Digital Ecosystems: Ecosystem-Oriented Architectures

We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve high-level software applications. Therefore, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. The Digital Ecosystem was then measured experimentally through simulations, with measures originating from theoretical ecology, evaluating its likeness to biological ecosystems. This included its responsiveness to requests for applications from the user base, as a measure of the ecological succession (ecosystem maturity). Overall, we have advanced the understanding of Digital Ecosystems, creating Ecosystem-Oriented Architectures where the word ecosystem is more than just a metaphor.Comment: 39 pages, 26 figures, journa

Payments for Ecosystem Services: Mechanisms to Achieve Desired Landscape Patterns

This paper evaluates the effectiveness of five payment for ecosystem service (PES) schemes at meeting conservation objectives when the spatial configuration is important in meeting desired landscape patterns. The five PES schemes are: 1) fee-simple acquisition; 2) subsidies; 3) tradable development rights (TDR) with zoning; 4) mitigation banking; and 5) purchased development rights (PDR) easements. Findings are that tradeoffs exist between PES schemes for meeting spatial conservation objectives. The appropriate PES scheme incentive mechanism for a given region will depend upon economic demand as well as the landowner and landscape characteristics of the conservation region.Landscape, Spatial conservation, payment for ecosystem services, PES

Urban socioeconomic inequality and biodiversity often converge, but not always: A global meta-analysis

It is through urban biodiversity that the majority of humans experience nature on a daily basis. As cities expand globally, it is increasingly important to understand how biodiversity is shaped by human decisions, institutions, and environments. In some cities, research has documented convergence between high socioeconomic status (SES) and high species diversity. Yet, other studies show that residents with low SES live amid high biodiversity or that SES and biodiversity appear unrelated. This study examines the conditions linked to varying types of relationships between SES and biodiversity. We identified and coded 84 case studies from 34 cities in which researchers assessed SES-biodiversity relationships. We used fuzzy-set Qualitative Comparative Analysis (fsQCA) to evaluate combinations of study design and city-level conditions that explain why SES-biodiversity relationships vary city to city and between plants and animals. While the majority of cases demonstrated increased biodiversity in higher SES neighborhoods, we identified circumstances in which inequality in biodiversity distribution was ameliorated or negated by disturbance, urban form, social policy, or collective human preference. Overall, our meta-analysis highlights the contributions of residential and municipal decisions in differentially promoting biodiversity along socioeconomic lines, situated within each city’s environmental and political context. Through identifying conditions under which access to biodiversity is more or less unequal, we call attention to outstanding research questions and raise prospects for better promoting equitable access to biodiversity

Protecting and restoring habitat to help Australia’s threatened species adapt to climate change

