论在可持续发展战略思想指导下的工业设计

阐述了可持续发展战略思想的重要意义和实施可持续设计的必要性，明确了工业设计师在整体设计流程中追求的终极目标。     

Blending science and public policies for remediation of a degraded ecosystem: Jackfish Bay, north shore of Lake Superior, Ontario, Canada

The Jackfish Bay Remedial Action Plan is the first of Lake Superior's Areas of Concern (AOCs) to consider recognition as an Area in Recovery (AiR). As a result of a high degree of complexity and uncertainty, ecosystem recovery in Jackfish Bay has been determined using a combination of regulatory policies and scientific evidence and extensive public and expert-based decision making. As a result, the conceptualization of the AiR status in Jackfish Bay has been developed with the adaptive management and the ecosystem approach, which provide the basic principles of assessing, monitoring, and managing the Area of Concern. To determine the status of beneficial use impairments caused by effluent from the Terrace Bay Pulp Inc., three public advisory committees—an academic panel of experts, a government technical review committee, and the Jackfish Bay Public Area in Recovery Review Committee (PARRC)—reviewed relevant scientific data and documents, including peer-reviewed publications, to assess changes in pollution levels in Jackfish Bay and improvements to aquatic, biotic, and benthic environments of the bay. The public decision-making process concluded with recommendations by the PARRC to develop a systematic monitoring program so that the ecosystem recovery process in the bay could be assessed on a continued basis, leading to its eventual delisting as an AOC. The entire process provides an example of blending science and public policies for remediation of a degraded ecosystem on the Great Lakes.     

Ecological assessment of Phragmites australis wetlands using multi-season SPOT-5 scenes

Ecologists and conservationists need accurate and replicable tools for monitoring wetland conditions in order to develop and implement adaptive management strategies efficiently. The Rhone Delta (Camargue) in southern France encloses 9200 ha of fragmented reed marshes actively managed for reed harvesting, waterfowl hunting or cattle grazing, and holding significant numbers of vulnerable European birds. We used multi-season SPOT-5 data in conjunction with ground survey to assess the predictive power of satellite imagery in modelling indicators of reed structure (height, diameter, density and cover of green/dry stems) relevant to ecosystem management and bird ecology. All indicators could be predicted accurately with a combination of bands (SWIR, NIR) and indices (SAVI, OSAVI, NDWI, DVI, DVW, MSI) issued from scenes of March, June, July, September or December and subtraction between these. All models were robust when validated with an independent set of satellite and field data. The high spatial resolution of SPOT-5 scenes (pixel of 10 × 10 m) permits the monitoring of detailed attributes characterizing the reed ecosystem across a large spatial extent, providing a scientifically-based, replicable tool for managers, stakeholders and decision-makers to follow wetland conditions in the short and long-term. Combined with models on the ecological requirements of vulnerable bird species, these tools can provide maps of potential species ranges at spatial extents that are relevant to ecosystem functioning and bird populations.     

Integration of MODIS-derived metrics to assess interannual variability in snowpack, lake ice, and NDVI in southwest Alaska

Impacts of global climate change are expected to result in greater variation in the seasonality of snowpack, lake ice, and vegetation dynamics in southwest Alaska. All have wide-reaching physical and biological ecosystem effects in the region. We used Moderate Resolution Imaging Spectroradiometer (MODIS) calibrated radiance, snow cover extent, and vegetation index products for interpreting interannual variation in the duration and extent of snowpack, lake ice, and vegetation dynamics for southwest Alaska. The approach integrates multiple seasonal metrics across large ecological regions.Throughout the observation period (2001-2007), snow cover duration was stable within ecoregions, with variable start and end dates. The start of the lake ice season lagged the snow season by 2 to 3 months. Within a given lake, freeze-up dates varied in timing and duration, while break-up dates were more consistent. Vegetation phenology varied less than snow and ice metrics, with start-of-season dates comparatively consistent across years. The start of growing season and snow melt were related to one another as they are both temperature dependent. Higher than average temperatures during the El Niño winter of 2002-2003 were expressed in anomalous ice and snow season patterns. We are developing a consistent, MODIS-based dataset that will be used to monitor temporal trends of each of these seasonal metrics and to map areas of change for the study area.     

