Geology topics

G.D. Peterson

Publications and source records attributed to G.D. Peterson.

5 recordsLinked to original sources

USGS2023

Bringing the Nature Futures Framework to life: Creating a set of illustrative narratives of nature futures

To halt further destruction of the biosphere, most people and societies around the globe need to transform their relationships with nature. The internationally agreed vision under the Convention of Biological Diversity—Living in harmony with nature—is that “By 2050, biodiversity is valued, conserved, restored and wisely used, maintaining ecosystem services, sustaining a healthy planet and delivering benefits essential for all people”. In this context, there are a variety of debates between alternative perspectives on how to achieve this vision. Yet, scenarios and models that are able to explore these debates in the context of “living in harmony with nature” have not been widely developed. To address this gap, the Nature Futures Framework has been developed to catalyse the development of new scenarios and models that embrace a plurality of perspectives on desirable futures for nature and people. In this paper, members of the IPBES task force on scenarios and models provide an example of how the Nature Futures Framework can be implemented for the development of illustrative narratives representing a diversity of desirable nature futures: information that can be used to assess and develop scenarios and models whilst acknowledging the underpinning value perspectives on nature. Here, the term illustrative reflects the multiple ways in which desired nature futures can be captured by these narratives. In addition, to explore the interdependence between narratives, and therefore their potential to be translated into scenarios and models, the six narratives developed here were assessed around three areas of the transformative change debate, specifically, (1) land sparing vs. land sharing, (2) Half Earth vs. Whole Earth conservation, and (3) green growth vs. post-growth economic development. The paper concludes with an assessment of how the Nature Futures Framework could be used to assist in developing and articulating transformative pathways towards desirable nature futures.

Sustainability Science↗

USGS2023

Towards a better future for biodiversity and people: Modelling Nature Futures

The Nature Futures Framework (NFF) is a heuristic tool for co-creating positive futures for nature and people. It seeks to open up a diversity of futures through mainly three value perspectives on nature – Nature for Nature, Nature for Society, and Nature as Culture. This paper describes how the NFF can be applied in modelling to support decision-making. First, we describe key considerations for the NFF in developing qualitative and quantitative scenarios: i) multiple value perspectives on nature as a state space where pathways improving nature toward a frontier can be represented, ii) mutually reinforcing key feedbacks of social-ecological systems that are important for nature conservation and human wellbeing, iii) indicators of multiple knowledge systems describing the evolution of complex social-ecological dynamics. We then present three approaches to modelling Nature Futures scenarios in the review, screening, and design phases of policy processes. This paper seeks to facilitate the integration of relational values of nature in models and strengthen modelled linkages across biodiversity, nature’s contributions to people, and quality of life.

Global Environmental Change↗

USGS2008

A test of the cross-scale resilience model: Functional richness in Mediterranean-climate ecosystems

Ecological resilience has been proposed to be generated, in part, in the discontinuous structure of complex systems. Environmental discontinuities are reflected in discontinuous, aggregated animal body mass distributions. Diversity of functional groups within body mass aggregations (scales) and redundancy of functional groups across body mass aggregations (scales) has been proposed to increase resilience. We evaluate that proposition by analyzing mammalian and avian communities of Mediterranean-climate ecosystems. We first determined that body mass distributions for each animal community were discontinuous. We then calculated the variance in richness of function across aggregations in each community, and compared observed values with distributions created by 1000 simulations using a null of random distribution of function, with the same n, number of discontinuities and number of functional groups as the observed data. Variance in the richness of functional groups across scales was significantly lower in real communities than in simulations in eight of nine sites. The distribution of function across body mass aggregations in the animal communities we analyzed was non-random, and supports the contentions of the cross-scale resilience model. ?? 2007 Elsevier B.V. All rights reserved.

Ecological Complexity↗

USGS2006

Ecological thresholds: The key to successful enviromental management or an important concept with no practical application?

An ecological threshold is the point at which there is an abrupt change in an ecosystem quality, property or phenomenon, or where small changes in an environmental driver produce large responses in the ecosystem. Analysis of thresholds is complicated by nonlinear dynamics and by multiple factor controls that operate at diverse spatial and temporal scales. These complexities have challenged the use and utility of threshold concepts in environmental management despite great concern about preventing dramatic state changes in valued ecosystems, the need for determining critical pollutant loads and the ubiquity of other threshold-based environmental problems. In this paper we define the scope of the thresholds concept in ecological science and discuss methods for identifying and investigating thresholds using a variety of examples from terrestrial and aquatic environments, at ecosystem, landscape and regional scales. We end with a discussion of key research needs in this area.

Ecosystems↗

USGS2006

Trade-offs across space, time, and ecosystem services

Ecosystem service (ES) trade-offs arise from management choices made by humans, which can change the type, magnitude, and relative mix of services provided by ecosystems. Trade-offs occur when the provision of one ES is reduced as a consequence of increased use of another ES. In some cases, a trade-off may be an explicit choice; but in others, trade-offs arise without premeditation or even awareness that they are taking place. Trade-offs in ES can be classified along three axes: spatial scale, temporal scale, and reversibility. Spatial scale refers to whether the effects of the trade-off are felt locally or at a distant location. Temporal scale refers to whether the effects take place relatively rapidly or slowly. Reversibility expresses the likelihood that the perturbed ES may return to its original state if the perturbation ceases. Across all four Millennium Ecosystem Assessment scenarios and selected case study examples, trade-off decisions show a preference for provisioning, regulating, or cultural services (in that order). Supporting services are more likely to be "taken for granted." Cultural ES are almost entirely unquantified in scenario modeling; therefore, the calculated model results do not fully capture losses of these services that occur in the scenarios. The quantitative scenario models primarily capture the services that are perceived by society as more important - provisioning and regulating ecosystem services - and thus do not fully capture trade-offs of cultural and supporting services. Successful management policies will be those that incorporate lessons learned from prior decisions into future management actions. Managers should complement their actions with monitoring programs that, in addition to monitoring the short-term provisions of services, also monitor the long-term evolution of slowly changing variables. Policies can then be developed to take into account ES trade-offs at multiple spatial and temporal scales. Successful strategies will recognize the inherent complexities of ecosystem management and will work to develop policies that minimize the effects of ES trade-offs. Copyright ?? 2006 by the author(s).

Ecology and Society↗