Summary for policy makers Australia’s biodiversity is threatened by climate change, but we currently know little about the scale of the threat or how to deploy on ground conservation actions to protect biodiversity against the changes expected. In this project we predict the impacts of climate change for threatened species and delineate the best options for climate adaptation for all these species collectively via protecting and restoring their habitat.For 504 of Australia’s currently threatened species we predict their distributional responses to climate change, under three climate change scenarios of increasing severity: early mitigation, delayed mitigation and business-as-usual. We then simulate the optimal placement of new protected areas and where necessary, restoration of critical habitat for those species most affected by a changing climate, taking into account variation in the costs and benefits of taking action in different places.We measured the benefits of protecting and restoring habitat by considering the long-term availability and quality of habitat for threatened species as climate changes. We undertook a state-of-the-art multi-action optimisation that accounts for spatial and temporal habitat connectivity under climate change. The scale of the prioritisation analysis implemented here is unprecedented in the conservation literature, and is only possible because of recent advances in software sophistication and parallel computer processing power.We discovered that:• Fifty-nine of the 355 threatened plant species and 11 of the 149 threatened animals considered could completely lose their climatically suitable range by 2085 under the most pessimistic (business as usual) climate change scenario, while four plant species face almost certain extinction due to complete loss of suitable range even under the most optimistic mitigation scenario tested.• Climate is predicted to become unsuitable across more than half of their geographic distribution for 310 (61%) of the modelled species under the business-as-usual scenario and for 80 (16%) species under the early mitigation scenario.• For an available budget of $3 billion, protecting an additional 877,415 km2 of intact habitat, and restoring 1,190 km2 of degraded habitat immediately was identified by our analysis as the optimal set of actions to help the 504 threatened species adapt to climate change assuming early mitigation. Under a more pessimistic business-as-usual climate change scenario, 837,914 km2 of protection is required, along with 77 km2 of restoration. In all cases, appropriate threat management within the protected areas is required.• Within the$3 billion budget, optimal allocation of protection focuses on forests and woodland areas of eastern Australia, Northern Territory, the Great Western Woodlands of Western Australia, and southern South Australia. Restoration effort is required mostly in south-eastern Australia.• We tested a range of conservation budgets from $500 million to$8 billion, and found that the spatial pattern of priority does not change dramatically, and that conservation gains do not level off within that range, i.e. that each dollar invested up to at least 8 billion generates additional benefits for threatened species under climate change.Our analysis deals only with threatened species, i.e. those currently most vulnerable to threats including climate change, and while this doesn’t represent all Australian native animals and plants and how they may all be best provided for, these species have great immediate significance for national biodiversity policy.In summary, the 504 threatened species considered in this study require an increase of between 838,077 km2 and 878,590 km2 in areas protected against loss or degradation either through legislation to protect habitat, designation of protected areas, or negotiations of long-lasting voluntary conservation covenants.Please cite this report as: Maggini, R, Kujala, H, Taylor, MFJ, Lee, JR, Possingham, HP, Wintle, BA, Fuller, RA 2013 Protecting and restoring habitat to help Australia’s threatened species adapt to climate change, National Climate Change Adaptation Research Facility,  Gold Coast, pp. 59.Australia’s biodiversity is threatened by climate change, but we currently know little about the scale of the threat or how to deploy on ground conservation actions to protect biodiversity against the changes expected. In this project we predict the impacts of climate change for threatened species and delineate the best options for climate adaptation for all these species collectively via protecting and restoring their habitat.For 504 of Australia’s currently threatened species we predict their distributional responses to climate change, under three climate change scenarios of increasing severity: early mitigation, delayed mitigation and business-as-usual. We then simulate the optimal placement of new protected areas and where necessary, restoration of critical habitat for those species most affected by a changing climate, taking into account variation in the costs and benefits of taking action in different places.We measured the benefits of protecting and restoring habitat by considering the long-term availability and quality of habitat for threatened species as climate changes. We undertook a state-of-the-art multi-action optimisation that accounts for spatial and temporal habitat connectivity under climate change. The scale of the prioritisation analysis implemented here is unprecedented in the conservation literature, and is only possible because of recent advances in software sophistication and parallel computer processing power.We discovered that: Fifty-nine of the 355 threatened plant species and 11 of the 149 threatened animals considered could completely lose their climatically suitable range by 2085 under the most pessimistic (business as usual) climate change scenario, while four plant species face almost certain extinction due to complete loss of suitable range even under the most optimistic mitigation scenario tested.Climate is predicted to become unsuitable across more than half of their geographic distribution for 310 (61%) of the modelled species under the business-as-usual scenario and for 80 (16%) species under the early mitigation scenario.For an available budget of 3 billion, protecting an additional 877,415 km2 of intact habitat, and restoring 1,190 km2 of degraded habitat immediately was identified by our analysis as the optimal set of actions to help the 504 threatened species adapt to climate change assuming early mitigation. Under a more pessimistic business-as-usual climate change scenario, 837,914 km2 of protection is required, along with 77 km2 of restoration. In all cases, appropriate threat management within the protected areas is required.Within the $3 billion budget, optimal allocation of protection focuses on forests and woodland areas of eastern Australia, Northern Territory, the Great Western Woodlands of Western Australia, and southern South Australia. Restoration effort is required mostly in south-eastern Australia.We tested a range of conservation budgets from$500 million to $8 billion, and found that the spatial pattern of priority does not change dramatically, and that conservation gains do not level off within that range, i.e. that each dollar invested up to at least$8 billion generates additional benefits for threatened species under climate change. Our analysis deals only with threatened species, i.e. those currently most vulnerable to threats including climate change, and while this doesn’t represent all Australian native animals and plants and how they may all be best provided for, these species have great immediate significance for national biodiversity policy.In summary, the 504 threatened species considered in this study require an increase of between 838,077 km2 and 878,590 km2 in areas protected against loss or degradation either through legislation to protect habitat, designation of protected areas, or negotiations of long-lasting voluntary conservation covenants.Please cite this report as: Maggini, R, Kujala, H, Taylor, MFJ, Lee, JR, Possingham, HP, Wintle, BA, Fuller, RA 2013 Protecting and restoring habitat to help Australia’s threatened species adapt to climate change, National Climate Change Adaptation Research Facility,  Gold Coast, pp. 59.&nbsp

