Comparing screening outcomes for private sector nature‐related assessments based on national and global biodiversity datasets - Takuya Nomura; Luke Kelly; Andrew Skowno; Emily Nicholson (Conservation Biology, 2026)
In response to demand for better biodiversity stewardship from the private sector, frameworks such as the Taskforce on Nature‐related Financial Disclosures (TNFD) have been developed to help companies assess, manage, and disclose their nature‐related impacts, dependencies, risks, and opportunities. A key initial screening step is to identify operations in ecologically sensitive areas. This step is often conducted using global datasets that are readily available and consistent but may be less accurate than national data informed by local expertise and conditions. In this study, we explored the implications of using global versus national biodiversity datasets for identifying ecologically sensitive sites at large scales, using South Africa as a case study. We simulated a screening process by generating sites through stratified random sampling and screened these based on three TNFD criteria for ecologically sensitive sites: biodiversity importance, high ecosystem integrity, and rapid decline in ecosystem integrity. We compared results from multiple global and national datasets, calculating omission errors, where global datasets omit sites identified by national data, and commission errors, where global datasets flag sites as sensitive but national data do not. We found global datasets missed over 39% of areas important for biodiversity, as identified by national datasets. Such omission errors risk ongoing biodiversity loss because sites omitted at early screening stages are unlikely to have resources allocated for conservation or restoration. Our findings suggest a cautious use of global datasets, with an emphasis on encouraging the use of national datasets, particularly when fine‐scale, field‐validated, and frequently updated data are available.

SNAPSHOT USA 2024: Year 6 of the Coordinated National Camera Trap Survey of the United States - Brigit Rooney; Roland Kays; Michael V. Cove; Alex Jensen; Daniel J. Herrera; Camilla Price; Phuong‐Thao Nguyen‐Nu; Katrina Adamczyk; Peter D. Alexander; David Allen; Jesse M. Alston; Diego F. Alvarado‐Serrano; et al. (Global Ecology and Biogeography, 2026)
Motivation SNAPSHOT USA is an annual, multi‐contributor camera trap survey of mammals across the United States. The growing SNAPSHOT USA dataset is intended for tracking the spatial and temporal responses of mammal populations to changes in land use, land cover and climate. These data will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, as well as the impacts of species interactions on daily activity patterns. Main Types of Variables Contained SNAPSHOT USA 2024 contains 377,427 records of camera trap image sequence data and 3127 records of camera trap deployment metadata. Spatial Location and Grain Data were collected across the United States of America in 49 states, 12 ecoregions and many ecosystems. Time Period and Grain Data were collected between 1 August and 19 December in 2024. Major Taxa and Level of Measurement The dataset includes a wide range of taxa but is primarily focused on medium to large mammals. Software Format SNAPSHOT USA 2024 comprises two .csv files. The original data can be found within the SNAPSHOT USA 2024 project on the Wildlife Insights platform.

Innovative In Vitro-In Silico Platform for Dose–Response Modeling in Canine Bladder Cancer: A 3D Organoid- and Mathematics-Based Approach - Mackenzie Long; Yvonne Peng; Saumya Gade; Hannah Nicholson; Michael Catucci; Christopher Zdyrski; Aleksandra Pawlak; Megan Corbett; Corey Saba; Travis Laver; Emily Rawlings; Maria Orbay-Cerrato; et al. (The AAPS Journal, 2026)

Applying the IUCN Global Ecosystem Typology to classify, describe, and map ecosystems based on regional data and Indigenous knowledge - Alys R. Young; Hugh F. Davies; Margaret L. Ayre; Alana Brekelmans; Brett A. Bryan; Jane Elith; Kate Hadden; Mavis Kerinaiua; David A. Keith; Donna L. Lewis; Kinjia M. Munkara‐Murray; Sarah Ryan; et al. (Conservation Biology, 2025)
Effective ecosystem conservation for biodiversity and human well‐being relies on accurate information. Consistent approaches to classifying, describing, and assessing ecosystems can improve understanding of ecological processes, threats, and management. We explored how the International Union for Conservation of Nature (IUCN) Global Ecosystem Typology—a global classification framework based on ecosystem function—could support the development of a classification of ecosystems for the Tiwi Islands, Australia, by incorporating scientific information and Indigenous Tiwi knowledge to facilitate environmental management and conservation. We synthesized ecosystem information from previous research, field data, reports, and Tiwi knowledge authorities to develop a classification, descriptions, and a map of 14 terrestrial ecosystem types. These ecosystem types were defined and described based on ecological processes and were broader yet largely congruent with existing vegetation classifications. Including functional properties accounted for variation in the vegetation physiognomy exhibited by dynamic and disturbance‐prone ecosystems, such as savannas. Because we considered Tiwi knowledge authorities and the IUCN Global Ecosystem Typology, our inventory included ecosystem types that were typically omitted from previous classifications, which should allow for more comprehensive assessments and management. Relating the new ecosystem typology to the IUCN Global Ecosystem Typology will facilitate comparisons among similar ecosystems, regarding, for example, effective threat abatement options. Describing the biota and processes opens new avenues for monitoring. More collaborative work is needed to explore how Western scientific ecosystem inventories operate alongside and in connection with management of Tiwi murrakupuni enacted by Tiwi people. Given the ongoing loss of biodiversity, ecosystem management must draw on information across domains, scales, and knowledge systems. We demonstrated an approach to this task and provided socioecologically relevant ecosystem information.

