Thomas Newsome of Oregon State University talked about his work with William Ripple on a trophic cascade involving wolves, coyotes, and foxes. He pointed out that carnivores in North America–including the wolverine, gray wolf, cougar, and lynx–have undergone large range contractions. The role of wilderness areas in their recoveries is a big unanswered question. He posited that wolves suppress coyotes and elk, and that there are indirect positive benefits to both of these suppressions. For example, he hypothesized, wolves suppress coyotes, which might in turn benefit red foxes. Wolves suppress coyotes through direct predation and also because coyotes avoid areas where wolves persist. Coyotes and wolves have greater dietary overlap than wolves and foxes, so they compete. Foxes could benefit from carcasses wolves left behind.
So, he predicted that there would be more red foxes than coyotes in the presence of wolves. He looked at this on a really broad scale across North America, and also across a really broad temporal scale using data sets that go back to the 1910s and 1930s. These data supported his hypothesis. He also looked at a region, Saskatchewan, that included areas without wolves and areas with wolves for a more detailed analysis of this relationship. He showed that in the wolf range, coyote numbers go down, but that there is a large “transition zone” of as much as 200 km where coyote numbers are still high over the border of wolf ranges. This result led him to think about how much wilderness is enough, with such large transition zones, and the role of other lands (such as agricultural lands) in augmenting ranges of these carnivores.
Wendy Loya of The Wilderness Society Alaska talked about her work studying caribou migrations with coauthor Ryan Wilson. She started by saying that North America is home to important national and international migration pathways, from offshore whales to migratory birds, to monarch butterflies. In 1980, President Carter signed the Alaska National Interest Lands Conservation Act, which designated a whopping 56 million acres of wilderness–an “amazing conservation estate.” Alaska’s caribou herds are important migrators through these areas. For example, the largest of them, the Western Arctic herd, takes up about one third of Alaska. This herd experiences a wilderness landscape throughout its migration range. Loya wanted to know what the cost of any one path was for all herds. She found that in the fall migration, the caribou’s pathways avoid high elevations (>2,000 m), steep slopes (>40%), and crossing first-order rivers or dense vegetation. In the spring migration, they avoid high elevations (>1,000 m), steep slopes (60%), and dense vegetation, but they made less effort to avoid large rivers, because they are often still frozen and easily crossed. She also found that caribou responded to a gravel industrial road with fairly regular traffic that extended 40 miles into the wilderness among their 1,000 mile migration. However, there were different “camps” among a herd: Some crossed the road without hesitation, others stopped at the road and delayed crossing before finally doing so, some avoided the road for awhile and then crossed, and some just would not cross and traveled the miles to go around it. She showed that those that cross the road go significantly further south than those that don’t, but that she and her colleagues don’t yet know if that’s favorable or unfavorable behavior at this point. Eighty-eight percent of “normal” caribou (those that crossed) and 77% of the “deflectors” were likely to come close to a community, and the “normal” were more likely to come nearer to the community than the “deflectors.” She plans to analyze the expanded range of development scenarios to guide development away from migration pathways critical to the caribou.
Jonathan Greenberg talked about the effect of foreclosures on land cover, using a map that combined foreclosures and lawn greenness in Maricopa County, AZ during the period from 2002 to 2012. Each year, he measured number of foreclosures and greenness (using NDVI) for every grid cell at a resolution of 250 km (I think). He predicted that areas with high foreclosures should result in lower NDVI and vice versa, because lawns were not watered on vacant property or because such property was replaced by something impermeable (buildings or pavement). He also predicted that this relationship would be stable across years. He showed that indeed areas with low foreclosures showed high greenness and vice versa. Next, he hopes to track individual locations over time and at higher resolution, teasing apart lawns, wooded areas, and xeriscapes.
Jacquelyn Gill, whose talk at last year’s ESA I also summarized, talked about the novel plant associations that arose during the novel climates of the last deglaciation, especially in the midwestern and eastern US. She showed that pollen assemblages that are highly dissimilar to the present plant assemblages arose immediately following the extinction of megaherbivores. Unusual combinations of plants (by today’s standards) were found then: For example, in Indiana, temperate deciduous taxa lived alongside boreal conifers, which don’t mix much today. From northwest to southeast, the peak in such vegetation dissimilarity occurred around the same time. She used an ordination technique called non-metric multidimensional scaling to show assemblage changes over time. About 11,700 years ago, she observed changes toward the modern assemblages we see today. Changes in assemblages from the late Pleistocene to early Holocene correspond to big climatic events. Ash in particular was a major component of the no-analog sites that she documented, and Gill suggested that herbivory might have been a driver of its ubiquity. She noted, however, that performance of ash across sites is variable, probably because topography and proximity to the ice sheet affected the tree’s performance. She noted that shifts in assemblage could occur over the timescale of a couple of decades or less.
Jonathan London of UC Davis spoke about his work studying the uptake of social and socio-spatial science in urban and regional planning. He noted that a core problem is limited uptake of urban sustainability science in urban policy. He has been studying what might account for the variation in uptake and what can be done to encourage it. He used several case studies from his work in the San Joaquin Valley and Sacramento. He rated five factors that could affect policy impact: relationships (between scientists and policymakers, e.g.), context (political, social), tools (mapping, measuring), technical capacity (of agencies, e.g.), and timing. In one case study in San Joaquin Valley, he helped develop an environmental justice mapping tool to help decisions about allocating cap and trade funds to communities. In another case study, he helped design tools to determine health impacts and community vulnerability. He noted that the biggest concern of the people in this area was unemployment and that planners felt people did not rally behind environmental justice because they did not understand any connection to that immediate concern. The best uptake was his work on environmental justice mapping in the San Joaquin Valley.
In all cases, relationships were very important to success. He noted that he needed to understand the conflicts between stakeholders so that he could be proactive about addressing them. In one situation, giving technical assistance built relationships, because it filled a need. Each case was funded differently, so his role in creating tools for others versus involving them in it varied. In Sacramento, they worked under contract with a regional government, and they designed social equity tools. The agency needed to pick transit priority areas. Cities and counties submitted 50 different proposals, but they could only pick 7. The mapping helped the decision-making. He also pointed out that in many cases staff don’t make decisions, so the tools are instrumental in their ability to tell a compelling story to their board. Also, capacity of the agency mattered in how they went about creating tools. If there were people to work on studying the details, they gave them the tools they needed, but in other cases, his team created a report using the tools.
He concluded that (1) sustainability science had to be understood as embedded in a political/economic/social context, (2) successful research translation requires fluency in multiple “languages” (policy, community, and science), and (3) the social science approach to organizational dynamics, policy analysis, and community/regional development was a crucial element.