Global mismatches between threat mapping research effort and the potential of threat abatement actions to reduce extinction risk.

Threat mapping is a necessary tool for identifying and abating direct threats to species in the ongoing extinction crisis. There are known gaps in the threat mapping literature for particular threats and geographic locations, and it remains unclear if the distribution of research effort is appropriately targeted relative to conservation need. We aimed to determine the drivers of threat mapping research effort and to quantify gaps that, if filled, could inform actions with the highest potential to reduce species' extinction risk. We used a negative binomial generalized linear model to analyze research effort as a function of threat abatement potential (quantified as the potential reduction in species extinction risk from abating threats), species richness, land area, and human pressure. The model showed that threat mapping research effort increased by 1.1 to 1.2 times per standardized unit change in threat abatement potential. However, species richness and land area were stronger predictors of research effort overall. The greatest areas of mismatch between research effort and threat abatement potential, receiving disproportionately low research effort, were related to the threats to species of agriculture, aquaculture, and biological resource use across the tropical regions of the Americas, Asia, and Madagascar. Conversely, the threat of linear infrastructure (e.g., roads and rails) across regions, the threat of biological resource use (e.g., hunting or collection) in sub-Saharan Africa, and overall threats in North America and Europe all received disproportionately high research effort. We discuss the range of methodological and sociopolitical factors that may be behind the overall trends and specific areas of mismatch we found. We urge a stronger emphasis on targeting research effort toward those threats and geographic locations where threat abatement activities could make the greatest contribution to reducing global species extinction risk.

Disparidades mundiales entre la investigación sobre el esfuerzo de mapeo de amenazas y la potencial amenaza de las acciones de abatimiento para reducir el riesgo de extinción Resumen El mapeo de amenazas es una herramienta necesaria para identificar y abatir las amenazas directas para las especies en la actual crisis de extinción. Existen vacíos conocidos en la literatura del mapeo de amenazas para amenazas particulares y ubicaciones geográficas, y todavía no está claro si la distribución de los esfuerzos de investigación está enfocada de forma apropiada en relación con las necesidades de conservación. Buscamos determinar los factores que influyen sobre el esfuerzo de investigación del mapeo de amenazas y cuantificar los vacíos que, si se cierran, podrían guiar las acciones con el potencial más alto para reducir el riesgo de extinción de las especies. Usamos un modelo binomial lineal negativo generalizado para analizar el esfuerzo de investigación como función del potencial de abatimiento de amenazas (cuantificado como la reducción potencial en el riesgo de extinción a partir del abatimiento de amenazas), la riqueza de especies, el área del suelo y la presión humana. El modelo mostró que el esfuerzo de investigación del mapeo de amenazas incrementó entre 1.1 y 1.2 veces por unidad estandarizada de cambio en el potencial de abatimiento de amenazas. Sin embargo, la riqueza de especies y el área del suelo fueron pronósticos más sólidos del esfuerzo de investigación generalizado. Las principales áreas de disparidad entre el esfuerzo de investigación y el potencial de abatimiento de amenazas, las cuales reciben un esfuerzo de investigación desproporcionalmente bajo, estuvieron relacionadas con las amenazas para las especies de agricultura, acuacultura y recursos biológicos que se usan en las regiones tropicales de América, Asia y Madagascar. Al contrario, la amenaza de la infraestructura lineal (p. ej.: carreteras y vías férreas) en las regiones, la amenaza del uso de recursos biológicos (p. ej.: caza o recolección) en la África subsahariana y las amenazas generales en América del Norte y en Europa recibieron un esfuerzo de investigación desproporcionalmente alto. Abordamos el rango de factores metodológicos y sociopolíticos que pueden estar detrás de las tendencias generales y las áreas específicas de disparidad que encontramos. Instamos a un mayor énfasis en el enfoque del esfuerzo de investigación hacia aquellas amenazas y ubicaciones geográficas en donde las actividades de abatimiento de amenazas podrían brindar una mayor contribución para reducir el riesgo mundial de extinción de especies.

