Management strategies to address the challenges associated with invasive species are critical for effective conservation. An increasing variety of mathematical models offer insight into invasive populations, and can help managers identify cost effective prevention, control, and eradication actions. Despite this, as model complexity grows, so does the inaccessibility of these tools to conservation practitioners making decisions about management. Here, we seek to narrow the science-practice gap by reviewing invasive species management models (ISMMs). We define ISMMs as mechanistic models used to explore invasive species management strategies, and include reaction-advectiondiffusion models, integrodifference equations, gravity models, particle transport models, nonspatial and spatial discrete-time population growth models, cellular automata, and individual-based models. For each approach, we describe the model framework and its implementation, discuss strengths and weaknesses, and give examples of conservation applications. We conclude by discussing how ISMMs can be used in concert with adaptive management to address scientific uncertainties impeding action and with multiple objective decision processes to evaluate tradeoffs among management objectives. We undertook this review to support more effective decision-making involving invasive species by providing conservation practitioners with the information they need to identify tools most useful for their applications.

Objectives Social frailty poses a major threat to successful ageing, but its social cognitive and psychological wellbeing correlates remain poorly understood. This cross-sectional study provides initial insights into whether social cognitive difficulties in older age are associated with social frailty, as well as how social frailty is linked to psychological characteristics known to be important for health and wellbeing. Method Ninety community-dwelling older adults completed measures of social frailty and social cognition (social perception, theory of mind, affective empathy, and informant-rated social behavior) as well as measures of psychological function known to be important for health and wellbeing, both positively (resilience and life satisfaction) and negatively (demoralization, social anxiety, and apathy). Measures of cognitive frailty, physical frailty and depression were also administered to test the specificity of any observed relationships with social frailty. Results Both affective empathy and social behavior were predictive of increased social frailty, but social behavior emerged as the only unique predictor after controlling for covariates. Social frailty also predicted unique variance in all five measures of psychological wellbeing, and for three of these measures (demoralization, resilience, and life satisfaction), the effects remained significant even after adjusting for covariates. Discussion Findings are discussed in relation to models of socioemotional aging and frailty. Potential mechanisms linking social behavior to social capital in older age are identified, as well as how loss of social resources might both directly and indirectly impact wellbeing.

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