SNAPSHOT USA 2019–2023: The First Five Years of Data From a Coordinated Camera Trap Survey of the United States - Brigit Rooney; Roland Kays; Michael V. Cove; Alex Jensen; Benjamin R. Goldstein; Christopher Pate; Paula Castiblanco; Maggie E. Abell; Jessie Adley; Briana Agenbroad; Adam A. Ahlers; Peter D. Alexander; et al. (Global Ecology and Biogeography, 2025)
Motivation SNAPSHOT USA is an annual, multicontributor camera trap survey of mammals across the United States. The growing SNAPSHOT USA dataset is intended for tracking the spatial and temporal responses of mammal populations to changes in land use, land cover and climate. These data will be useful for exploring the drivers of spatial and temporal changes in relative abundance and distribution, as well as the impacts of species interactions on daily activity patterns. Main Types of Variables Contained SNAPSHOT USA 2019–2023 contains 987,979 records of camera trap image sequence data and 9694 records of camera trap deployment metadata. Spatial Location and Grain Data were collected across the United States of America in all 50 states, 12 ecoregions and many ecosystems. Time Period and Grain Data were collected between 1st August and 29th December each year from 2019 to 2023. Major Taxa and Level of Measurement The dataset includes a wide range of taxa but is primarily focused on medium to large mammals. Software Format SNAPSHOT USA 2019–2023 comprises two .csv files. The original data can be found within the SNAPSHOT USA Initiative in the Wildlife Insights platform.

C9orf72-Associated Dipeptide Repeat Expansions Perturb ER-Golgi Vesicular Trafficking, Inducing Golgi Fragmentation and ER Stress, in ALS/FTD - Jessica Sultana; Audrey M. G. Ragagnin; Sonam Parakh; Sayanthooran Saravanabavan; Kai Ying Soo; Marta Vidal; Cyril Jones Jagaraj; Kunjie Ding; Sharlynn Wu; Sina Shadfar; Emily K. Don; Anand Deva; et al. (Molecular Neurobiology, 2024)
Hexanucleotide repeat expansions (HREs) in the chromosome 9 open reading frame 72 ( C9orf72 ) gene are the most frequent genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Both are debilitating neurodegenerative conditions affecting either motor neurons (ALS) in the brain and spinal cord or neurons in the frontal and/or temporal cortical lobes (FTD). HREs undergo repeat-associated non-ATG (RAN) translation on both sense and anti-sense strands, generating five distinct dipeptide repeat proteins (DPRs), poly-GA, -GR, -GP, -PA and -PR. Perturbed proteostasis is well-recognised in ALS pathogenesis, including processes affecting the endoplasmic reticulum (ER) and Golgi compartments. However, these mechanisms have not been well characterised for C9orf72-mediated ALS/FTD. In this study we demonstrate that C9orf72 DPRs polyGA, polyGR and polyGP (× 40 repeats) disrupt secretory protein transport from the ER to the Golgi apparatus in neuronal cells. Consistent with this finding, these DPRs also induce fragmentation of the Golgi apparatus, activate ER stress, and inhibit the formation of the omegasome, the precursor of the autophagosome that originates from ER membranes. We also demonstrate Golgi fragmentation in cells undergoing RAN translation that express polyGP. Furthermore, dysregulated ER-Golgi transport was confirmed in C9orf72 patient dermal fibroblasts. Evidence of aberrant ER-derived vesicles in spinal cord motor neurons from C9orf72 ALS patients compared to controls was also obtained. These data thus confirm that ER proteostasis and ER-Golgi transport is perturbed in C9orf72-ALS in the absence of protein over-expression. Hence this study identifies novel molecular mechanisms associated with the ER and Golgi compartments induced by the C9orf72 HRE.