Quantifying and mapping species threat abatement opportunities to support national target setting.

The successful implementation of the Convention on Biological Diversity's post-2020 Global Biodiversity Framework will rely on effective translation of targets from global to national level and increased engagement across diverse sectors of society. Species conservation targets require policy support measures that can be applied to a diversity of taxonomic groups, that link action targets to outcome goals, and that can be applied to both global and national data sets to account for national context, which the species threat abatement and restoration (STAR) metric does. To test the flexibility of STAR, we applied the metric to vascular plants listed on national red lists of Brazil, Norway, and South Africa. The STAR metric uses data on species' extinction risk, distributions, and threats, which we obtained from national red lists to quantify the contribution that threat abatement and habitat restoration activities could make to reducing species' extinction risk. Across all 3 countries, the greatest opportunity for reducing plant species' extinction risk was from abating threats from agricultural activities, which could reduce species' extinction risk by 54% in Norway, 36% in South Africa, and 29% in Brazil. Species extinction risk could be reduced by a further 21% in South Africa by abating threats from invasive species and by 21% in Brazil by abating threats from urban expansion. Even with different approaches to red-listing among countries, the STAR metric yielded informative results that identified where the greatest conservation gains could be made for species through threat-abatement and restoration activities. Quantifiably linking local taxonomic coverage and data collection to global processes with STAR would allow national target setting to align with global targets and enable state and nonstate actors to measure and report on their potential contributions to species conservation.

Quantifying and categorising national extinction-risk footprints.

Biodiversity, essential to delivering the ecosystem services that support humanity, is under threat. Projections show that loss of biodiversity, specifically increases in species extinction, is likely to continue without significant intervention. Human activity is the principal driver of this loss, generating direct threats such as habitat loss and indirect threats such as climate change. Often, these threats are induced by consumption of products and services in locations far-removed from the affected species, creating a geographical displacement between cause and effect. Here we quantify and categorise extinction-risk footprints for 188 countries. Seventy-six countries are net importers of extinction-risk footprint, 16 countries are net exporters of extinction-risk footprint, and in 96 countries domestic consumption is the largest contributor to the extinction-risk footprint. These profiles provide insight into the underlying sources of consumption which contribute to species extinction risk, a valuable input to the formulation of interventions aimed at transforming humanity's interactions with biodiversity.

A metric for spatially explicit contributions to science-based species targets.

The Convention on Biological Diversity's post-2020 Global Biodiversity Framework will probably include a goal to stabilize and restore the status of species. Its delivery would be facilitated by making the actions required to halt and reverse species loss spatially explicit. Here, we develop a species threat abatement and restoration (STAR) metric that is scalable across species, threats and geographies. STAR quantifies the contributions that abating threats and restoring habitats in specific places offer towards reducing extinction risk. While every nation can contribute towards halting biodiversity loss, Indonesia, Colombia, Mexico, Madagascar and Brazil combined have stewardship over 31% of total STAR values for terrestrial amphibians, birds and mammals. Among actions, sustainable crop production and forestry dominate, contributing 41% of total STAR values for these taxonomic groups. Key Biodiversity Areas cover 9% of the terrestrial surface but capture 47% of STAR values. STAR could support governmental and non-state actors in quantifying their contributions to meeting science-based species targets within the framework.

Occupancy versus colonization-extinction models for projecting population trends at different spatial scales.

