Effective conservation planning of Iberian amphibians based on a regionalization of climate-driven range shifts

Amphibians are severely affected by climate change, particularly in regions where droughts prevail and water availability is scarce. The extirpation of amphibians triggers cascading effects that disrupt the trophic structure of food webs and ecosystems. Dedicated assessments of the spatial adaptive potential of amphibian species under climate change are, therefore, essential to provide guidelines for their effective conservation. I used predictions about the location of suitable climates for 27 amphibian species in the Iberian Peninsula from a baseline period to 2080 to typify shifting species' ranges. The time at which these range types are expected to be functionally important for the adaptation of a species was used to identify full or partial refugia; areas most likely to be the home of populations moving into new climatically suitable grounds; areas most likely to receive populations after climate adaptive dispersal; and climatically unsuitable areas near suitable areas. I implemented an area prioritization protocol for each species to obtain a cohesive set of areas that would provide maximum adaptability and where management interventions should be prioritized. A connectivity assessment pinpointed where facilitative strategies would be most effective. Each of the 27 species had distinct spatial requirements but, common to all species, a bottleneck effect was predicted by 2050 because source areas for subsequent dispersal were small in extent. Three species emerged as difficult to maintain up to 2080. The Iberian northwest was predicted to capture adaptive range for most species. My study offers analytical guidelines for managers and decision makers to undertake systematic assessments on where and when to intervene to maximize the persistence of amphibian species and the functionality of the ecosystems that depend on them.

Software for prioritizing conservation actions based on probabilistic information

Marxan is the most common decision-support tool used to inform the design of protected-area systems. The original version of Marxan does not consider risk and uncertainty associated with threatening processes affecting protected areas, including uncertainty about the location and condition of species' populations and habitats now and in the future. We described and examined the functionality of a modified version of Marxan, Marxan with Probability. This software explicitly considers 4 types of uncertainty: probability that a feature exists in a particular place (estimated based on species distribution models or spatially explicit population models); probability that features in a site will be lost in the future due to a threatening process, such as climate change, natural catastrophes, and uncontrolled human interventions; probability that a feature will exist in the future due to natural successional processes, such as a fire or flood; and probability the feature exists but has been degraded by threatening processes, such as overfishing or pollution, and thus cannot contribute to conservation goals. We summarized the results of 5 studies that illustrate how each type of uncertainty can be used to inform protected area design. If there were uncertainty in species or habitat distribution, users could maximize the chance that these features were represented by including uncertainty using Marxan with Probability. Similarly, if threatening processes were considered, users minimized the chance that species or habitats were lost or degraded by using Marxan with Probability. Marxan with Probability opens up substantial new avenues for systematic conservation planning research and application by agencies.

Leveraging technology for the treatment of type 1 diabetes in pregnancy: A review of past, current, and future therapeutic tools

The significant risks associated with pregnancies complicated by type 1 diabetes (T1D) were first recognized in the medical literature in the mid-twentieth century. Stringent glycemic control with hemoglobin A1c (HbA1c) values ideally less than 6% has been shown to improve maternal and fetal outcomes. The management options for pregnant women with T1D in the modern era include a variety of technologies to support self-care. Although self-monitoring of blood glucose (SMBG) and multiple daily injections (MDI) are often the recommended management options during pregnancy, many people with T1D utilize a variety of different technologies, including continuous glucose monitoring (CGM), continuous subcutaneous insulin infusion (CSII), and CSII including automated delivery or suspension algorithms. These systems have yielded invaluable diagnostic and therapeutic capabilities and have the potential to benefit this understudied higher-risk group. A recent prospective, multicenter study evaluating pregnant patients with T1D revealed that CGM significantly improves maternal glycemic parameters, is associated with fewer adverse neonatal outcomes, and minimizes burden. Outcome data for CSII, which is approved for use in pregnancy and has been utilized for several decades, remain mixed. Current evidence, although limited, for commercially available and emerging technologies for the management of T1D in pregnancy holds promise for improving patient and fetal outcomes.

Rapidly assessing cobenefits to advance threat-management alliances

Conservation strategies aimed at reducing threats to biodiversity can have significant implications for multiple sectors in a socioeconomic system, but these cobenefits are often poorly understood. For example, many of the threats to native species also impede agricultural production, yet agriculture is typically perceived as in competition with conservation objectives. Although a comprehensive, multiobjective decision analysis is usually beyond the scope and capacity of conservation decision makers, failing to incorporate key socioeconomic costs and benefits into conservation decision-making processes can result in missed opportunities for diversifying outcomes and creating cost-sharing multisectoral partnerships. We devised a straightforward and readily interpretable approach to incorporate cobenefits into a threat-management prioritization approach. We used it to analyze the agricultural cobenefits of implementing 9 invasive animal management strategies designed to ensure the persistence of 148 threatened species across Australia's Lake Eyre Basin over 50 years. A structured elicitation process with 24 participants (scientists, land managers, agriculturalists, and other stakeholders) was used to collect information on each strategy, including costs, technical and social feasibility, benefits to native threatened species, and cobenefits to agricultural production systems. The costs of targeted invasive animal management to save threatened species across the basin (AU$33 million/year) outweighed the overall benefits to the agricultural industry (estimated AU$226 million/year). The return on investment for these management strategies varied substantially when agricultural cobenefits were considered alongside threatened species benefits and showed synergies and challenges. Our approach demonstrates the value of incorporating cobenefits of conservation actions into cost-effectiveness analyses to guide potential investment and partnerships and to diversify implementation pathways.

Digital health technology and diabetes management

Diabetes care is largely dependent on patient self-management and empowerment, given that patients with diabetes must make numerous daily decisions as to what to eat, when to exercise, and determine their insulin dose and timing if required. In addition, patients and providers are generating vast amounts of data from many sources, including electronic medical records, insulin pumps, sensors, glucometers, and other wearables, as well as evolving genomic, proteomic, metabolomics, and microbiomic data. Multiple digital tools and apps have been developed to assist patients to choose wisely, and to enhance their compliance by using motivational tools and incorporating incentives from social media and gaming techniques. Healthcare teams (HCTs) and health administrators benefit from digital developments that sift through the enormous amounts of patient-generated data. Data are acquired, integrated, analyzed, and presented in a self-explanatory manner, highlighting important trends and items that require attention. The use of decision support systems may propose data-driven actions that, for the most, require final approval by the patient or physician before execution and, once implemented, may improve patient outcomes. The digital diabetes clinic aims to incorporate all digital patient data and provide individually tailored virtual or face-to-face visits to those persons who need them most. Digital diabetes care has demonstrated only modest HbA1c reduction in multiple studies and borderline cost-effectiveness, although patient satisfaction appears to be increased. Better understanding of the barriers to digital diabetes care and identification of unmet needs may yield improved utilization of this evolving technology in a safe, effective, and cost-saving manner.