Chalcophile element degassing at an active continental arc volcano - Emily M. Mason; Marie Edmonds; Samantha Hammond; Evgenia Ilyinskaya; Frances Jenner; Barbara Kunz; Emma J. Nicholson; Gabriela Velasquez (Geochimica et Cosmochimica Acta, 2024)

Spatially explicit ecosystem accounts for coastal wetland restoration - Micheli D. P. Costa; Melissa Wartman; Peter I. Macreadie; Lawrance W. Ferns; Rhiannon L. Holden; Daniel Ierodiaconou; Kimberley J. MacDonald; Tessa K. Mazor; Rebecca Morris; Emily Nicholson; Andrew Pomeroy; Elisa A. Zavadil; et al. (Ecosystem Services, 2024)

Corroboration and contradictions in global biodiversity indicators - Simone L. Stevenson; Kate Watermeyer; Simon Ferrier; Elizabeth A. Fulton; Hui Xiao; Emily Nicholson (Biological Conservation, 2024)

Uranus ring occultation observations: 1977–2006 - Richard G. French; Colleen A. McGhee-French; Mitchell Gordon; Richard L. Baron; Amanda S. Bosh; Marc W. Buie; Nancy Chanover; Mary Ann Clark; Edward W. Dunham; Linda M. French; Ian S. Glass; Jay D. Goguen; et al. (Icarus, 2023)

Prediction of disability-free survival in healthy older people - Johannes Tobias Neumann; Le T. P. Thao; Anne M. Murray; Emily Callander; Prudence R. Carr; Mark R. Nelson; Rory Wolfe; Robyn L. Woods; Christopher M. Reid; Raj C. Shah; Anne B. Newman; Jeff D. Williamson; et al. (GeroScience, 2022)
Prolonging survival in good health is a fundamental societal goal. However, the leading determinants of disability-free survival in healthy older people have not been well established. Data from ASPREE, a bi-national placebo-controlled trial of aspirin with 4.7 years median follow-up, was analysed. At enrolment, participants were healthy and without prior cardiovascular events, dementia or persistent physical disability. Disability-free survival outcome was defined as absence of dementia, persistent disability or death. Selection of potential predictors from amongst 25 biomedical, psychosocial and lifestyle variables including recognized geriatric risk factors, utilizing a machine-learning approach. Separate models were developed for men and women. The selected predictors were evaluated in a multivariable Cox proportional hazards model and validated internally by bootstrapping. We included 19,114 Australian and US participants aged ≥65 years (median 74 years, IQR 71.6–77.7). Common predictors of a worse prognosis in both sexes included higher age, lower Modified Mini-Mental State Examination score, lower gait speed, lower grip strength and abnormal (low or elevated) body mass index. Additional risk factors for men included current smoking, and abnormal eGFR. In women, diabetes and depression were additional predictors. The biased-corrected areas under the receiver operating characteristic curves for the final prognostic models at 5 years were 0.72 for men and 0.75 for women. Final models showed good calibration between the observed and predicted risks. We developed a prediction model in which age, cognitive function and gait speed were the strongest predictors of disability-free survival in healthy older people. Trial registration Clinicaltrials.gov (NCT01038583)

A guide to representing variability and uncertainty in biodiversity indicators - Jessica A. Rowland; Lucie M. Bland; Simon James; Emily Nicholson (Conservation Biology, 2021)
Biodiversity indicators are used to inform decisions and measure progress toward global targets, such as the United Nations Sustainable Development Goals. Indicators aggregate and simplify complex information, so underlying information influencing its reliability and interpretation (e.g., variability in data and uncertainty in indicator values) can be lost. Communicating uncertainty is necessary to ensure robust decisions and limit misinterpretations of trends, yet variability and uncertainty are rarely quantified in biodiversity indicators. We developed a guide to representing uncertainty and variability in biodiversity indicators. We considered the key purposes of biodiversity indicators and commonly used methods for representing uncertainty (standard error, bootstrap resampling, and jackknife resampling) and variability (quantiles, standard deviation, median absolute deviation, and mean absolute deviation) with intervals. Using 3 high‐profile biodiversity indicators (Red List Index, Living Planet Index, and Ocean Health Index), we tested the use, suitability, and interpretation of each interval method based on the formulation and data types underpinning the indicators. The methods revealed vastly different information; indicator formula and data distribution affected the suitability of each interval method. Because the data underpinning each indicator were not normally distributed, methods relying on normality or symmetrical spread were unsuitable. Quantiles, bootstrapping, and jackknifing provided useful information about the underlying variability and uncertainty. We built a decision tree to inform selection of the appropriate interval method to represent uncertainty or variation in biodiversity indicators, depending on data type and objectives. Our guide supports transparent and effective communication of biodiversity indicator trends to facilitate accurate interpretation by decision makers.

