• Energy Research

Abstract It is commonly recognized that there are constraints to successful regional-scale assessment and monitoring of cumulative impacts because of challenges in the selection of coherent and measurable indicators of the effects. It has also been sensibly declared that the connections between components in a region are as important as the state of the elements themselves. These have previously been termed “linked” cumulative impacts/effects. These connections can be difficult to discern because of a complicated set of interactions and unexpected linkages. In this paper we diagnose that a significant cause of these constraints is the selection of indicators without due regard for their inter-relationships in the formulation of the indicator set. The paper examines whether the common “forms of capital”, i.e., natural (renewable and non-renewable), manufactured, social, human and financial capitals, framework is a potential organizing structure. We examine a large region in western NSW Australia where the predominant production systems are mining and grazing for production of wool, beef and lamb. Production in both is driven by consumption of a non-renewable resource, i.e., ore for mining and topsoil for grazing, the latter on the basis that loss rate estimates far exceed soil formation rates. We propose that the challenge of identifying connections of components within and between capital stores can be approached by explicitly separating stores of capital and the flows of capital between stores and between elements within stores, so-called capital fluxes. We attempt to acquire data from public sources for both capital stores and fluxes. The question of whether these data are a sufficient base for regional assessment, with particular reference to connections, is discussed. The well-described challenge of a comparative common currency for stores and fluxes is also discussed. We conclude that the data acquisition is relatively successful for stores and fluxes. A number of linked impacts are identified and discussed. The potential use of money as the common currency for stores and fluxes of capital is considered. The basic proposition is that replacement or preservation costs be used for this. We conclude that the study is sufficiently positive to consider further research in fully-coupled models of capital stores and fluxes.

Australia's 2019-2020 mega-fires were exacerbated by drought, anthropogenic climate change and existing land-use management. Here, using a combination of remotely sensed data and species distribution models, we found these fires burnt ~97,000 km2 of vegetation across southern and eastern Australia, which is considered habitat for 832 species of native vertebrate fauna. Seventy taxa had a substantial proportion (>30%) of habitat impacted; 21 of these were already listed as threatened with extinction. To avoid further species declines, Australia must urgently reassess the extinction vulnerability of fire-impacted species and assist the recovery of populations in both burnt and unburnt areas. Population recovery requires multipronged strategies aimed at ameliorating current and fire-induced threats, including proactively protecting unburnt habitats.

AbstractEcosystem services (ES) are an increasingly popular policy framework for connecting biodiversity with human well-being. These efforts typically assume that biodiversity and ES covary, but the relationship between them remains remarkably unclear. Here we analyse >500 recent papers and show that reported relationships differ among ES, methods of measuring biodiversity and ES, and three different approaches to linking them (spatial correlations, management comparisons and functional experiments). For spatial correlations, biodiversity relates more strongly to measures of ES supply than to resulting human benefits. For management comparisons, biodiversity of ‘service providers’ predicts ES more often than biodiversity of functionally unrelated taxa, but the opposite is true for spatial correlations. Functional experiments occur at smaller spatial scales than management and spatial studies, which show contrasting responses to scale. Our results illuminate the varying dynamics relating biodiversity to ES, and show the importance of matching management efforts to the most relevant scientific evidence.

AbstractRenewable energy production is necessary to halt climate change and reverse associated biodiversity losses. However, generating the required technologies and infrastructure will drive an increase in the production of many metals, creating new mining threats for biodiversity. Here, we map mining areas and assess their spatial coincidence with biodiversity conservation sites and priorities. Mining potentially influences 50 million km2 of Earth’s land surface, with 8% coinciding with Protected Areas, 7% with Key Biodiversity Areas, and 16% with Remaining Wilderness. Most mining areas (82%) target materials needed for renewable energy production, and areas that overlap with Protected Areas and Remaining Wilderness contain a greater density of mines (our indicator of threat severity) compared to the overlapping mining areas that target other materials. Mining threats to biodiversity will increase as more mines target materials for renewable energy production and, without strategic planning, these new threats to biodiversity may surpass those averted by climate change mitigation.

Renewable energy projects, such as wind farms and hydropower dams, can indirectly benefit biodiversity by mitigating climate change. However, we explain why such indirect benefits should not contribute towards the accounting of project-level net biodiversity outcomes and provide guidance on the steps needed to legitimately claim no-net-loss of biodiversity.

AbstractSafeguarding ecosystem services and biodiversity is critical to achieving sustainable development. To date, ecosystem services quantification has focused on the biophysical supply of services with less emphasis on human beneficiaries (i.e., demand). Only when both occur do ecosystems benefit people, but demand may shift ecosystem service priorities toward human‐dominated landscapes that support less biodiversity. We quantified how accounting for demand affects the efficiency of conservation in capturing both human benefits and biodiversity by comparing conservation priorities identified with and without accounting for demand. We mapped supply and benefit for 3 ecosystem services (flood mitigation, crop pollination, and nature‐based recreation) by adapting existing ecosystem service models to include and exclude factors representing human demand. We then identified conservation priorities for each with the conservation planning program Marxan. Particularly for flood mitigation and crop pollination, supply served as a poor proxy for benefit because demand changed the spatial distribution of ecosystem service provision. Including demand when jointly targeting biodiversity and ecosystem service increased the efficiency of conservation efforts targeting ecosystem services without reducing biodiversity outcomes. Our results highlight the importance of incorporating demand when quantifying ecosystem services for conservation planning.

AbstractClimate change threatens the provisioning of forest ecosystem services and biodiversity (ESB). The climate sensitivity of ESB may vary with forest development from young to old‐growth conditions as structure and composition shift over time and space. This study addresses knowledge gaps hindering implementation of adaptive forest management strategies to sustain ESB. We focused on a number of ESB indicators to (a) analyze associations among carbon storage, timber growth rate, and species richness along a forest development gradient; (b) test the sensitivity of these associations to climatic changes; and (c) identify hotspots of climate sensitivity across the boreal–temperate forests of eastern North America. From pre‐existing databases and literature, we compiled a unique dataset of 18,507 forest plots. We used a full Bayesian framework to quantify responses of nine ESB indicators. The Bayesian models were used to assess the sensitivity of these indicators and their associations to projected increases in temperature and precipitation. We found the strongest association among the investigated ESB indicators in old forests (>170 years). These forests simultaneously support high levels of carbon storage, timber growth, and species richness. Older forests also exhibit low climate sensitivity of associations among ESB indicators as compared to younger forests. While regions with a currently low combined ESB performance benefitted from climate change, regions with a high ESB performance were particularly vulnerable to climate change. In particular, climate sensitivity was highest east and southeast of the Great Lakes, signaling potential priority areas for adaptive management. Our findings suggest that strategies aimed at enhancing the representation of older forest conditions at landscape scales will help sustain ESB in a changing world.