Search

The COVID-19 pandemic has disrupted HPV vaccination programmes worldwide. Using an agent-based model, EpiMetHeos, recently calibrated to Indian data, we illustrate how shifting from a girls-only (GO) to a gender-neutral (GN) vaccination strategy could improve the resilience of cervical cancer prevention against disruption of HPV vaccination. In the base case of 5-year disruption with no coverage, shifting from GO to GN strategy under 60% coverage (before disruption) would increase the resilience, in terms of cervical cancer cases still prevented in the disrupted birth cohorts per 100,000 girls born, by 2.8-fold from 107 to 302 cases, and by 2.2-fold from 209 to 464 cases under 90% coverage. Furthermore, shifting to GN vaccination helped in reaching the World Health Organization (WHO) elimination threshold. Under GO vaccination with 60% coverage, the age-standardised incidence rate of cervical cancer in India in the long term with vaccination decreased from 11.0 to 4.7 cases per 100,000 woman-years (above threshold), as compared to 2.8 cases (below threshold) under GN with 60% coverage and 2.4 cases (below threshold) under GN with 90% coverage. In conclusion, GN HPV vaccination is an effective strategy to improve the resilience to disruption of cancer prevention programmes and to enhance the progress towards cervical cancer elimination. [ABSTRACT FROM AUTHOR]

Local cervical cancer epidemiological data essential to project the context-specific impact of cervical cancer preventive measures are often missing. We developed a framework, hereafter named Footprinting, to approximate missing data on sexual behaviour, human papillomavirus (HPV) prevalence, or cervical cancer incidence, and applied it to an Indian case study. With our framework, we (1) identified clusters of Indian states with similar cervical cancer incidence patterns, (2) classified states without incidence data to the identified clusters based on similarity in sexual behaviour, (3) approximated missing cervical cancer incidence and HPV prevalence data based on available data within each cluster. Two main patterns of cervical cancer incidence, characterized by high and low incidence, were identified. Based on the patterns in the sexual behaviour data, all Indian states with missing data on cervical cancer incidence were classified to the low-incidence cluster. Finally, missing data on cervical cancer incidence and HPV prevalence were approximated based on the mean of the available data within each cluster. With the Footprinting framework, we approximated missing cervical cancer epidemiological data and made context-specific impact projections for cervical cancer preventive measures, to assist public health decisions on cervical cancer prevention in India and other countries. [ABSTRACT FROM AUTHOR]

Background: Despite the high burden of cervical cancer, access to preventive measures remains low in India. A single-dose immunisation schedule could facilitate the scale-up of human papillomavirus (HPV) vaccination, contributing to global elimination of cervical cancer. We projected the effect of single-dose quadrivalent HPV vaccination in India in comparison with no vaccination or to a two-dose schedule.Methods: In this modelling study, we adapted an HPV transmission model (EpiMetHeos) to Indian data on sexual behaviour (from the Demographic and Health Survey and the Indian National AIDS Control Organisation), HPV prevalence data (from two local surveys, from the states of Tamil Nadu and West Bengal), and cervical cancer incidence data (from Cancer Incidence in Five Continents for the period 2008-12 [volume XI], and the Indian National Centre for Disease Informatics and Research for the period 2012-16). Using the model, we projected the nationwide and state-specific effect of HPV vaccination on HPV prevalence and cervical cancer incidence, and lifetime risk of cervical cancer, for 100 years after the introduction of vaccination or in the first 50 vaccinated birth cohorts. Projections were derived under a two-dose vaccination scenario assuming life-long protection and under a single-dose vaccination scenario with protection duration assumptions derived from International Agency for Research on Cancer (IARC) India vaccine trial data, in combination with different vaccination coverages and catch-up vaccination age ranges. We used two thresholds to define cervical cancer elimination: an age-standardised incidence rate of less than 4 cases per 100 000 woman-years, and standardised lifetime risk of less than 250 cases per 100 000 women born.Findings: Assuming vaccination in girls aged 10 years, with 90% coverage, and life-long protection by two-dose or single-dose schedule, HPV vaccination could reduce the prevalence of HPV16 and HPV18 infection by 97% (80% UI 96-99) in 50 years, and the lifetime risk of cervical cancer by 71-78% from 1067 cases per 100 000 women born under a no vaccination scenario to 311 (80% UI 284-339) cases per 100 000 women born in the short term and 233 (219-252) cases per 100 000 women born in the long term in vaccinated cohorts. Under this scenario, we projected that the age-standardised incidence rate threshold for elimination could be met across India (range across Indian states: 1·6 cases [80% UI 1·5-1·7] to 4·0 cases [3·8-4·4] per 100 000 woman-years), while the complementary threshold based on standardised lifetime risk was attainable in 17 (68%) of 25 states, but not nationwide (range across Indian states: 207 cases [80% UI 194-223] to 477 cases [447-514] per 100 000 women born). Under the considered assumptions of waning vaccine protection, single-dose vaccination was projected to have a 21-100% higher per-dose efficiency than two-dose vaccination. Single-dose vaccination with catch-up for girls and women aged 11-20 years was more impactful than two-dose vaccination without catch-up, with reduction of 39-65% versus 38% in lifetime risk of cervical cancer across the ten catch-up birth cohorts and the first ten routine vaccination birth cohorts.Interpretation: Our evidence-based projections suggest that scaling up cervical cancer prevention through single-dose HPV vaccination could substantially reduce cervical cancer burden in India.Funding: The Bill & Melinda Gates Foundation. [ABSTRACT FROM AUTHOR]

