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Structural habitat complexity (SHC) and functional habitat connectivity (FHC) are the basic components that make up the physical architecture of an ecosystem, and can have substantial impacts on predator–prey interactions. These structural components influence animal behaviors such as inter‐patch movement, foraging, and competition, and can impact community structure/dynamics in terrestrial and aquatic ecosystems. The effects of SHC and FHC on predator–prey dynamics within an ecosystem may also have important cascading effects on neighboring ecosystems by altering the movement of individuals across ecosystem boundaries. For example, when aquatic insects emerge as adults, they enter terrestrial ecosystems where they become an important food resource for terrestrial predators. Using a multiple patch, predator enclosure design in ponds, we tested whether altering intra‐patch plant stem densities (SHC) and inter‐patch distances (FHC) would influence the impact a predatory fish has on the biomass, quality, and trophic composition of emergent insects. As expected, fish significantly reduced emergent insect biomass (33% ± 7.6, mean ± SE). Intra‐patch stem densities (SHC) did not significantly alter fish effects; however, inter‐patch distance (FHC) did significantly alter the impact of fish on the size of some emergent insects. Damselflies that emerged in treatments with fish present and shorter inter‐patch distances were significantly larger, 4.1 ± 0.1 mg/m2 compared to 3.3 mg/m2 ± 0.1 in the long/fish treatments. In fish treatments, this effect on damselfly size resulted in greater reductions in total emergent insect biomass in long inter‐patch distance treatments (47.3% ± 6.9) compared to short inter‐patch distance treatments (20.5% ± 12.4). Our results suggest that physical components of a habitat, such as inter‐patch distances, have important impacts on predator–prey dynamics within habitats. These altered predator–prey dynamics can then have cascading effects on adjacent habitats by influencing the abundance, trophic composition, and quality of exported trophic subsidies.

Structural habitat complexity ( SHC ) and functional habitat connectivity ( FHC ) have important effects on predator–prey interactions and exert a strong influence on community structure/dynamics in terrestrial and aquatic ecosystems. Although these factors vary simultaneously in most systems, their interactive effects are poorly understood. Using artificial pond mesocosms and multiple prey types, we manipulated plant density ( SHC : low, high) and inter‐patch distance ( FHC : short, long) in a full factorial design to test for potential interactive effects of these factors on competition and predation by a dragonfly larva ( Anax junius ) and fish predator ( Lepomis cyanallus ). When inter‐patch distances ( FHC ) were short, A. junius consumed more amphipods (36% ± 4.6%) compared with long treatments (19% ± 4.8%). We detected no significant effects of plant density ( SHC ) on prey consumption by A. junius . There were significant interactive effects of FHC and SHC on Lepomis cyanellus consumption of amphipods and damselflies. The most counterintuitive of these effects was that sunfish consumed more larval damselflies at high plant density (64% ± 6.0%) than at low plant density (38% ± 8.6%) but only in short connection treatments. This interactive effect of SHC and FHC on damselfly predation by L. cyanellus was likely because damselflies exhibited riskier behavior at higher SHC . Prey consumption with both predators present was additive, but no significant effect of either SHC or FHC on interspecific predation was detected, suggesting compensatory foraging responses. Structural habitat complexity and FHC interactively influence predator foraging behavior in complex, non‐intuitive ways that are highly dependent on the predator/prey combination in question. Structural habitat complexity and FHC are currently being influenced by anthropogenic factors in multiple ways (e.g., habitat loss, global climate change), and being able to predict the responses of biotic communities to these changes should be an important consideration in restoration and conservation efforts.

Corridors are expected to increase species dispersal in fragmented habitats. However, it remains unclear how the quality of corridors influences the dispersal process, and how it interacts with corridor length and width. Here we investigate these factors using a small-scale laboratory system where we track the dispersal of the model organism Collembola Folsomia candida. Using this system, we study the effects of corridor length, width, and quality on the probability of dispersal, net movement, body size of dispersers, and the rate of change in population size after colonization. We show that corridor quality positively affected dispersal probability, net movement, and the rate of change in population size in colonised patches. Moreover, corridor quality significantly affected the size of dispersers, with only larger individuals dispersing through poor quality corridors. The length and width of corridors affected both the rate at which populations increased in colonised patches and the net number of individuals which dispersed, suggesting that these physical properties may be important in maintaining the flow of individuals in space. Our results thus suggest that corridor quality can have an important role in determining not only the probability of dispersal occurs but also the phenotypes of the individuals which disperse, with concomitant effects on the net movement of individuals and the rate of change in population size in the colonised patches.

Distance measure plays a critical role in various applications of polarimetric synthetic aperture radar (PolSAR) image data. In recent decades, plenty of distance measures have been developed for PolSAR image data from different perspectives, which, however, have not been well analyzed and summarized. In order to make better use of these distance measures in algorithm design, this paper provides a systematic survey of them and analyzes their relations in detail. We divide these distance measures into five main categories (i.e., the norm distances, geodesic distances, maximum likelihood (ML) distances, generalized likelihood ratio test (GLRT) distances, stochastics distances) and two other categories (i.e., the inter-patch distances and those based on metric learning). Furthermore, we analyze the relations between different distance measures and visualize them with graphs to make them clearer. Moreover, some properties of the main distance measures are discussed, and some advice for choosing distances in algorithm design is also provided. This survey can serve as a reference for researchers in PolSAR image processing, analysis, and related fields.

We tested whether Tundra Swans use information on the spatial distribution of cryptic food items (belowground Sago pondweed tubers) to shape their movement paths. In a continuous environment, swans create their own food patches by digging craters, which they exploit in several feeding bouts. Series of short (<1 m) intra-patch movements alternate with longer inter-patch movements (>1 m). Tuber biomass densities showed a positive spatial auto-correlation at a short distance (<3 m), but not at a larger distance (3-8 m). Based on the spatial pattern of the food distribution (which is assumed to be pre-harvest information for the swan) and the energy costs and benefits for different food densities at various distances, we calculated the optimal length of an inter-patch movement. A swan that moves to the patch with the highest gain rate was predicted to move to the adjacent patch (at 1 m) if the food density in the current patch had been high (>25 g/m⁲) and to a more distant patch (at 7-8 m) if the food density in the current patch had been low (<25 g/m⁲). This prediction was tested by measuring the response of swans to manipulated tuber densities. In accordance with our predictions, swans moved a long distance (>3 m) from a low-density patch and a short distance (<3 m) from a high-density patch. The quantitative agreement between prediction and observation was greater for swans feeding in pairs than for solitary swans. The result of this movement strategy is that swans visit high-density patches at a higher frequency than on offer and, consequently, achieve a 38% higher long-term gain rate. Swans also take advantage of spatial variance in food abundance by regulating the time in patches, staying longer and consuming more food from rich than from poor patches. We can conclude that the shape of the foraging path is a reflection of the spatial pattern in the distribution of tuber densities and can be understood from an optimal foraging perspective.