Testing a MODIS Global Disturbance Index across North America

Large-scale ecosystem disturbances (LSEDs) have major impacts on the global carbon cycle as large pulses of CO₂ and other trace gases from terrestrial biomass loss are emitted to the atmosphere during disturbance events. The high temporal and spatial variability of the atmospheric emissions combined with the lack of a proven methodology to monitor LSEDs at the global scale make the timing, location and extent of vegetation disturbance a significant uncertainty in understanding the global carbon cycle. The MODIS Global Disturbance Index (MGDI) algorithm is designed for large-scale, regular, disturbance mapping using Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) Land Surface Temperature (LST) and Aqua/MODIS Enhanced Vegetation Index (EVI) data. The MGDI uses annual maximum composite LST data to detect fundamental changes in land-surface energy partitioning, while avoiding the high natural variability associated with tracking LST at daily, weekly, or seasonal time frames. Here we apply the full Aqua/MODIS dataset through 2006 to the improved MGDI algorithm across the woody ecosystems of North America and test the algorithm by comparison with confirmed, historical wildfire events and the windfall areas of documented major hurricanes. The MGDI accurately detects the location and extent of wildfire throughout North America and detects high and moderate severity impacts in the windfall area of major hurricanes. We also find detections associated with clear-cut logging and land-clearing on the forest-agricultural interface. The MGDI indicates that 1.5% (195,580 km²) of the woody ecosystems within North America was disturbed in 2005 and 0.5% (67,451 km²) was disturbed in 2006. The interannual variability is supported by wildfire detections and official burned area statistics.     

Optimisation as a process for understanding and managing river ecosystems

Optimisation can assist in the management of riverine ecosystems through the exploration of multiple alternative management strategies, and the evaluation of trade-offs between conflicting objectives. In addition, it can facilitate communication and learning about the system. However, the effectiveness of optimisation in aiding decision making for ecological management is currently limited by four major challenges: identification and quantification of ecosystem objectives; representation of ecosystems in predictive simulation models; specification of objectives and management alternatives in an optimisation framework; and evaluation of model results against actual ecological outcomes. This study evaluates previous literature in ecology, optimisation and decision science, and provides a strategy for addressing the challenges identified. It highlights the need for better recognition and analysis of assumptions in optimisation modelling as part of a process that generates and shares knowledge.     

Habitat structure influences below ground biocontrol services: A comparison between urban gardens and vacant lots

Urban agriculture offers a framework for local self-reliance by provisioning food security, employment opportunities, and other community benefits. However, urban agriculture must rely on the supporting and regulating services of the soil food web. Hence, we quantified belowground biocontrol activity in urban gardens and vacant lots in two post-industrial cities using an in situ insect baiting technique. Due to the differences in habitat structure, we hypothesized that belowground biocontrol services will differ between gardens and vacant lots and the influence of habitat structure would differ with the type of biocontrol organism. Results revealed that biocontrol activity, as assessed by % mortality of baited insects, varied between 51% and 98% with higher activity often recorded in vacant lots than gardens. Major contributions to bait insect mortality were by ants, followed by microbial pathogens and entomopathogenic nematodes, respectively. Ants showed higher (p < 0.0001) % mortality in vacant lots (60% ± 33.4%) than in urban gardens (33.3% ± 22.2%) whereas microbial pathogens exhibited higher (p < 0.0001) mortality in gardens (27.8% ± 15%) than vacant lots (8.3% ± 16.7%). Ants caused higher (p < 0.0001) mortality when larger-mesh size cages were used compared with the smaller-mesh size cages, but mortality by microbial pathogens did not differ with cage type. The high biocontrol activity indicates the resilience of the soil food web in urban ecosystems and the differential effects of habitat structure on biocontrol activity can help guide landscape planning and vegetation management to enhance urban environments and boost local self-reliance.     

Designing the framework of technological entrepreneurship ecosystem: A grounded theory approach in the context of Iran

The ecosystem approach, as a comprehensive way of understanding multi-aspect environments, has recently gained so much attention in entrepreneurship and innovation studies. The application of this approach has led to the introduction of the currently available ecosystem frameworks that are dealing with some issues such as infirm structure and heterogeneity of components. In this research, by adopting the grounded theory approach in the context of Iran, we defined a novel and comprehensive framework for the technological entrepreneurship ecosystem (TEE). Twenty-six in-depth and semi-structured interviews have been conducted and analysed through a modified grounded theory procedure. Seventy-four secondary sources were added to the study to expand the breadth of our analysis and reach a stronger saturation. The concluded framework comprised of four interconnected layers representing environmental conditions, entity domains, functional realms, and tech-entrepreneurial agents. In addition, we identified some general principles and rules as important underlying aspects of this framework. The inferred components and structure of this novel framework not only could enable us to design the relations between the ecosystem components, but also prompt and support further research on each dimension of the ecosystem.