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  1. Abstract

    How species richness scales spatially is a foundational concept of community ecology, but how biotic interactions scale spatially is poorly known. Previous studies have proposed interactions-area relationships (IARs) based on two competing relationships for how the number of interactions scale with the number of species, the ‘link-species scaling law’ and the ‘constant connectance hypothesis.’ The link-species scaling law posits that the number of interactions per species remains constant as the size of the network increases. The constant connectance hypothesis says that the proportion of realized interactions remains constant with network size. While few tests of these IARs exist, evidence for the original interactions-species relationships are mixed. We propose a novel IAR and test it against the two existing IARs. We first present a general theory for how interactions scale spatially and the mathematical relationship between the IAR and the species richness-area curve. We then provide a new mathematical formulation of the IAR, accounting for connectance varying with area. Employing data from three mutualistic networks (i.e. a network which specifies interconnected and mutually-beneficial interactions between two groups of species), we evaluate three competing models of how interactions scale spatially: two previously published IAR models and our proposed IAR. We find the new IAR described by our theory-based equation fits the empirical datasets equally as well as the previously proposed IAR based on the link-species scaling law in one out of three cases and better than the previously-proposed models in two out of three cases. Our novel IAR improves upon previous models and quantifies mutualist interactions across space, which is paramount to understanding biodiversity and preventing its loss.

     
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  2. Abstract

    Determining factors that shape a species’ population genetic structure is beneficial for identifying effective conservation practices. We assessed population structure and genetic diversity for Saltmarsh Sparrow (Ammospiza caudacuta), an imperiled tidal marsh specialist, using 13 microsatellite markers and 964 individuals sampled from 24 marshes across the breeding range. We show that Saltmarsh Sparrow populations are structured regionally by isolation-by-distance, with gene flow occurring among marshes within ~110 to 135 km of one another. Isolation-by-resistance and isolation-by-environment also shape genetic variation; several habitat and landscape features are associated with genetic diversity and genetic divergence among populations. Human development in the surrounding landscape isolates breeding marshes, reducing genetic diversity, and increasing population genetic divergence, while surrounding marshland and patch habitat quality (proportion high marsh and sea-level-rise trend) have the opposite effect. The distance of the breeding marsh to the Atlantic Ocean also influences genetic variation, with marshes farther inland being more divergent than coastal marshes. In northern marshes, hybridization with Nelson’s Sparrow (A. nelsoni) strongly influences Saltmarsh Sparrow genetic variation, by increasing genetic diversity in the population; this has a concomitant effect of increasing genetic differentiation of marshes with high levels of introgression. From a conservation perspective, we found that the majority of population clusters have low effective population sizes, suggesting a lack of resiliency. To conserve the representative breadth of genetic and ecological diversity and to ensure redundancy of populations, it will be important to protect a diversity of marsh types across the latitudinal gradient of the species range, including multiple inland, coastal, and urban populations, which we have shown to exhibit signals of genetic differentiation. It will also require maintaining connectivity at a regional level, by promoting high marsh habitat at the scale of gene flow (~130 km), while also ensuring “stepping stone” populations across the range.

     
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  3. Abstract

    Conceptual models are necessary to synthesize what is known about a topic, identify gaps in knowledge and improve understanding. The process of developing conceptual models that summarize the literature using ad hoc approaches has high potential to be incomplete due to the challenges of tracking information and hypotheses across the literature.

    We present a novel, systematic approach to conceptual model development through qualitative synthesis and graphical analysis of hypotheses already present in the scientific literature. Our approach has five stages: researchers explicitly define the scope of the question, conduct a systematic review, extract hypotheses from prior studies, assemble hypotheses into a single network model and analyse trends in the model through network analysis.

    The resulting network can be analysed to identify shifts in thinking over time, variation in the application of ideas over different axes of investigation (e.g. geography, taxonomy, ecosystem type) and the most important hypotheses based on the network structure. To illustrate the approach, we present examples from a case study that applied the method to synthesize decades of research on the effects of forest fragmentation on birds.

    This approach can be used to synthesize scientific thinking across any field of research, guide future research to fill knowledge gaps efficiently and help researchers systematically build conceptual models representing alternative hypotheses.

     
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  4. Abstract

    Reports of declines in abundance and biomass of insects and other invertebrates from around the world have raised concerns about food limitation that could have profound impacts for insectivorous species. Food availability can clearly affect species; however, there is considerable variation among studies in whether this effect is evident, and thus a lack of clarity over the generality of the relationship. To understand how decreased food availability due to invertebrate declines will affect bird populations, we conducted a systematic review and used meta‐analytic structural equation modelling, which allowed us to treat our core variables of interest as latent variables estimated by the diverse ways in which researchers measure fecundity and chick body condition. We found a moderate positive effect of food availability on chick body condition and a strong positive effect on reproductive success. We also found a negative relationship between chick body condition and reproductive success. Our results demonstrate that food is generally a limiting factor for breeding songbirds. Our analysis also provides evidence for a consistent trade‐off between chick body condition and reproductive success, demonstrating the complexity of trophic dynamics important for these vital rates.

     
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  5. Abstract

    The interdisciplinary nature of conservation problems is increasingly being incorporated into research, raising fundamental questions about the relative importance of the different types of knowledge and data. Although there has been extensive research on the development of methods and tools for conservation planning, especially spatial planning, comparatively little is known about the relative importance of ecological versus non-ecological data for prioritization, or the likely return on investment of incorporating better data. We demonstrate a simple approach for (1) quantifying the sensitivity of spatial planning results to different ecological and non-ecological data layers, and (2) estimating the potential gains in efficiency from incorporating additional data. Our case study involves spatial planning for coastal squeeze, a process by which development blocks coastal ecosystems from moving landward in response to sea-level rise. We show that incorporating spatial data on landowners’ likelihood of selling had little effect on identifying relative priorities but drastically changed the outlook for whether conservation goals could be achieved. Better data on the costs of conservation actions had the greatest potential to improve the efficiency of spatial planning, in some cases generating more than an order of magnitude greater cost savings compared to ecological data. Our framework could be applied to other systems to guide the development of spatial planning and to identify general rules of thumb for the importance of alternative data sources for conservation problems in different socio-ecological contexts.

     
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  7. Abstract

    Habitat loss disrupts species interactions through local extinctions, potentially orphaning species that depend on interacting partners, via mutualisms or commensalisms, and increasing secondary extinction risk. Orphaned species may become functionally or secondarily extinct, increasing the severity of the current biodiversity crisis. While habitat destruction is a major cause of biodiversity loss, the number of secondary extinctions is largely unknown. We investigate the relationship between habitat loss, orphaned species, and bipartite network properties. Using a real seed dispersal network, we simulate habitat loss to estimate the rate at which species are orphaned. To be able to draw general conclusions, we also simulate habitat loss in synthetic networks to quantify how changes in network properties affect orphan rates across broader parameter space. Both real and synthetic network simulations show that even small amounts of habitat loss can cause up to 10% of species to be orphaned. More area loss, less connected networks, and a greater disparity in the species richness of the network's trophic levels generally result in more orphaned species. As habitat is lost to land‐use conversion and climate change, more orphaned species increase the loss of community‐level and ecosystem functions. However, the potential severity of repercussions ranges from minimal (no species orphaned) to catastrophic (up to 60% of species within a network orphaned). Severity of repercussions also depends on how much the interaction richness and intactness of the community affects the degree of redundancy within networks. Orphaned species could add substantially to the loss of ecosystem function and secondary extinction worldwide.

     
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