Combating ecosystem collapse from the tropics to the Antarctic - Dana M. Bergstrom; Barbara C. Wienecke; John van den Hoff; Lesley Hughes; David B. Lindenmayer; Tracy D. Ainsworth; Christopher M. Baker; Lucie Bland; David M. J. S. Bowman; Shaun T. Brooks; Josep G. Canadell; Andrew J. Constable; et al. (Global Change Biology, 2021)
Globally, collapse of ecosystems—potentially irreversible change to ecosystem structure, composition and function—imperils biodiversity, human health and well‐being. We examine the current state and recent trajectories of 19 ecosystems, spanning 58° of latitude across 7.7 M km 2 , from Australia's coral reefs to terrestrial Antarctica. Pressures from global climate change and regional human impacts, occurring as chronic ‘presses’ and/or acute ‘pulses’, drive ecosystem collapse. Ecosystem responses to 5–17 pressures were categorised as four collapse profiles—abrupt, smooth, stepped and fluctuating. The manifestation of widespread ecosystem collapse is a stark warning of the necessity to take action. We present a three‐step assessment and management framework (3As Pathway Awareness , Anticipation and Action ) to aid strategic and effective mitigation to alleviate further degradation to help secure our future.

Using decision science to evaluate global biodiversity indices - Kate E. Watermeyer; Gurutzeta Guillera‐Arroita; Payal Bal; Michael J. Burgass; Lucie M. Bland; Ben Collen; Chris Hallam; Luke T. Kelly; Michael A. McCarthy; Tracey J. Regan; Simone Stevenson; Brendan A. Wintle; et al. (Conservation Biology, 2021)
Global biodiversity indices are used to measure environmental change and progress toward conservation goals, yet few indices have been evaluated comprehensively for their capacity to detect trends of interest, such as declines in threatened species or ecosystem function. Using a structured approach based on decision science, we qualitatively evaluated 9 indices commonly used to track biodiversity at global and regional scales against 5 criteria relating to objectives, design, behavior, incorporation of uncertainty, and constraints (e.g., costs and data availability). Evaluation was based on reference literature for indices available at the time of assessment. We identified 4 key gaps in indices assessed: pathways to achieving goals (means objectives) were not always clear or relevant to desired outcomes (fundamental objectives); index testing and understanding of expected behavior was often lacking; uncertainty was seldom acknowledged or accounted for; and costs of implementation were seldom considered. These gaps may render indices inadequate in certain decision‐making contexts and are problematic for indices linked with biodiversity targets and sustainability goals. Ensuring that index objectives are clear and their design is underpinned by a model of relevant processes are crucial in addressing the gaps identified by our assessment. Uptake and productive use of indices will be improved if index performance is tested rigorously and assumptions and uncertainties are clearly communicated to end users. This will increase index accuracy and value in tracking biodiversity change and supporting national and global policy decisions, such as the post‐2020 global biodiversity framework of the Convention on Biological Diversity.

Matching biodiversity indicators to policy needs - Simone L. Stevenson; Kate Watermeyer; Giovanni Caggiano; Elizabeth A. Fulton; Simon Ferrier; Emily Nicholson (Conservation Biology, 2021)
At the global scale, biodiversity indicators are typically used to monitor general trends, but are rarely implemented with specific purpose or linked directly to decision making. Some indicators are better suited to predicting future change, others are more appropriate for evaluating past actions, but this is seldom made explicit. We developed a conceptual model for assigning biodiversity indicators to appropriate functions based on a common approach used in economics. Using the model, indicators can be classified as leading (indicators that change before the subject of interest, informing preventative actions), coincident (indicators that measure the subject of interest), or lagging (indicators that change after the subject of interest has changed and thus can be used to evaluate past actions). We classified indicators based on ecological theory on biodiversity response times and management objectives in 2 case studies: global species extinction and marine ecosystem collapse. For global species extinctions, indicators of abundance (e.g., the Living Planet Index or biodiversity intactness index) were most likely to respond first, as leading indicators that inform preventative action, while extinction indicators were expected to respond slowly, acting as lagging indicators flagging the need for evaluation. For marine ecosystem collapse, indicators of direct responses to fishing were expected to be leading, while those measuring ecosystem collapse could be lagging. Classification defines an active role for indicators within the policy cycle, creates an explicit link to preventative decision‐making, and supports preventative action.