Predictions of cervical cancer burden and the impact of measures taken to control this cancer are usually data-demanding and based on complex assumptions. We propose a predictive method (called PANDORA) based on human papillomavirus (HPV) prevalence, measured 1993–2008, and cervical cancer incidence (CCI), measured 1993–2012, in the same birth cohorts from different worldwide locations, informed by data on age at detection of high-risk HPV and sexual debut. The model can predict CCI among high-risk HPV–positive women and predict CCI up to 14 years following high-risk HPV detection. We found CCI to increase during the 14 years following high-risk HPV detection in unscreened women aged <35 years but to remain mainly constant among women ≥35 years. Age at sexual debut was a significant modifier of CCI. Using our model, we accurately reproduced CCI among high-risk HPV–positive women as observed in cohort studies and in the general population of multiple countries. We also predicted the annual number of cervical cancer cases and CCI in locations with HPV prevalence data but no cancer registry. These findings could inform cervical cancer control programs in settings without cancer registries, as they can be used to predict future cervical cancer burden from population-based surveys of HPV prevalence. [ABSTRACT FROM AUTHOR]

Background Men who have sex with men (MSM) without HIV are known to be at elevated relative risk for Human papillomavirus (HPV)-associated anal cancer in comparison to men who have sex with women (MSW), but are poorly characterized in terms of anal cancer incidence due to absence of reporting of sexual behavior/identity at a population-level. Methods By combining age-specific statistics from multiple data sources (anal cancer incidence among all males; anal cancer incidence among MSM and MSW with HIV; population size of men with HIV by sexual orientation), we developed a mathematical model to estimate anal cancer incidence, annual number of cases, and proportion by (a) sexual orientation (MSM versus MSW), (b) HIV status, and (c) age (<30, 30–44, 45–59, and ≥60 years). Results Anal cancer incidence (per 100 000) among MSM without HIV was 1.4 (95% uncertainty interval [UI], 0.6 to 2.3), 17.6 (95% UI = 13.8–23.5), and 33.9 (95% UI = 28.3–42.3), at ages 30–44, 45–59 and ≥60 years, respectively. 19.1% of all male anal cancer occurred in MSM without HIV, increasing from 4% of anal cancer diagnosed at 30–44 years to 24% at ≥60 years; 54.3% occurred in MSW without HIV (increasing from 13% at age 30–44 to 67% at >60 years), and the remaining 26.6% in men (MSM and MSW combined) with HIV (decreasing from 83% at age 30–44 to 9% at >60 years). Conclusions These findings should inform anal cancer prevention recommendations in male risk groups, including, for the first time, for the important group of MSM without HIV. [ABSTRACT FROM AUTHOR]

