Biology subjects

Ferrier, S.

Publications and source records attributed to Ferrier, S..

6 recordsLinked to original sources

bioRxiv2019

Reconciling global priorities for conserving biodiversity habitat

Degradation and loss of natural habitat is the major driver of the current global biodiversity crisis. Most habitat conservation efforts to date have targeted small areas of highly threatened habitat, but emerging debate suggests retaining large intact natural systems may be just as important. We reconcile these perspectives by integrating fine-resolution global data on habitat condition and species assemblage turnover, to identify Earths high-value biodiversity habitat. These are areas in better condition than most other locations once supporting a similar assemblage of species, and are found within both intact regions and human dominated landscapes. However, only 18.6 % of this high-value habitat is currently protected globally. Averting permanent biodiversity loss requires clear spatially explicit targets for retaining these unprotected high-value habitats.

ecology↗

bioRxiv2019

A global indicator of the capacity of terrestrial ecosystems to retain biological diversity under climate change: the Bioclimatic Ecosystem Resilience Index

An important element of the Convention on Biological Diversitys Aichi Target 15 - i.e. to enhance \"ecosystem resilience ... through conservation and restoration\" - remains largely unaddressed by existing indicators. We here develop an indicator addressing just one of many possible dimensions of ecosystem resilience, by focusing on the capacity of ecosystems to retain biological diversity in the face of ongoing, and uncertain, climate change. The Bioclimatic Ecosystem Resilience Index (BERI) assesses the extent to which a given spatial configuration of natural habitat will promote or hinder climate-induced shifts in biological distributions. The approach uses existing global modelling of spatial turnover in species composition within three broad biological groups (plants, invertebrates and vertebrates) to scale projected changes in composition under a plausible range of climate scenarios. These projections serve as filters through which to analyse the configuration of habitat observed at a given point in time (e.g. for a particular year) - represented as a grid in which cells are scored in terms of habitat condition. BERI is then calculated, for each cell in this grid, as a function of the connectedness of that cell to areas of natural habitat in the surrounding landscape which are projected to support a similar composition of species under climate change to that currently associated with the focal cell. All analyses are performed at 30-arcsecond grid resolution (approximately 1km cells at the equator). Results can then be aggregated to report on status and trends for any desired set of reporting units - e.g. ecoregions, countries, or ecosystem types. We present example outputs for the Moist Tropical Forest Biome, based on a habitat-condition time series derived from the Global Forest Change dataset. We also describe how BERI is now being extended to cover all biomes (forest and non-forest) across the entire terrestrial surface of the planet.

ecology↗

bioRxiv2019

Extending site-based observations to predict the spatial patterns of vegetation structure and composition

ContextConservation planning and land management are inherently spatial processes that are most effective when implemented over large areas.\n\nObjectivesOur objectives were to (i) use existing plot data to aggregate species inventories to growth forms and derive indicators of vegetation structure and composition and ii) generate spatially-explicit, continuous, landscape scaled models of these discrete vegetation indicators, accompanied by maps of model uncertainty.\n\nMethodUsing a case study from New South Wales, Australia, we aggregated floristic observations from 7234 sites into growth forms. We trained ensembles of artificial neural networks (ANN) to predict the distribution of these indicators over a broad region covering 11.5 million hectares. Importantly, we show spatially explicit models of uncertainty so that end-users have a tangible and transparent means of assessing models.\n\nResultsOur key findings were firstly, widely available site-based floristic records can be used to derive aggregated indicators of the structure and composition of plant growth forms. Secondly, ANNs are a powerful method to predict continuous patterns in complex, non-linear data (Pearsons correlation coefficient 0.83 (total native vegetation cover) to 0.42 (forb cover)). Thirdly, maps of the standardised residual error give insight into model performance and provide an assessment of model uncertainty in specific locations.\n\nConclusionsSpatially explicit, continuous representations of vegetation composition and structural complexity can add considerable value to conventional maps of vegetation extent or community type. This application has the potential to enhance the capacity for conservation planners, landscape managers and policy-makers to make informed decisions across landscape and regional scales.

ecology↗

bioRxiv2018

Supporting global biodiversity assessment through high-resolution macroecological modelling: Methodological underpinnings of the BILBI framework