Estimating changes and trends in ecosystem extent with dense time‐series satellite remote sensing - Calvin K.F. Lee; Emily Nicholson; Clare Duncan; Nicholas J. Murray (Conservation Biology, 2021)
Quantifying trends in ecosystem extent is essential to understanding the status of ecosystems. Estimates of ecosystem loss are widely used to track progress toward conservation targets, monitor deforestation, and identify ecosystems undergoing rapid change. Satellite remote sensing has become an important source of information for estimating these variables. Despite regular acquisition of satellite data, many studies of change in ecosystem extent use only static snapshots, which ignores considerable amounts of data. This approach limits the ability to explicitly estimate trend uncertainty and significance. Assessing the accuracy of multiple snapshots also requires time‐series reference data which is often very costly and sometimes impossible to obtain. We devised a method of estimating trends in ecosystem extent that uses all available Landsat satellite imagery. We used a dense time series of classified maps that explicitly accounted for covariates that affect extent estimates (e.g., time, cloud cover, and seasonality). We applied this approach to the Hukaung Valley Wildlife Sanctuary, Myanmar, where rapid deforestation is greatly affecting the lowland rainforest. We applied a generalized additive mixed model to estimate forest extent from more than 650 Landsat image classifications (1999–2018). Forest extent declined significantly at a rate of 0.274%/year (SE = 0.078). Forest extent declined from 91.70% (SE = 0.02) of the study area in 1999 to 86.52% (SE = 0.02) in 2018. Compared with the snapshot method, our approach improved estimated trends of ecosystem loss by allowing significance testing with confidence intervals and incorporation of nonlinear relationships. Our method can be used to identify significant trends over time, reduces the need for extensive reference data through time, and provides quantitative estimates of uncertainty.

Measuring impacts on species with models and metrics of varying ecological and computational complexity - Christopher D. Hallam; Brendan A. Wintle; Heini Kujala; Amy L. Whitehead; Emily Nicholson (Conservation Biology, 2020)
Approaches to assess the impacts of landscape disturbance scenarios on species range from metrics based on patterns of occurrence or habitat to comprehensive models that explicitly include ecological processes. The choice of metrics and models affects how impacts are interpreted and conservation decisions. We explored the impacts of 3 realistic disturbance scenarios on 4 species with different ecological and taxonomic traits. We used progressively more complex models and metrics to evaluate relative impact and rank of scenarios on the species. Models ranged from species distribution models that relied on implicit assumptions about environmental factors and species presence to highly parameterized spatially explicit population models that explicitly included ecological processes and stochasticity. Metrics performed consistently in ranking different scenarios in order of severity primarily when variation in impact was driven by habitat amount. However, they differed in rank for cases where dispersal dynamics were critical in influencing metapopulation persistence. Impacts of scenarios on species with low dispersal ability were better characterized using models that explicitly captured these processes. Metapopulation capacity provided rank orders that most consistently correlated with those from highly parameterized and data‐rich models and incorporated information about dispersal with little additional computational and data cost. Our results highlight the importance of explicitly considering species’ ecology, spatial configuration of habitat, and disturbance when choosing indicators of species persistence. We suggest using hybrid approaches that are a mixture of simple and complex models to improve multispecies assessments.

