Ecological metrics predict connectivity better than geographic distance

Green infrastructure connectivity analysis across spatiotemporal scales: A transferable approach in the Ruhr Metropolitan Area, Germany

Developing green infrastructure (GI) has drawn increasing attention as a strategic planning approach for advancing urban sustainability. The connectivity of green spaces, a central principle of GI, has been considered in planning studies regarding its structure and functions for biodiversity conservation and ecosystem services delivery; however, aspects of GI connectivity across temporal and spatial scales are rarely addressed. This paper aims to develop and apply a method for the GI connectivity analysis at multiple spatiotemporal scales. A transferable and multi-scale workable approach is presented to reveal the changes of structural and spatial heterogeneity of urban GI. Our method includes i) morphological spatial patterns analysis for central and green corridors recognition, ii) a graph-based quantification of GI connectivity based on the Conefor model, and iii) least-cost path analysis for identifying potential green corridors. We apply the GI connectivity analysis method in the Ruhr Metropolitan Area (RMA), one of Europe's largest agglomerations. We use spatial Urban Atlas data from 2006 to 2018. At the metropolitan scale, we find that GI connectivity in the RMA decreases 3.9% from 2006 to 2018, even though the general distributions of GI changes only slightly. With reference to the municipal scale from 2006 to 2018, four major types of GI connectivity changes were discovered in RMA's 15 cities, namely consistent decreasing, consistent increasing, increase followed by decrease, and vice-versa. Our findings provide new evidence on GI connectivity changes across a twelve-year difference and at metropolitan and municipal scales, as well as the identification of priority areas for increasing GI connectivity. It provides insights on the evolving and heterogenous nature of GI connectivity in support of decision-making for more sustainable metropolitan development for people and nature.

Conservation and Management Strategies Create Opportunities for Integrative Organismal Research

Conservation and management activities are geared toward the achievement of particular goals for a specific species, or groups of species, at the population level or higher. Conversely, organismal or functional research is typically organized by hypothesis tests or descriptive work that examines a broader theory studying individual organismal traits. Here, we outline how integrative organismal biologists might conduct mutually beneficial and meaningful research to inform or assist conservation and management biologists. We argue that studies of non-target species are very useful to both groups because non-target species can meet the goals of managers and organismal biologists alike, while also informing the other. We highlight our work on a threatened lizard species' thermal physiology, behavior, and color pattern-all of which are impacted by species management plans for sympatric, threatened, bird species. We show that management practices affect activity time, thermal adaptation, and substrate use, while also altering predation rates, crypsis, ectoparasite load, and sexual coloration in the study species. These case studies exemplify the challenges of conservation and management efforts for threatened or endangered species in that non-target species can be both positively and negatively affected by those efforts. Yet, the collaboration of organismal biologists with conservation and management efforts provides a productive system for mutually informative research.

Physiological vagility and its relationship to dispersal and neutral genetic heterogeneity in vertebrates

Vagility is the inherent power of movement by individuals. Vagility and the available duration of movement determine the dispersal distance individuals can move to interbreed, which affects the fine-scale genetic structure of vertebrate populations. Vagility and variation in population genetic structure are normally explained by geographic variation and not by the inherent power of movement by individuals. We present a new, quantitative definition for physiological vagility that incorporates aerobic capacity, body size, body temperature and the metabolic cost of transport, variables that are independent of the physical environment. Physiological vagility is the speed at which an animal can move sustainably based on these parameters. This meta-analysis tests whether this definition of physiological vagility correlates with empirical data for maximal dispersal distances and measured microsatellite genetic differentiation with distance {[F(ST)/[1-F(ST))]/ln distance} for amphibians, reptiles, birds and mammals utilizing three locomotor modes (running, flying, swimming). Maximal dispersal distance and physiological vagility increased with body mass for amphibians, reptiles and mammals utilizing terrestrial movement. The relative slopes of these relationships indicate that larger individuals require longer movement durations to achieve maximal dispersal distances. Both physiological vagility and maximal dispersal distance were independent of body mass for flying vertebrates. Genetic differentiation with distance was greatest for terrestrial locomotion, with amphibians showing the greatest mean and variance in differentiation. Flying birds, flying mammals and swimming marine mammals showed the least differentiation. Mean physiological vagility of different groups (class and locomotor mode) accounted for 98% of the mean variation in genetic differentiation with distance in each group. Genetic differentiation with distance was not related to body mass. The physiological capacity for movement (physiological vagility) quantitatively predicts genetic isolation by distance in the vertebrates examined.

The sensitivity of genetic connectivity measures to unsampled and under-sampled sites

Landscape genetic analyses assess the influence of landscape structure on genetic differentiation. It is rarely possible to collect genetic samples from all individuals on the landscape and thus it is important to assess the sensitivity of landscape genetic analyses to the effects of unsampled and under-sampled sites. Network-based measures of genetic distance, such as conditional genetic distance (cGD), might be particularly sensitive to sampling intensity because pairwise estimates are relative to the entire network. We addressed this question by subsampling microsatellite data from two empirical datasets. We found that pairwise estimates of cGD were sensitive to both unsampled and under-sampled sites, and F_ST, D_est, and d_eucl were more sensitive to under-sampled than unsampled sites. We found that the rank order of cGD was also sensitive to unsampled and under-sampled sites, but not enough to affect the outcome of Mantel tests for isolation by distance. We simulated isolation by resistance and found that although cGD estimates were sensitive to unsampled sites, by increasing the number of sites sampled the accuracy of conclusions drawn from landscape genetic analyses increased, a feature that is not possible with pairwise estimates of genetic differentiation such as F_ST, D_est, and d_eucl. We suggest that users of cGD assess the sensitivity of this measure by subsampling within their own network and use caution when making extrapolations beyond their sampled network.

Connectivity among populations of pygmy whitefish (Prosopium coulterii) in northwestern North America inferred from microsatellite DNA analyses

We studied microsatellite DNA variation in 15 populations of northwestern North American pygmy whitefish ( Prosopium coulterii (Eigenmann and Eigenmann, 1892)), an enigmatic freshwater fish thought to be highly fragmented by residency in deep, cold postglacial lakes. Population subdivision (θ) across 10 loci was 0.12 (P < 0.001) across samples, but one western Alaskan population was more divergent than all others (θ = 0.31–0.41, P < 0.001). Within the Williston Reservoir watershed (WRW), θ averaged 0.08 (P < 0.001) and was positively associated with both the geographic distance between localities (r2 = 0.36, P < 0.001) and the number of branch points interconnecting them (r2 = 0.33, P < 0.001). Differentiation among populations was modeled as the sum of the genetic distances for the stream sections interconnecting them (r2 = 0.74). Differences among subwatersheds with the WRW accounted for 5.1% of the total variation in allele frequencies (P < 0.001). Assignment tests suggested limited movement among lakes, with most inferred dispersal between adjacent watersheds. Coalescent analysis strongly supported a gene flow–drift equilibrium model of population structure over a drift-only model. Effective management of diversity in pygmy whitefish requires the maintenance of stream networks that interconnect lakes within a watershed.