Understanding spatiotemporal population trends and their drivers is a key aim in population ecology. We further need to be able to predict how the dynamics and sizes of populations are affected in the long term by changing landscapes and climate. However, predictions of future population trends are sensitive to a range of modeling assumptions. Deadwood-dependent fungi are an excellent system for testing the performance of different predictive models of sessile species as these species have different rarity and spatial population dynamics, the populations are structured at different spatial scales, and they utilize distinct substrates. We tested how the projected large-scale occupancies of species with differing landscape-scale occupancies are affected over the coming century by different modeling assumptions. We compared projections based on occupancy models against colonization-extinction models, conducting the modeling at alternative spatial scales and using fine- or coarse-resolution deadwood data. We also tested effects of key explanatory variables on species occurrence and colonization-extinction dynamics. The hierarchical Bayesian models applied were fitted to an extensive repeated survey of deadwood and fungi at 174 patches. We projected higher occurrence probabilities and more positive trends using the occupancy models compared to the colonization-extinction models, with greater difference for the species with lower occupancy, colonization rate, and colonization:extinction ratio than for the species with higher estimates of these statistics. The magnitude of future increase in occupancy depended strongly on the spatial modeling scale and resource resolution. We encourage using colonization-extinction models over occupancy models, modeling the process at the finest resource-unit resolution that is utilizable by the species, and conducting projections for the same spatial scale and resource resolution at which the model fitting is conducted. Further, the models applied should include key variables driving the metapopulation dynamics, such as the availability of suitable resource units, habitat quality, and spatial connectivity.

Forest management could counteract distribution retractions forced by climate change.

Climate change is expected to drive the distribution retraction of northern species. However, particularly in regions with a history of intensive exploitation, changes in habitat management could facilitate distribution expansions counter to expectations under climate change. Here, we test the potential for future forest management to facilitate the southward expansion of an old-forest species from the boreal region into the boreo-nemoral region, contrary to expectations under climate change. We used an ensemble of species distribution models based on citizen science data to project the response of Phellinus ferrugineofuscus, a red-listed old-growth indicator, wood-decaying fungus, to six forest management and climate change scenarios. We projected change in habitat suitability across the boreal and boreo-nemoral regions of Sweden for the period 2020-2100. Scenarios varied in the proportion of forest set aside from production, the level of timber extraction, and the magnitude of climate change. Habitat suitabilities for the study species were projected to show larger relative increases over time in the boreo-nemoral region compared to the boreal region, under all scenarios. By 2100, mean suitabilities in set-aside forest in the boreo-nemoral region were similar to the suitabilities projected for set-aside forest in the boreal region in 2020, suggesting that occurrence in the boreo-nemoral region could be increased. However, across all scenarios, consistently higher projected suitabilities in set-aside forest in the boreal region indicated that the boreal region remained the species stronghold. Furthermore, negative effects of climate change were evident in the boreal region, and projections suggested that climatic changes may eventually counteract the positive effects of forest management in the boreo-nemoral region. Our results suggest that the current rarity of this old-growth indicator species in the boreo-nemoral region may be due to the history of intensive forestry. Forest management therefore has the potential to compensate for the negative effects of climate change. However, increased occurrence at the southern range edge would depend on the dispersal and colonization ability of the species. An increase in the amount of set-aside forest across both the boreal and boreo-nemoral regions is therefore likely to be required to prevent the decline of old-forest species under climate change.

Evaluating citizen science data for forecasting species responses to national forest management.

The extensive spatial and temporal coverage of many citizen science datasets (CSD) makes them appealing for use in species distribution modeling and forecasting. However, a frequent limitation is the inability to validate results. Here, we aim to assess the reliability of CSD for forecasting species occurrence in response to national forest management projections (representing 160,366 km2) by comparison against forecasts from a model based on systematically collected colonization-extinction data. We fitted species distribution models using citizen science observations of an old-forest indicator fungus Phellinus ferrugineofuscus. We applied five modeling approaches (generalized linear model, Poisson process model, Bayesian occupancy model, and two MaxEnt models). Models were used to forecast changes in occurrence in response to national forest management for 2020-2110. Forecasts of species occurrence from models based on CSD were congruent with forecasts made using the colonization-extinction model based on systematically collected data, although different modeling methods indicated different levels of change. All models projected increased occurrence in set-aside forest from 2020 to 2110: the projected increase varied between 125% and 195% among models based on CSD, in comparison with an increase of 129% according to the colonization-extinction model. All but one model based on CSD projected a decline in production forest, which varied between 11% and 49%, compared to a decline of 41% using the colonization-extinction model. All models thus highlighted the importance of protected old forest for P. ferrugineofuscus persistence. We conclude that models based on CSD can reproduce forecasts from models based on systematically collected colonization-extinction data and so lead to the same forest management conclusions. Our results show that the use of a suite of models allows CSD to be reliably applied to land management and conservation decision making, demonstrating that widely available CSD can be a valuable forecasting resource.