Stable isotopes infer the value of Australia’s coastal vegetated ecosystems from fisheries - Holger Jänes; Peter I. Macreadie; Emily Nicholson; Daniel Ierodiaconou; Simon Reeves; Matthew D. Taylor; Paul E. Carnell (Fish and Fisheries, 2020)
Wild capture fisheries provide substantial input to the global economy through employment and revenue. The coastal zone is especially productive, accounting for just 7% of the total area of the ocean, but supporting an estimated 50% of the world's fisheries. Vegetated coastal ecosystems—seagrass meadows, tidal marshes and mangrove forests—are widely cited as providing nutritional input that underpin coastal fisheries production; however, quantitative evidence of this relationship is scarce. Using Australia as a case study, we synthesized fisheries stable isotope data to estimate nutritional input derived from coastal vegetated ecosystems and combined these “proportional contribution” estimates with total annual catch data from commercial fisheries to determine species‐specific dollar values for coastal vegetated ecosystems. Based on the data from 96 commercially important fish species across Australian states (total landings 14 × 10 6 tonnes pa), we provide a conservative estimate that Australia's coastal vegetated ecosystems contribute at least 78 million AUD per year to the fisheries economy. Two thirds of this contribution came from tidal marshes and seagrasses that were both equally valued at 31.5 million AUD per year (39.4%) followed by mangroves at 14.9 million AUD per year (18.6%). The highest dollar values of coastal ecosystems originated from eastern king prawn ( Melicertus plebejus ) and giant mud crab ( Scylla serrata ). This study demonstrates the substantial economic value supported by Australia's coastal vegetated ecosystems through commercial fisheries harvest. These estimates create further impetus to conserve and restore coastal wetlands and maintain their support of coastal fisheries into the future.

Simultaneous‐count models to estimate abundance from counts of unmarked individuals with imperfect detection - Gerard Edward Ryan; Emily Nicholson; Jonathan C. Eames; Thomas N. E. Gray; Robin Loveridge; Simon P. Mahood; Phearun Sum; Michael A. McCarthy (Conservation Biology, 2019)
We developed a method to estimate population abundance from simultaneous counts of unmarked individuals over multiple sites. We considered that at each sampling occasion, individuals in a population could be detected at 1 of the survey sites or remain undetected and used either multinomial or binomial simultaneous‐count models to estimate abundance, the latter being equivalent to an N‐mixture model with one site. We tested model performance with simulations over a range of detection probabilities, population sizes, growth rates, number of years, sampling occasions, and sites. We then applied our method to 3 critically endangered vulture species in Cambodia to demonstrate the real‐world applicability of the model and to provide the first abundance estimates for these species in Cambodia. Our new approach works best when existing methods are expected to perform poorly (i.e., few sites and large variation in abundance among sites) and if individuals may move among sites between sampling occasions. The approach performed better when there were >8 sampling occasions and net probability of detection was high (>0.5). We believe our approach will be useful in particular for simultaneous surveys at aggregation sites, such as roosts. The method complements existing approaches for estimating abundance of unmarked individuals and is the first method designed specifically for simultaneous counts.

Remembering Dr. Ben Collen, an exemplary conservation biologist - Georgina M. Mace; E. J. Milner‐Gulland; Emily Nicholson (Conservation Biology, 2018)

Selecting and applying indicators of ecosystem collapse for risk assessments - Jessica A. Rowland; Emily Nicholson; Nicholas J. Murray; David A. Keith; Rebecca E. Lester; Lucie M. Bland (Conservation Biology, 2018)
Ongoing ecosystem degradation and transformation are major threats to biodiversity. Measuring ecosystem change toward collapse relies on monitoring indicators that quantify key ecological processes. Yet little guidance is available on selection and use of indicators for ecosystem risk assessment. We reviewed indicator use in ecological studies of ecosystem collapse in marine pelagic and temperate forest ecosystems. We examined indicator‐selection methods, indicator types (geographic distribution, abiotic, biotic), methods of assessing multiple indicators, and temporal quality of time series. We compared how these factors were applied in the ecological studies with how they were applied in risk assessments by using the International Union for Conservation of Nature's Red List of Ecosystems (RLE), for which indicators are used to estimate risk of ecosystem collapse. Ecological studies and RLE assessments rarely reported how indicators were selected, particularly in terrestrial ecosystems. Few ecological studies and RLE assessments quantified ecosystem change based on all 3 indicator types, and indicators types used differed between marine and terrestrial ecosystems. Several studies used indices or multivariate analyses to assess multiple indicators simultaneously, but RLE assessments did not because as RLE guidelines advise against them. Most studies and RLE assessments used time‐series data that spanned at least 30 years, which increases the probability of reliably detecting change. Limited use of indicator‐selection protocols and infrequent use of all 3 indicator types may hamper accurate detection of change. To improve the value of risk assessments for informing policy and management, we recommend using explicit protocols, including conceptual models, to identify and select indicators; a range of indicators spanning distributional, abiotic, and biotic features; indices and multivariate analyses with extreme care until guidelines are developed; time series with sufficient data to increase ability to accurately diagnose directional change; data from multiple sources to support assessments; and explicitly reporting steps in the assessment process.

