Combining local- and large-scale models to predict the distributions of invasive plant species

Habitat-distribution models are increasingly used to predict the potential distributions of invasive species and to inform monitoring. However, these models assume that species are in equilibrium with the environment, which is clearly not true for most invasive species. Although this assumption is frequently acknowledged, solutions have not been adequately addressed. There are several potential methods for improving habitat-distribution models. Models that require only presence data may be more effective for invasive species, but this assumption has rarely been tested. In addition, combining modeling types to form ‘ensemble’ models may improve the accuracy of predictions. However, even with these improvements, models developed for recently invaded areas are greatly influenced by the current distributions of species and thus reflect near- rather than long-term potential for invasion. Larger scale models from species’ native and invaded ranges may better reflect long-term invasion potential, but they lack finer scale resolution. We compared logistic regression (which uses presence/absence data) and two presence-only methods for modeling the potential distributions of three invasive plant species on the Olympic Peninsula in Washington State, USA. We then combined the three methods to create ensemble models. We also developed climate-envelope models for the same species based on larger scale distributions and combined models from multiple scales to create an index of near- and long-term invasion risk to inform monitoring in Olympic National Park (ONP). Neither presence-only nor ensemble models were more accurate than logistic regression for any of the species. Larger scale models predicted much greater areas at risk of invasion. Our index of near- and long-term invasion risk indicates that \u3c4% of ONP is at high near-term risk of invasion while 67-99% of the Park is at moderate or high long-term risk of invasion. We demonstrate how modeling results can be used to guide the design of monitoring protocols and monitoring results can in turn be used to refine models. We propose that by using models from multiple scales to predict invasion risk and by explicitly linking model development to monitoring, it may be possible to overcome some of the limitations of habitat-distribution models

Design optimization of a multi-mission helicopter configuration

The MH-60S helicopter program is currently in the development stages of incorporating provisions for the Airborne Mine Countermeasures (AMCM) Mission and the Armed Helicopter Mission. The integration of these mission provisions represents a departure from the initial design goals of the MH-60S as solely a combat support helicopter. This aircraft will ultimately be expected to execute in excess of 18 different missions in place of seven existing aircraft rather than just serving as a replacement for the H-46 helicopter. Common to any aircraft program is the issue of weight growth. Weight growth has been cited as a major risk on this program in light of the fact that there will be provisions for both major mission areas in the final (FY 07) aircraft configuration. As a result of not anticipating specific design impacts associated with the requirement to perform a wide range of missions, the aircraft will not meet the requirements set forth in the Operational Requirements Document. The fact that a single aircraft will be taking the place of several aircraft that were implicitly designed for specific missions serves to further increase the gap between the requirements and the realized, as-designed performance. The specific weight issue can be further clarified by a discussion of weight growth over time and a study of how each mission area will add weight. Incident to this discussion is a comparison of aircraft performance versus the requirements and the associated shortfalls in range, time on station, and combat radius. There are many areas where weight can be shed. Weight reduction and performance enhancements have become unfunded program requirements, resulting in detailed analysis and considerations for postproduction changes to the aircraft. In this thesis, background and causal factors for the weight/performance issue will be analyzed. Candidates for weight reduction and performance enhancements that yield the greatest performance increase will be proposed

Unexpected Management Choices When Accounting for Uncertainty in Ecosystem Service Tradeoff Analyses

Resource management and conservation increasingly focus on ecosystem service provisioning and potential tradeoffs among services under different management actions. Application of bioeconomic approaches to tradeoffs assessment is touted as a way to find win-win outcomes or avoid unnecessary stakeholder conflict. Yet, nearly all assessments to date have ignored inherent uncertainties in the provision and valuation of services. We incorporate uncertainty into the ecosystem services analytical framework and show how such inclusion improves optimal decision making. In particular, we show: (1) “suboptimal” solutions can become optimal when uncertainties are accounted for; (2) uncertainty paradoxically makes stakeholders value conservation despite their lack of preference for it; and (3) substantial losses or missed gains in ecosystem service provisioning can be incurred when uncertainty is ignored. Our results highlight the urgency of accounting for uncertainties in ecosystem services in tradeoff assessments given the widespread use of this approach by government agencies and conservation organizations

Designing MPAs for food security in open-access fisheries

Food security remains a principal challenge in the developing tropics where communities rely heavily on marine-based protein. While some improvements in fisheries management have been made in these regions, a large fraction of coastal fisheries remain unmanaged, mismanaged, or use only crude input controls. These quasi-open-access conditions often lead to severe overfishing, depleted stocks, and compromised food security. A possible fishery management approach in these institution-poor settings is to implement fully protected marine protected areas (MPAs). Although the primary push for MPAs has been to solve the conservation problems that arise from mismanagement, MPAs can also benefit fisheries beyond their borders. The literature has not completely characterized how to design MPAs under diverse ecological and economic conditions when food security is the objective. We integrated four key biological and economic variables (i.e., fish population growth rate, fish mobility, fish price, and fishing cost) as well as an important aspect of reserve design (MPA size) into a general model and determined their combined influence on food security when MPAs are implemented in an open-access setting. We explicitly modeled open-access conditions that account for the behavioral response of fishers to the MPA; this approach is distinct from much of the literature that focuses on assumptions of “scorched earth” (i.e., severe over-fishing), optimized management, or an arbitrarily defined fishing mortality outside the MPA’s boundaries. We found that the MPA size that optimizes catch depends strongly on economic variables. Large MPAs optimize catch for species heavily harvested for their high value and/or low harvesting cost, while small MPAs or no closure are best for species lightly harvested for their low value and high harvesting cost. Contrary to previous theoretical expectations, both high and low mobility species are expected to experience conservation benefits from protection, although, as shown previously, greater conservation benefits are expected for low mobility species. Food security benefits from MPAs can be obtained from species of any mobility. Results deliver both qualitative insights and quantitative guidance for designing MPAs for food security in open-access fisheries

Causality and the semantics of provenance

Provenance, or information about the sources, derivation, custody or history of data, has been studied recently in a number of contexts, including databases, scientific workflows and the Semantic Web. Many provenance mechanisms have been developed, motivated by informal notions such as influence, dependence, explanation and causality. However, there has been little study of whether these mechanisms formally satisfy appropriate policies or even how to formalize relevant motivating concepts such as causality. We contend that mathematical models of these concepts are needed to justify and compare provenance techniques. In this paper we review a theory of causality based on structural models that has been developed in artificial intelligence, and describe work in progress on a causal semantics for provenance graphs.Comment: Workshop submissio