DiscussionMonitoring ecological consequences of efforts to restore landscape-scale connectivity
Introduction
There has been a worldwide shift away from managing biodiversity within individual protected areas toward whole-of-landscape approaches (Worboys et al., 2010). This is partly because individual reserves are generally too small to support viable populations of many species, so multiple patches need to be connected by movements of individuals and genes to ensure persistence (Crooks and Sanjayan, 2006, Hilty et al., 2006). Moreover, with climates changing at unprecedented rates, the future of many ecosystems (even biomes; Moen et al., 2014) depends on the ability of species to adapt or track shifting regions of habitat suitability. Adaptation to new climates and range-shifting are more likely if populations are functionally large and genetically diverse, both of which are facilitated by ecological connectivity (Sgrò et al., 2011, Driscoll et al., 2012).
This growing appreciation that effective conservation needs large, connected populations has led to landscape-scale connectivity initiatives (or ‘connectivity conservation’ initiatives; Worboys et al., 2010) proliferating in governmental and non-governmental programs (Fig. 1). Several countries base their national conservation strategies on large-scale connectivity (e.g., DeClerck et al., 2010), with concepts like ‘defragmentation’ and ‘rewilding’ being increasingly used to frame policy discussions (Finchman et al., 2014, Drenthen and Keulartz, 2014, Nogués-Bravo et al., 2016). Rather than being motivated by explicit research questions, the intent is usually to manage or restore structural connectivity (physical links between areas) to facilitate movement of individuals and/or genes through the landscape or support large-scale abiotic processes (Soulé et al., 2004). Connectivity is typically viewed in terms of structural measures of habitat (e.g., tree-cover) but such measures may not relate directly to movement or permeability (Kadoya, 2009). That is, structural connectivity need not beget functional connectivity and the conditions required for movement by species vary widely, even within the same region (Amos et al., 2014; see ‘Definitions of connectivity concepts’ section, below). Furthermore, movement needed to support ecological and demographic processes may differ from that needed to support evolutionary processes (Lowe and Allendorf, 2010). Thus monitoring the ecological and evolutionary outcomes of attempts to enhance connectivity is critical to understand which approaches actually achieve their intended purpose.
A major impediment to monitoring connectivity conservation initiatives is that existing approaches to ecological monitoring focus on quantifying changes in metrics such as abundance of target species, species occurrence at patch scales (Worboys et al., 2010) or indirect measures such as habitat extent and configuration (Tischendorf and Fahrig, 2000). While these may be among the desired outcomes of connectivity management initiatives, such approaches do not quantify changes to connectivity nor their influence on biodiversity or ecological dynamics (including modified fire or flow regimes). Moreover, indirect measures of connectivity cannot distinguish proximate changes to populations and ecological processes from effects of habitat augmentation and/or improvement (Driscoll et al., 2014). Thus, conventional inventory- and habitat-based methods are often inappropriate for monitoring connectivity—misaligned with the immediate objectives of connectivity management and the spatial and temporal scales over which actions are expected to have desired effects (Kadoya, 2009, Gregory and Beier, 2014). New monitoring approaches are required to generate consistent and comparable measures of functional connectivity. An integrated approach is also critical to working across the spatial and temporal scales involved to inform on-ground management and restoration efforts in the context of landscape-scale conservation.
Implementing an effective strategy to monitor connectivity conservation initiatives necessarily involves more work but we argue that it is an essential investment rather than an ‘added extra’. Currently, we have no way of judging which on-ground method has the greatest effect on a population, how to make methods work more effectively, or whether these interventions are addressing the long-term objectives of initiatives. In addition to generating information critical for reporting and evaluating effectiveness for particular projects, monitoring multiple initiatives using comparable approaches would enhance our generalized understanding of how connectivity affects populations. For example, are more connected populations necessarily more resistant to stochastic events; does increased connectivity across landscapes reduce the likelihood of invasion by exotic species and resultant changes to community dynamics? By measuring relevant response variables consistently at multiple scales across multiple systems, the mechanistic basis of observed patterns can be revealed, and generalized answers to these questions will emerge, improving our ability to make robust predictions and extrapolate projected outcomes to new sites, species or systems.