Integrating Biological and Social Values When Prioritizing Places for Biodiversity Conservation - AMY L. WHITEHEAD; HEINI KUJALA; CHRISTOPHER D. IVES; ASCELIN GORDON; PIA E. LENTINI; BRENDAN A. WINTLE; EMILY NICHOLSON; CHRISTOPHER M. RAYMOND (Conservation Biology, 2014)
The consideration of information on social values in conjunction with biological data is critical for achieving both socially acceptable and scientifically defensible conservation planning outcomes. However, the influence of social values on spatial conservation priorities has received limited attention and is poorly understood. We present an approach that incorporates quantitative data on social values for conservation and social preferences for development into spatial conservation planning. We undertook a public participation GIS survey to spatially represent social values and development preferences and used species distribution models for 7 threatened fauna species to represent biological values. These spatially explicit data were simultaneously included in the conservation planning software Zonation to examine how conservation priorities changed with the inclusion of social data. Integrating spatially explicit information about social values and development preferences with biological data produced prioritizations that differed spatially from the solution based on only biological data. However, the integrated solutions protected a similar proportion of the species’ distributions, indicating that Zonation effectively combined the biological and social data to produce socially feasible conservation solutions of approximately equivalent biological value. We were able to identify areas of the landscape where synergies and conflicts between different value sets are likely to occur. Identification of these synergies and conflicts will allow decision makers to target communication strategies to specific areas and ensure effective community engagement and positive conservation outcomes. Integración de Valores Biológicos y Sociales al Priorizar Sitios para la Conservación de la Biodiversidad

The Why, What, and How of Global Biodiversity Indicators Beyond the 2010 Target - JULIA P. G. JONES; BEN COLLEN; GILES ATKINSON; PETER W. J. BAXTER; PHILIP BUBB; JANINE B. ILLIAN; TODD E. KATZNER; AIDAN KEANE; JONATHAN LOH; EVE MCDONALD‐MADDEN; EMILY NICHOLSON; HENRIQUE M. PEREIRA; et al. (Conservation Biology, 2011)
The 2010 biodiversity target agreed by signatories to the Convention on Biological Diversity directed the attention of conservation professionals toward the development of indicators with which to measure changes in biological diversity at the global scale. We considered why global biodiversity indicators are needed, what characteristics successful global indicators have, and how existing indicators perform. Because monitoring could absorb a large proportion of funds available for conservation, we believe indicators should be linked explicitly to monitoring objectives and decisions about which monitoring schemes deserve funding should be informed by predictions of the value of such schemes to decision making. We suggest that raising awareness among the public and policy makers, auditing management actions, and informing policy choices are the most important global monitoring objectives. Using four well‐developed indicators of biological diversity (extent of forests, coverage of protected areas, Living Planet Index, Red List Index) as examples, we analyzed the characteristics needed for indicators to meet these objectives. We recommend that conservation professionals improve on existing indicators by eliminating spatial biases in data availability, fill gaps in information about ecosystems other than forests, and improve understanding of the way indicators respond to policy changes. Monitoring is not an end in itself, and we believe it is vital that the ultimate objectives of global monitoring of biological diversity inform development of new indicators.

Establishing IUCN Red List Criteria for Threatened Ecosystems - JON PAUL RODRÍGUEZ; KATHRYN M. RODRÍGUEZ‐CLARK; JONATHAN E. M. BAILLIE; NEVILLE ASH; JOHN BENSON; TIMOTHY BOUCHER; CLAIRE BROWN; NEIL D. BURGESS; BEN COLLEN; MICHAEL JENNINGS; DAVID A. KEITH; EMILY NICHOLSON; et al. (Conservation Biology, 2011)
The potential for conservation of individual species has been greatly advanced by the International Union for Conservation of Nature's (IUCN) development of objective, repeatable, and transparent criteria for assessing extinction risk that explicitly separate risk assessment from priority setting. At the IV World Conservation Congress in 2008, the process began to develop and implement comparable global standards for ecosystems. A working group established by the IUCN has begun formulating a system of quantitative categories and criteria, analogous to those used for species, for assigning levels of threat to ecosystems at local, regional, and global levels. A final system will require definitions of ecosystems; quantification of ecosystem status; identification of the stages of degradation and loss of ecosystems; proxy measures of risk (criteria); classification thresholds for these criteria; and standardized methods for performing assessments. The system will need to reflect the degree and rate of change in an ecosystem's extent, composition, structure, and function, and have its conceptual roots in ecological theory and empirical research. On the basis of these requirements and the hypothesis that ecosystem risk is a function of the risk of its component species, we propose a set of four criteria: recent declines in distribution or ecological function, historical total loss in distribution or ecological function, small distribution combined with decline, or very small distribution. Most work has focused on terrestrial ecosystems, but comparable thresholds and criteria for freshwater and marine ecosystems are also needed. These are the first steps in an international consultation process that will lead to a unified proposal to be presented at the next World Conservation Congress in 2012.