Effectiveness of Biological Surrogates for Predicting Patterns of Marine Biodiversity: A Global Meta-Analysis

The use of biological surrogates as proxies for biodiversity patterns is gaining popularity, particularly in marine systems where field surveys can be expensive and species richness high. Yet, uncertainty regarding their applicability remains because of inconsistency of definitions, a lack of standard methods for estimating effectiveness, and variable spatial scales considered. We present a Bayesian meta-analysis of the effectiveness of biological surrogates in marine ecosystems. Surrogate effectiveness was defined both as the proportion of surrogacy tests where predictions based on surrogates were better than random (i.e., low probability of making a Type I error; P) and as the predictability of targets using surrogates (R2). A total of 264 published surrogacy tests combined with prior probabilities elicited from eight international experts demonstrated that the habitat, spatial scale, type of surrogate and statistical method used all influenced surrogate effectiveness, at least according to either P or R2. The type of surrogate used (higher-taxa, cross-taxa or subset taxa) was the best predictor of P, with the higher-taxa surrogates outperforming all others. The marine habitat was the best predictor of R2, with particularly low predictability in tropical reefs. Surrogate effectiveness was greatest for higher-taxa surrogates at a <10-km spatial scale, in low-complexity marine habitats such as soft bottoms, and using multivariate-based methods. Comparisons with terrestrial studies in terms of the methods used to study surrogates revealed that marine applications still ignore some problems with several widely used statistical approaches to surrogacy. Our study provides a benchmark for the reliable use of biological surrogates in marine ecosystems, and highlights directions for future development of biological surrogates in predicting biodiversity

Constraints on Patterns of Abundance and Aggregation in Biological Systems

Understanding the mechanisms that structure biological systems is a primary goal of biology. My research shows that the biological structure is constrained in important ways by general variables such as the number of base pairs in a genome and the number of individuals and species in a community. I used a combination of macroecology, bioinformatics, statistics, mathematics, and advanced computing to pursue my research and published several peer-reviewed scientific manuscripts and open-source software as a result.I was funded through a combination of fellowships and scholarships awarded by the Utah State University School of Graduate Studies, College of Science, and Department of Biology, as well as teaching assistantships awarded through the Department of Biology at Utah State University, and research assistantships funded through a CAREER grant from the U.S. National Science Foundation (DEB-0953694) awarded to my advisor, Dr. Ethan White. With the help of my advisor, I also obtained a computing grant from Amazon Web Services in the amount of $7,500. Altogether, funding for my research and education totaled approximately$123,500. Using over 9000 communities of plants, animals, fungi, and microorganisms, I demonstrated that the forms of empirical species abundance distributions (SADs) are constrained by total abundance and species richness. Using over 300 microbial genomes, I demonstrate that nucleotide aggregation is constrained by genome length and differs between regions of coding and noncoding DNA. General state variables of genomes and ecological communities (i.e. genome length, total abundance and species richness) constrain simple structural properties of each system

