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The spread of ecosystem modifying invasive plant (EMIP) species is one of the largest threats to native ecosystems in Hawaiʻi. However, differences in niche characteristics between Hawaiʻi's isolated insular environment and the wider global distribution of these species have not been carefully examined. We used species distribution modeling (SDM) methods to assess similarities and differences in niche characteristics between global and regional scales for 17 EMIPs present in Hawaiʻi. With a clearer understanding of the global context of regional plant invasion, we combined two SDM methods to better understand the potential future regional spread: (1) a nested modeling approach to integrate global and regional invasive species distribution projections; and (2) integrating all available agency and citizen science data to minimize the effect of monitoring gaps and biases. Our results show there are multiple similarities in niche characteristics across regional and global scales for most species, such as similar sets of climatic determinants of distribution, similar responses along environmental gradients, and moderate to high niche overlap between global and regional models. However, some differences were apparent and likely due to several factors including incomplete regional spread, community assembly or diversity effects. Invaders that established earlier showed a higher degree of niche overlap and similar environmental gradient responses when comparing global and regional models. This pattern, coupled with the tendency for regionally-based projections to predict narrower distributions than global projections, indicates a potential for continued spread of several invasive species across the Hawaiian landscape. Our study has broader implications for understanding the distribution and spread of invasive species in other regions, as similar analyses and models, including a novel way to characterize environmental gradient response differences across regions or scales, can likely provide valuable information for conservation and management efforts. [ABSTRACT FROM AUTHOR]

DRIFT (Downstream Response to Imposed Flow Transformation) is an interactive, ecological-social process and software package to assist with environmental flow assessments and river management decision-making. It was originally developed in the 1990s and has subsequently evolved and been applied in over 50 studies in Africa, South America, Asia and Europe. Early versions provided predicted ecological responses over time to specific flow changes, while the latest version provides responses to flow and non-flow drivers as seasonal time series. Here, an ecosystem or eco-social network is built for the river, with links between driver and responder indicators, and relationships created for each link. The network and relationships are developed and entered into the software by specialists based on available data and their knowledge. A range of scenarios is explored through the predicted indicator time series, discipline and site level ecological integrity, and social well-being. While DRIFT models vary in complexity, they are all based on relatively simple fundamental principles and arithmetic. Sequential averaging and summation through the system network is used to calculate an indicator's response to different drivers for successive seasons over time, while the discipline and site level summaries are found using weighted summation of indicator results and individual discipline results, respectively. Information from different specialist areas is therefore processed in the same way, thereby enabling coherent integration across disciplines. [ABSTRACT FROM AUTHOR]

This paper presents the application of an exponential version of the harmonic balance method to the analysis of steady state vibration of geometrically nonlinear systems. A detailed description of the method and of the corresponding numerical procedure is provided. The von Karman theory is used to describe the effects of geometric nonlinearity. The material of the beams is modelled with the help of the Zener model using the fractional calculus. The problem is solved using an exponential version of the harmonic balance method. In the above-mentioned version, the complex calculus is used in contrast to the ordinary harmonic balance method, where the steady state vibrations are described with the help of the trigonometric functions. It significantly simplifies derivation of the amplitude equations. Moreover, the exponential version of the harmonic balance method is more elegant in comparison with the ordinary one. A detailed derivation of the amplitude equations is presented. The modified continuation method is proposed to solve the nonlinear amplitude equations and to determine the response curves. Moreover, the results of the exemplary calculation are presented and compared with known results in order to justify the efficiency and the correctness of the proposed approach. [ABSTRACT FROM AUTHOR]

Environmental variation within a species' range can create contrasting selective pressures, leading to divergent selection and novel adaptations. The conservation value of populations inhabiting environmentally marginal areas remains in debate and is closely related to the adaptive potential in changing environments. Strong selection caused by stressful conditions may generate novel adaptations, conferring these populations distinct evolutionary potential and high conservation value under climate change. On the other hand, environmentally marginal populations may be genetically depauperate, with little potential for new adaptations to emerge. Here, we explored the use of ecological niche models (ENMs) linked with common garden experiments to predict and test for genetically determined phenotypic differentiation related to contrasting environmental conditions. To do so, we built an ENM for the alpine plant Silene ciliata in central Spain and conducted common garden experiments, assessing flowering phenology changes and differences in leaf cell resistance to extreme temperatures. The suitability patterns and response curves of the ENM led to the predictions that: (1) the environmentally marginal populations experiencing less snowpack and higher minimum temperatures would have delayed flowering to avoid risks of late‐spring frosts and (2) those with higher minimum temperatures and greater potential evapotranspiration would show enhanced cell resistance to high temperatures to deal with physiological stress related to desiccation and heat. The common garden experiments revealed the expected genetically based phenotypic differentiation in flowering phenology. In contrast, they did not show the expected differentiation for cell resistance, but these latter experiments had high variance and hence lower statistical power. The results highlight ENMs as useful tools to identify contrasting putative selective pressures across species ranges. Linking ENMs with common garden experiments provides a theoretically justified and practical way to study adaptive processes, including insights regarding the conservation value of populations inhabiting environmentally marginal areas under ongoing climate change. [ABSTRACT FROM AUTHOR]