Assessing the Threat Status of Ecological Communities - EMILY NICHOLSON; DAVID A. KEITH; DAVID S. WILCOVE (Conservation Biology, 2009)
Conservationists are increasingly interested in determining the threat status of ecological communities as a key part of their planning efforts. Such assessments are difficult because of conceptual challenges and a lack of generally accepted criteria. We reviewed 12 protocols for assessing the threat status of communities and identified conceptual and operational issues associated with developing a rigorous, transparent, and universal set of criteria for assessing communities, analogous to the International Union for Conservation of Nature (IUCN) Red List standards for species. We examined how each protocol defines a community and its extinction and how each applies 3 overarching criteria: decline in geographic distribution, restricted geographic distribution, and changes to ecological function. The protocols vary widely in threshold values used to assess declines and distribution size and the time frames used to assess declines, leading to inconsistent assessments of threat status. Few of the protocols specify a scale for measuring distribution size, although assessment outcomes are highly sensitive to scale. Protocols that apply different thresholds for species versus communities tend to require greater declines and more restricted distributions for communities than species to be listed in equivalent threat categories. Eleven of the protocols include a reduction in ecological function as a criterion, but almost all assess it qualitatively rather than quantitatively. We argue that criteria should be explicit and repeatable in their concepts, parameters, and scale, applicable to a broad range of communities, and address synergies between types of threats. Such criteria should focus on distribution size, declines in distribution, and changes to key ecological functions, with the latter based on workable proxies for assessing the severity, scope, and immediacy of degradation. Threat categories should be delimited by thresholds that are assessed at standard scales and are logically consistent with the viability of component species and important ecological functions.

A new method for conservation planning for the persistence of multiple species - Emily Nicholson; Michael I. Westphal; Karin Frank; Wayne A. Rochester; Robert L. Pressey; David B. Lindenmayer; Hugh P. Possingham (Ecology Letters, 2006)
Although the aim of conservation planning is the persistence of biodiversity, current methods trade‐off ecological realism at a species level in favour of including multiple species and landscape features. For conservation planning to be relevant, the impact of landscape configuration on population processes and the viability of species needs to be considered. We present a novel method for selecting reserve systems that maximize persistence across multiple species, subject to a conservation budget. We use a spatially explicit metapopulation model to estimate extinction risk, a function of the ecology of the species and the amount, quality and configuration of habitat. We compare our new method with more traditional, area‐based reserve selection methods, using a ten‐species case study, and find that the expected loss of species is reduced 20‐fold. Unlike previous methods, we avoid designating arbitrary weightings between reserve size and configuration; rather, our method is based on population processes and is grounded in ecological theory.

Objectives for Multiple‐Species Conservation Planning - EMILY NICHOLSON; HUGH P. POSSINGHAM (Conservation Biology, 2006)
The first step in conservation planning is to identify objectives. Most stated objectives for conservation, such as to maximize biodiversity outcomes, are too vague to be useful within a decision‐making framework. One way to clarify the issue is to define objectives in terms of the risk of extinction for multiple species. Although the assessment of extinction risk for single species is common, few researchers have formulated an objective function that combines the extinction risks of multiple species. We sought to translate the broad goal of maximizing the viability of species into explicit objectives for use in a decision‐theoretic approach to conservation planning. We formulated several objective functions based on extinction risk across many species and illustrated the differences between these objectives with simple examples. Each objective function was the mathematical representation of an approach to conservation and emphasized different levels of threat. Our objectives included minimizing the joint probability of one or more extinctions, minimizing the expected number of extinctions, and minimizing the increase in risk of extinction from the best‐case scenario. With objective functions based on joint probabilities of extinction across species, any correlations in extinction probabilities had to be known or the resultant decisions were potentially misleading. Additive objectives, such as the expected number of extinctions, did not produce the same anomalies. We demonstrated that the choice of objective function is central to the decision‐making process because alternative objective functions can lead to a different ranking of management options. Therefore, decision makers need to think carefully in selecting and defining their conservation goals.