To improve connectivity monitoring strategies, we developed a process to guide decisions about what, where, when and how to monitor connectivity management and restoration. Rather than a generic “how to design a connectivity conservation monitoring strategy” or comparing the pros and cons of particular methods or objectives, we provide a novel framework for biologists, conservation managers and policy makers to align objectives of any initiative with planned actions, allowing them to determine how best to monitor the effectiveness of those actions in achieving the stated objectives. We build a conceptual model that makes explicit the many hypothesised links from on-ground connectivity management to organismal movement to the demographic parameters that define population processes and finally to the ultimate conservation outcomes intended. We embed this model within an adaptive management framework (Westgate et al., 2013) to provide a decision-support tool that links objectives to achievable monitoring goals, advising on the most appropriate methods to use for understanding, managing and reporting effects of connectivity restoration. We provide a real-world example of the mismatch between best-practice monitoring applying our approach and the actual approach adopted, comparing how the two strategies relate to aspirational and practical objectives. Our model and decision framework can be used to coordinate monitoring programs to yield generalisable conclusions from diverse conservation initiatives while addressing some of the most fundamental questions in ecology (Sutherland et al., 2013).
Section snippets
Definitions of connectivity concepts
Any discussion of connectivity must begin by clarifying terminology, as key terms have been variously used in the literature. In our conceptual model and decision framework, we use the following definitions:
Structural connectivity refers to the physical arrangement of habitats within a landscape, and is typically measured as a landscape pattern without regard to species-specific movement processes or habitat needs (Tischendorf and Fahrig, 2000). Some recent treatments of the concept account for
Connectivity in complex landscapes
Landscape managers often assume that the relationships are relatively direct between on-ground actions to improve structural connectivity and long-term goals such as maintaining population viability and evolutionary potential, yet ecological theory suggests otherwise (Roshier and Reid, 2003, Bowler and Benton, 2005, Pierson et al., 2015 and references therein). Changes to connectivity are expected to have direct, proximate effects on movement processes, with the ultimate outcomes on population
A decision framework for connectivity monitoring in the real world
Since funds are usually limited, the ideal monitoring program suggested by the conceptual model is unlikely to be achievable within any single connectivity initiative. In this real-world context, informed decisions need to be made about the type and scale of data that best match the monitoring goals (e.g., learning, improving, reporting) and, thus, which goals are achievable with available resources. We therefore modified an established adaptive management framework (Westgate et al., 2013) to
Methods to monitor movement
Multiple methods are available for monitoring at each level of the model, with trade-offs between the complexity/expense of the method and the quality of the information/depth of understanding obtained. There is often an assumption that survey data on species occurrence (and thus tracking distributions and diversity for reporting purposes) are cheaper and easier to collect, making monitoring choices a foregone conclusion based on feasibility and cost. However, new methods for collecting data on
Our decision framework in practice
The Australian Capital Territory (ACT) government is consolidating and connecting over 60,000 ha of remnant box-gum grassy woodland along an urban to rural gradient. The ACT approached two of us (V. & E. Doerr) to develop a plan for monitoring the landscape-scale outcomes of this program of work with a particular focus on improvements in connectivity. We present this plan as a worked example of how our conceptual model and decision framework can inform choices about connectivity monitoring with
Prospect
Limits to funding and resources may mean that managers themselves will only be able to monitor at one level of the model and likely only for a small range of species. Partnerships with researchers, community groups and citizen science initiatives can facilitate more comprehensive monitoring if explicitly linked (Bird et al., 2014). In particular, this allows comparison of a range of species with different dispersal abilities, helping discern relationships between management actions and multiple
Acknowledgments
We acknowledge the financial support of the New South Wales Government's Environmental Trust and the Great Eastern Ranges Initiative (courtesy of a Slopes to Summit partnership grant) and the Australian Capital Territory Environment and Sustainable Development Directorate. We thank Gary Howling, Sam Niedra, and Kylie Durant for their invaluable workshop contributions and feedback on an earlier version. RvdR was supported by The Baker Foundation.
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