Citation: Pitcher, K. A., and D. A. Soluk. 2016. Inter-patch connectivity and intra-patch structure differentially alter prey consumption by multiple predators. Ecosphere 7(11):e01598. 10.1002/ecs2.1598 Abstract. 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% AE 4.6%) compared with long treatments (19% AE 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% AE 6.0%) than at low plant density (38% AE 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.
Differences in habitat use and dispersal responses among competing species are mechanisms that may influence patterns of coexistence. Predaceous diving beetles (Coleóptera: Dytiscidae) are a model group for testing these potential coexistence mechanisms because they are abundant, interact in finite habitats, and are mobile among habitats. We focused on two morphologically similar species, Lacco/^hihis fasciatus rufus (Aube) and Laccophilus proximus (Say), to determine if mechanisms exist that help to explain patterns of their coexistence. Behavioral observations and feeding trials in the laboratory, a field experiment, and a mesocosm experiment were used to determine if habitat use, prey consumption, or dispersal rates of these two species were inherently different or changed when in the presence of intra-or interspecific competitors. We found no difference between habitat use or prey consumption between species in constant depth aquaria, and no effect of intra-or interspecifics on their behaviors. In variable depth aquaria, L. proximus occupied significantly shallower habitat when compared with L. f rufus; in the former this difference only occurred between conspecific treatments. Field collections confirmed that L. proximus occupied shallower habitats than L. / rufus. In field mesocosms, L. proximus displayed higher dispersal rates than L. / rufus. These species also do not appear food limited in the field, suggesting that adult competition for food is unlikely. L.f. rufus and L. proximus exhibit different habitat use and dispersal responses, but this does not seem to be in response to intra-or interspecific competitive interactions.KEY WORDS behavior, habitat use, dispersal, Laccophilus, temporary aquatic habitat Factors promoting the coexistence of species within a terns. Compared with other families of aquatic insects, community have traditionally been attributed to the communities of these beetles have a relatively high varying propensities ofdifferent species to avoid pred-biodiversity of interacting species concentrated ators, compete, or tolerate stress at the local level within small habitat areas (g., preecologists have also investigated the importance of dation, competition) occur both within and among behavioral habitat use (Preisser et al. 2007, Yee 2010, habitats, and can be affected by multiple processes Woodcock and Heard 2011) and dispersal at the land-across varying scales; a variety of coexistence, coscape level (Rundle et al. 2002, Bowler and Benton occurrence, and exclusion patterns of these aquatic 2005, Yee et al. 2009) as potential mechanisms pro-insect species can result (Larson 1985, Kholin and motingboth the coexistence and exclusion of species Nilsson 1998, Carrido and Munilla 2008). Understandwithin a community. Though not as easily quantified,ing the spatial, resource, and behavioral based mechand often underlying the larger factors already un-anisms that affect the community structure of these derstood to influence coexistence (e.g., competition, aquatic beetles within ephemeral ha...
Citation: Pitcher, K. A., and D. A. Soluk. 2018. Fish presence and inter-patch connectivity interactively alter the size of emergent insects in experimental enclosures. Ecosphere 9(3):e02118. 10.1002/ecs2.2118Abstract. 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% AE 7.6, mean AE 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 AE 0.1 mg/m 2 compared to 3.3 mg/m 2 AE 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% AE 6.9) compared to short inter-patch distance treatments (20.5% AE 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 predatorprey dynamics can then have cascading effects on adjacent habitats by influencing the abundance, trophic composition, and quality of exported trophic subsidies.
Bats play crucial ecological roles and provide valuable ecosystem services, yet many populations face serious threats from various ecological disturbances. The North American Bat Monitoring Program (NABat) aims to use its technology infrastructure to assess status and trends of bat populations, while developing innovative and community‐driven conservation solutions. Here, we present NABat ML, an automated machine‐learning algorithm that improves the scalability and scientific transparency of NABat acoustic monitoring. This model combines signal processing techniques and convolutional neural networks (CNNs) to detect and classify recorded bat echolocation calls. We developed our CNN model with internet‐based computing resources (‘cloud environment’), and trained it on >600,000 spectrogram images. We also incorporated species range maps to improve the robustness and accuracy of the model for future ‘unseen’ data. We evaluated model performance using a comprehensive, independent, holdout dataset. NABat ML successfully distinguished 31 classes (30 species and a noise class) with overall weighted‐average accuracy and precision rates of 92%, and ≥90% classification accuracy for 19 of the bat species. Using a single cloud‐environment computing instance, the entire model training process took <16 h. Synthesis and applications. Our convolutional neural network (CNN)‐based model, NABat ML, classifies 30 North American bat species using their recorded echolocation calls with an overall accuracy of 92%. In addition to providing highly accurate species‐level classification, NABat ML and its outputs are compatible with Bayesian and other statistical techniques for measuring uncertainty in classification. Our model is open‐source and reproducible, enabling future implementations as software on end‐user devices and cloud‐based web applications. These qualities make NABat ML highly suitable for applications ranging from grassroots community science initiatives to big‐data methods developed and implemented by researchers and professional practitioners. We believe the transparency and accessibility of NABat ML will encourage broad‐scale participation in bat monitoring, and enable development of innovative solutions needed to conserve North American bat species.
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