Spatial Relationships among Soil Nutrients, Plant Biodiversity and Aboveground Biomass In the Inner Mongolia Grassland, China

abstract: The relationship between biodiversity and ecosystem functioning (BEF) is a central issue in ecology, and a number of recent field experimental studies have greatly improved our understanding of this relationship. Spatial heterogeneity is a ubiquitous characterization of ecosystem processes, and has played a significant role in shaping BEF relationships. The first step towards understanding the effects of spatial heterogeneity on the BEF relationships is to quantify spatial heterogeneity characteristics of key variables of biodiversity and ecosystem functioning, and identify the spatial relationships among these variables. The goal of our research was to address the following research questions based on data collected in 2005 (corresponding to the year when the initial site background information was conducted) and in 2008 (corresponding to the year when removal treatments were conducted) from the Inner Mongolia Grassland Removal Experiment (IMGRE) located in northern China: 1) What are the spatial patterns of soil nutrients, plant biodiversity, and aboveground biomass in a natural grassland community of Inner Mongolia, China? How are they related spatially? and 2) How do removal treatments affect the spatial patterns of soil nutrients, plant biodiversity, and aboveground biomass? Is there any change for their spatial correlations after removal treatments? Our results showed that variables of biodiversity and ecosystem functioning in the natural grassland community would present different spatial patterns, and they would be spatially correlated to each other closely. Removal treatments had a significant effect on spatial structures and spatial correlations of variables, compared to those prior to the removal treatments. The differences in spatial pattern of plant and soil variables and their correlations before and after the biodiversity manipulation may not imply that the results from BEF experiments like IMGRE are invalid. However, they do suggest that the possible effects of spatial heterogeneity on the BEF relationships should be critically evaluated in future studies.Dissertation/ThesisM.S. Biology 201

Ecological Modelling with the Calculus of Wrapped Compartments

The Calculus of Wrapped Compartments is a framework based on stochastic multiset rewriting in a compartmentalised setting originally developed for the modelling and analysis of biological interactions. In this paper, we propose to use this calculus for the description of ecological systems and we provide the modelling guidelines to encode within the calculus some of the main interactions leading ecosystems evolution. As a case study, we model the distribution of height of Croton wagneri, a shrub constituting the endemic predominant species of the dry ecosystem in southern Ecuador. In particular, we consider the plant at different altitude gradients (i.e. at different temperature conditions), to study how it adapts under the effects of global climate change.Comment: A preliminary version of this paper has been presented in CMC13 (LNCS 7762, pp 358-377, 2013

Functional Integration of Ecological Networks through Pathway Proliferation

Large-scale structural patterns commonly occur in network models of complex systems including a skewed node degree distribution and small-world topology. These patterns suggest common organizational constraints and similar functional consequences. Here, we investigate a structural pattern termed pathway proliferation. Previous research enumerating pathways that link species determined that as pathway length increases, the number of pathways tends to increase without bound. We hypothesize that this pathway proliferation influences the flow of energy, matter, and information in ecosystems. In this paper, we clarify the pathway proliferation concept, introduce a measure of the node--node proliferation rate, describe factors influencing the rate, and characterize it in 17 large empirical food-webs. During this investigation, we uncovered a modular organization within these systems. Over half of the food-webs were composed of one or more subgroups that were strongly connected internally, but weakly connected to the rest of the system. Further, these modules had distinct proliferation rates. We conclude that pathway proliferation in ecological networks reveals subgroups of species that will be functionally integrated through cyclic indirect effects.Comment: 29 pages, 2 figures, 3 tables, Submitted to Journal of Theoretical Biolog