Vegetation is a key driver of ecosystem functioning (e.g. productivity and stability) and of the maintenance of biodiversity (e.g. creating habitats for other species groups). While vegetation sensitivity to climate change has been widely investigated, its spatio-temporally response to the dual effects of land management and climate change has been ignored at landscape scale. Here we use a dynamic vegetation model called FATE-HD, which describes the dominant vegetation dynamics and associated functional diversity, in order to anticipate vegetation response to climate and land-use changes in both short and long-term perspectives. Using three contrasted management scenarios for the Ecrins National Park (French Alps) developed in collaboration with the park managers, and one regional climate change scenario, we tracked the dynamics of vegetation structure (forest expansion) and functional diversity over 100 yr of climate change and a further 400 additional years of stabilization. As expected, we observed a slow upward shift in forest cover distribution, which appears to be severely impacted by pasture management (i.e. maintenance or abandonment). The time lag before observing changes in vegetation cover was the result of demographic and seed dispersal processes. However, plant diversity response to environmental changes was rapid. After land abandonment, local diversity increased and spatial turnover was reduced, whereas local diversity decreased following land use intensification. Interestingly, in the long term, as both climate and management scenarios interacted, the regional diversity declined. Our innovative spatio-temporally explicit framework demonstrates that the vegetation may have contrasting responses to changes in the short and the long term. Moreover, climate and land-abandonment interact extensively leading to a decrease in both regional diversity and turnover in the long term. Based on our simulations we therefore suggest a continuing moderate intensity pasturing to maintain high levels of plant diversity in this system. [ABSTRACT FROM AUTHOR]

Aim To incorporate changes in alpine land cover (tree line shift, glacier retreat and primary succession) into species distribution model ( SDM) predictions for a selection of 31 high-elevation plants. Location Chamonix Valley, French Alps. Methods We fit linear mixed effects ( LME) models to historical changes in forest and glacier cover and projected these trends forward to align with 21st century IPCC climate scenarios. We used a logistic function to model the probability of plant establishment in glacial forelands zones expected to become ice free between 2008 and 2051-2080. Habitat filtering consisted of intersecting land cover maps with climate-driven SDMs to refine habitat suitability predictions. SDM outputs for tree, heath and alpine species were compared based on whether habitat filtering during the prediction period was carried out using present-day (static) land cover, future (dynamic) land cover filters or no land cover filter (unfiltered). Species range change ( SRC) was used to measure differences in habitat suitability predictions across methods. Results LME predictions for 2021-2080 showed continued glacier retreat, tree line rise and primary succession in glacier forelands. SRC was highest in the unfiltered scenario (−10%), intermediate in the dynamic scenario (−15%) and lowest in the static scenario (−31%). Tree species were the only group predicted to gain overall range by 2051-2080. Although alpine plants lost range in all three land cover scenarios, new habitat made available by glacier retreat in the dynamic land cover scenario buffered alpine plant range loss due to climate change. Main conclusions We provide a framework for combining trajectories of land cover change with SDM predictions. Our pilot study shows that incorporating shifts in land cover improves habitat suitability predictions and leads to contrasting outcomes of future mountain plant distribution. Alpine plants in particular may lose less suitable habitat than standard SDMs predict due to 21st century glacier retreat. [ABSTRACT FROM AUTHOR]

Although our knowledge on the stabilising role of biodiversity and on how it is affected by perturbations has greatly improved, we still lack a comprehensive view on ecosystem stability that is transversal to different habitats and perturbations. Hence, we propose a framework that takes advantage of the multiplicity of components of an ecosystem and their contribution to stability. Ecosystem components can range from species or functional groups, to different functional traits, or even the cover of different habitats in a landscape mosaic. We make use of n-dimensional hypervolumes to define ecosystem states and assess how much they shift after environmental changes have occurred. We demonstrate the value of this framework with a study case on the effects of environmental change on Alpine ecosystems. Our results highlight the importance of a multidimensional approach when studying ecosystem stability and show that our framework is flexible enough to be applied to different types of ecosystem components, which can have important implications for the study of ecosystem stability and transient dynamics. [ABSTRACT FROM AUTHOR]

Phylogenetic Generalized Least Square (PGLS) is the tool of choice among phylogenetic comparative methods to measure the correlation between species features such as morphological and life-history traits or niche characteristics. In its usual form, it assumes that the residual variation follows a homogenous model of evolution across the branches of the phylogenetic tree. Since a homogenous model of evolution is unlikely to be realistic in nature, we explored the robustness of the phylogenetic regression when this assumption is violated. We did so by simulating a set of traits under various heterogeneous models of evolution, and evaluating the statistical performance (type I error [the percentage of tests based on samples that incorrectly rejected a true null hypothesis] and power [the percentage of tests that correctly rejected a false null hypothesis]) of classical phylogenetic regression. We found that PGLS has good power but unacceptable type I error rates. This finding is important since this method has been increasingly used in comparative analyses over the last decade. To address this issue, we propose a simple solution based on transforming the underlying variance-covariance matrix to adjust for model heterogeneity within PGLS. We suggest that heterogeneous rates of evolution might be particularly prevalent in large phylogenetic trees, while most current approaches assume a homogenous rate of evolution. Our analysis demonstrates that overlooking rate heterogeneity can result in inflated type I errors, thus misleading comparative analyses. We show that it is possible to correct for this bias even when the underlying model of evolution is not known a priori. [ABSTRACT FROM AUTHOR]