AimGlobal indicators of change in the state of terrestrial biodiversity are often derived by intersecting observed or projected changes in the distribution of habitat transformation, or of protected areas, with underlying patterns in the distribution of biodiversity. However the two main sources of data used to account for biodiversity patterns in such assessments - i.e. ecoregional boundaries, and vertebrate species ranges - are typically delineated at a much coarser resolution than the spatial grain of key ecological processes shaping both land-use and biological distributions at landscape scale. Species distribution modelling provides one widely used means of refining the resolution of mapped species distributions, but is limited to a subset of species which is biased both taxonomically and geographically, with some regions of the world lacking adequate data to generate reliable models even for better-known biological groups.\n\nInnovationMacroecological modelling of collective properties of biodiversity (e.g. alpha and beta diversity) as a correlative function of environmental predictors offers an alternative, yet highly complementary, approach to refining the spatial resolution with which patterns in the distribution of biodiversity can be mapped across our planet. Here we introduce a new capability - BILBI (the Biogeographic Infrastructure for Large-scaled Biodiversity Indicators) - which has implemented this approach by integrating advances in macroecological modelling, biodiversity informatics, remote sensing and high-performance computing to assess spatial-temporal change in biodiversity at ~1km grid resolution across the entire terrestrial surface of the planet. The initial implementation of this infrastructure focuses on modelling beta-diversity patterns using a novel extension of generalised dissimilarity modelling (GDM) designed to extract maximum value from sparsely and unevenly distributed occurrence records for over 400,000 species of plants, invertebrates and vertebrates.\n\nMain conclusionsModels generated by BILBI greatly refine the mapping of beta-diversity patterns relative to more traditional biodiversity surrogates such as ecoregions. This capability is already proving of considerable value in informing global biodiversity assessment through: 1) generation of indicators of past-to-present change in biodiversity based on observed changes in habitat condition and protected-area coverage; and 2) projection of potential future change in biodiversity as a consequence of alternative scenarios of global change in drivers and policy options.

ecology↗

bioRxiv2018

Changes in the Biodiversity Intactness Index in tropical and subtropical forest biomes, 2001-2012.

Few biodiversity indicators are available that reflect broad-sense biodiversity - rather than particular taxa - at fine spatial and temporal resolution. The Biodiversity Intactness Index (BII) reports how the average abundance of native terrestrial species in a region compares with their abundances before pronounced human impacts. BII is designed for use with data from a wide range of taxa and functional groups and for estimation at any resolution for which data on land use and related pressures are available. For each year from 2001 to 2012 we combined models of how land use and related pressures in tropical and subtropical forested biomes affect overall abundance and compositional similarity with data on anthropogenic pressures. We used these data to produce annual maps of modelled BII at a spatial resolution of 30 arc seconds (roughly 1km at the equator) across tropical and subtropical forested biomes. This is the first time temporal change in BII has been estimated across such a large region. The modelling approach used for compositional similarity is an improvement over that used previously when estimating BII, using data more efficiently. Overall, BII fell by an average of 2.4 percentage points between 2001 and 2012, with 83 countries seeing an average reduction and 45 an average increase, and the extent of primary forest fell by 3.9% over the same period. Changes are not strongly related to countries rates of economic growth over the same period.

ecology↗

bioRxiv2018

A protocol for an intercomparison of biodiversity and ecosystem services models using harmonized land-use and climate scenarios

Abstract.To support the assessments of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), the IPBES Expert Group on Scenarios and Models is carrying out an intercomparison of biodiversity and ecosystem services models using harmonized scenarios (BES-SIM). The goals of BES-SIM are (1) to project the global impacts of land use and climate change on biodiversity and ecosystem services (i.e. natures contributions to people) over the coming decades, compared to the 20th century, using a set of common metrics at multiple scales, and (2) to identify model uncertainties and research gaps through the comparisons of projected biodiversity and ecosystem services across models. BES-SIM uses three scenarios combining specific Shared Socio-economic Pathways (SSPs) and Representative Concentration Pathways (RCPs) to explore a wide range of land-use change and climate change futures. This paper describes the rationale for scenarios selection, the process of harmonizing input data for land use, based on the second phase of the Land Use Harmonization Project (LUH2), and climate, the biodiversity and ecosystem service models used, the core simulations carried out, the harmonization of the model output metrics, and the treatment of uncertainty. The results of this collaborative modelling project will support the ongoing global assessment of IPBES, strengthen ties between IPBES and the Intergovernmental Panel on Climate Change (IPCC) scenarios and modelling processes, advise the Convention on Biological Diversity (CBD) on its development of a post-2020 strategic plans and conservation goals, and inform the development of a new generation of nature-centred scenarios.

ecology↗