportunity to implement water management strategies is narrowing. Because impacts from groundwater extraction are cumulative and cannot be immediately reversed, proactive water management strategies should be implemented where groundwater will be used to support new municipal demand. Our approach provides a low-cost method to identify where alternative water and growth management strategies may have the most impact, and demonstrates that such strategies can maintain a continued water supply for both people and the environment.

/pdf/sustainable-water-management-in-the-southwestern-united-31hlwc239m.pdf

Sustainable water management in the southwestern United States: reality or rhetoric?

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Forks in the Road: Choices in Procedures for Designing Wildland Linkages

Uncertainty analysis of least-cost modeling for designing wildlife linkages

Sustainable water management in the southwestern United States: reality or rhetoric?