1. CH15: Connectivity and Landscape
Management

2. FIGURE 15.1 Low-connectivity landscape.
Satellite image of forests in Ghana. The influence of protection is visible; the irregular shapes of remaining forest fragments correspond exactly to the outlines of forest reserves (dotted lines). The large areas in which connectivity has been lost are plainly visible in almost all areas not protected. These areas are now agricultural landscapes, making reconnection difficult. Source: From United Nations Environment Programme.

3. FIGURE 15.2 A high-connectivity forest landscape.
Planning for broad-scale connectivity is still possible in this Canadian forest. Source: Courtesy of WRI Features.

4. FIGURE 15.3 Jaguar and the landscape species concept.
The jaguar, Panthera onca, is a large carnivore that has been used as an icon for establishing landscape connectivity (left). Paseo Panthera is a network of connected protected areas intended to allow passage of jaguar across Central America. This provides important connectivity for range shifts, even though it was not specifically designed for climate change. The landscape species concept (right) can be used to design connectivity for iconic species. Species’ needs at different times of the year or different stages of live history are mapped in the landscape and connectivity between these key resources can be a goal of landscape conservation. The map illustrates landscape species needs for a hypothetical large mammal. Because different elements in the landscape can be affected differently by climate change, the landscape species approach is a useful concept for climate change planning. Source: From Wikimedia Commons and Sanderson et al. (2002).

5. FIGURE 15.4 Migratory bird flyways, Europe and Africa.
Migratory pathways, such as these flyways, are highly likely to shift temporarily or spatially owing to climate change. Conservation responses to anticipate and track these changes are needed. Source: Courtesy of Born to Travel Campaign, BirdLife International.

6. FIGURE 15.5 Chains of connectivity.
Protecting chains of connectivity is one way to ensure species representation in protected areas as climate changes. Green rectangles indicate planning units that have suitable climate for a target species at each time step. Arrows indicate “chains” of suitable habitat through time. Dispersal is limited to one 2-km cell per 10-year time step in this ant-dispersed plant species. Only one combination of cells provides a complete “chain” of habitat from 2000 to Source: Williams et al. (2005).

7. FIGURE 15.6 Building connectivity to existing protection.
Choosing chains of suitable habitat that occur partly or entirely within existing protected areas helps create cost-effective solutions by minimizing the need for new protection. This map of the Cape Floristic Region shows existing protected areas (light green) and areas needed to conserve 300 species of proteas as climate changes (dark green), selected by conservation planning software. The planning software was programmed to represent complete chains of habitat, such as that illustrated in Figure 15.5, for all species. Where chains could not be represented in existing protected areas, new areas were selected for connectivity. Note that most new protected areas connect to existing protected areas. Source: Figure courtesy Steven Phillips.

8. FIGURE 15.7 Conservation, climate change and wine.
Shifts in suitability for wine grape growing by 2050, shown as level of agreement in an ensemble of general circulation models. The map shows model agreement on new areas (blue) becoming suitable and on existing areas losing suitability (red). Newly suitable areas include the Yellowstone to Yukon conservation area in North America (Inset A), where open grazing range is the most common land use. Vineyards may present serious new barriers to wildlife movement in these areas. In areas of declining suitability (e.g., Insets C and E), vineyards may use water to adapt to deteriorating growing conditions, placing pressure on water resources and riverine habitats. Source: Hannah et al. (2013).

9. FIGURE 15.8 Adaptation priorities defined by intersecting change in agriculture and biodiversity.
Climate change-driven losses in crop suitability (green) are shown with decline in climatic suitability for restricted-range birds (blue) by Intensity of color indicates level of agreement among multiple models and general circulation models. Areas of intersection (yellow–red) indicate areas in which agricultural change and decline in rare bird habitat suitability co-occur, areas in which collaborative planning between conservationists and agriculturalists may help avoid conservation blowback from shifting cropping patterns. Areas outlined in solid black show strong intersection by 2050, areas outlined with broken line show moderate intersection by Source: Hannah et al. (2013).

10. In systems in which predators and prey are not very diverse, population cycles often develop. Particularly when single species of prey and predator are involved, these cycles may be pronounced. For instance, lynx and hare populations in boreal forests may show strong cycles. When hare are abundant, lynx populations rise, and as predator density increases, hare populations cycle down. Lynx populations decrease soon after because of the lack of food, and then hare proliferate once predators are less abundant, starting the cycle anew. Similar effects are seen in wolf and moose populations on Isle Royale, Michigan (see figure). Prey populations (top panel) cycle with food availability that may be mediated by climate change. Modeling has shown that prey populations may be less vulnerable to crashes during climate change if healthy predator populations (bottom panel) exist to help keep them in check.

11. Sea surface temperature fronts (colors) off the southwest United States and northwest Mexico, shown with telemetry tracks from a blue whale (lines), illustrating the heavy use of these sea surface temperature features by large marine vertebrates (including billfish, turtles, and marine mammals). From Etnoyer et al. (2006).