Local epiphyte establishment and future metapopulation dynamics in landscapes with different spatiotemporal properties.

Understanding the relative importance of different ecological processes on the metapopulation dynamics of species is the basis for accurately forecasting metapopulation size in fragmented landscapes. Successful local colonization depends on both species dispersal range and how local habitat conditions affect establishment success. Moreover, there is limited understanding of the effects of different spatiotemporal landscape properties on future metapopulation size. We investigate which factors drive the future metapopulation size of the epiphytic model lichen species Lobaria pulmonaria in a managed forest landscape. First, we test the importance of dispersal and local conditions on the colonization-extinction dynamics of the species using Bayesian state-space modelling of a large-scale data set collected over a 10-yr period. Second, we test the importance of dispersal and establishment limitation in explaining establishment probability and subsequent local population growth, based on a 10-yr propagule sowing experiment. Third, we test how future metapopulation size is affected by different metapopulation and spatiotemporal landscape dynamics, using simulations with the metapopulation models fitted to the empirical data. The colonization probability increased with tree inclination and connectivity, with a mean dispersal distance of 97 m (95% credible intervals, 5-530 m). Local extinctions were mainly deterministic set by tree mortality, but also by tree cutting by forestry. No experimental establishments took place on clearcuts, and in closed forest the establishment probability was higher on trees growing on moist than on dry-mesic soils. The subsequent local population growth rate increased with increasing bark roughness. The simulations showed that the restricted dispersal range estimated (compared to non-restricted dispersal range), and short tree rotation length (65 yr instead of 120) had approximately the same negative effects on future metapopulation size, while regeneration of trees creating a random tree pattern instead of an aggregated one had only some negative effect. However, using the colonization rate obtained with the experimentally added diaspores led to a considerable increase in metapopulation size, making the dispersal limitation of the species clear. The future metapopulation size is thus set by the number of host trees located in shady conditions, not isolated from occupied trees, and by the rotation length of these host trees.

Explaining Spatial Variation in the Recording Effort of Citizen Science Data across Multiple Taxa.

The collation of citizen science data in open-access biodiversity databases makes temporally and spatially extensive species' observation data available to a wide range of users. Such data are an invaluable resource but contain inherent limitations, such as sampling bias in favour of recorder distribution, lack of survey effort assessment, and lack of coverage of the distribution of all organisms. Any technical assessment, monitoring program or scientific research applying citizen science data should therefore include an evaluation of the uncertainty of its results. We use 'ignorance' scores, i.e. spatially explicit indices of sampling bias across a study region, to further understand spatial patterns of observation behaviour for 13 reference taxonomic groups. The data is based on voluntary observations made in Sweden between 2000 and 2014. We compared the effect of six geographical variables (elevation, steepness, population density, log population density, road density and footpath density) on the ignorance scores of each group. We found substantial variation among taxonomic groups in the relative importance of different geographic variables for explaining ignorance scores. In general, road access and logged population density were consistently important variables explaining bias in sampling effort, indicating that access at a landscape-scale facilitates voluntary reporting by citizen scientists. Also, small increases in population density can produce a substantial reduction in ignorance score. However the between-taxa variation in the importance of geographic variables for explaining ignorance scores demonstrated that different taxa suffer from different spatial biases. We suggest that conservationists and researchers should use ignorance scores to acknowledge uncertainty in their analyses and conclusions, because they may simultaneously include many correlated variables that are difficult to disentangle.