Climate and land cover changes are important drivers of the plant species distributions and diversity patterns in mountainous regions. Although the need for a multifaceted view of diversity based on taxonomic, functional and phylogenetic dimensions is now commonly recognized, there are no complete risk assessments concerning their expected changes. In this paper, we used a range of species distribution models in an ensemble-forecasting framework together with regional climate and land cover projections by 2080 to analyze the potential threat for more than 2500 plant species at high resolution (2.5 × 2.5 km) in the French Alps. We also decomposed taxonomic, functional and phylogenetic diversity facets into α and β components and analyzed their expected changes by 2080. Overall, plant species threats from climate and land cover changes in the French Alps were expected to vary depending on the species' preferred altitudinal vegetation zone, rarity, and conservation status. Indeed, rare species and species of conservation concern were the ones projected to experience less severe change, and also the ones being the most efficiently preserved by the current network of protected areas. Conversely, the three facets of plant diversity were also projected to experience drastic spatial re-shuffling by 2080. In general, the mean α-diversity of the three facets was projected to increase to the detriment of regional β-diversity, although the latter was projected to remain high at the montane-alpine transition zones. Our results show that, due to a high-altitude distribution, the current protection network is efficient for rare species, and species predicted to migrate upward. Although our modeling framework may not capture all possible mechanisms of species range shifts, our work illustrates that a comprehensive risk assessment on an entire floristic region combined with functional and phylogenetic information can help delimitate future scenarios of biodiversity and better design its protection. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA) are the two main histological subtypes of primary liver cancer. Estimates of the burden of liver cancer by subtype are needed to facilitate development and evaluation of liver cancer control globally. We provide worldwide, regional and national estimates of HCC and iCCA incidence using high-quality data. We used population-based cancer registry data on liver cancer cases by histological subtype from 95 countries to compute the sex- and country-specific distributions of HCC, iCCA and other specified histology. Subtype distributions were applied to estimates of total liver cancer cases for 2018 from the Global Cancer Observatory. Age-standardised incidence rates (ASRs) were calculated. There were an estimated 826,000 cases of liver cancer globally in 2018: 661,000 HCC (ASR 7.3 cases per 100,000); 123,000 iCCA (ASR 1.4) and 42,000 other specified histology (ASR 0.5). HCC contributed 80% of the world total liver cancer burden followed by iCCA (14.9%) and other specified histology (5.1%). HCC rates were highest in Eastern Asia (ASR 14.8), Northern Africa (ASR 13.2) and South-Eastern Asia (ASR 9.5). Rates of iCCA were highest in South-Eastern Asia (ASR 2.9), Eastern Asia (ASR 2.0), Northern Europe, the Caribbean and Central America and Oceania (ASR all 1.8). We have shown the importance of uncovering the distinct patterns of the major subtypes of liver cancer. The use of these estimates is critical to further develop public health policy to reduce the burden of liver cancer and monitor progress in controlling HCC and iCCA globally. • Liver cancer is the third cause of cancer death worldwide and has two major subtypes. • Cancer registry data were used to estimate regional liver cancer subtype distribution. • Hepatocellular carcinoma contributed 80% of all liver cancer cases globally. • Intrahepatic cholangiocarcinoma contributed 15% of all liver cancer cases globally. • Considering histological subtypes is essential to assess global liver cancer burden. [ABSTRACT FROM AUTHOR]

Background: Worldwide, halting biodiversity loss is still a major challenge. Climate and land-use change (CLUC) are major drivers of species decline, and further expected to drive species' future ranges. Understanding how these changes may impact species in the future is thus of utmost importance in the context of conservation and monitoring. This is especially critical for species of conservation concern, known to be more prone to extinction under environmental change. Aims: Here we addressed how CLUC may affect future distributions of 64 plant species designated under conservation legislation for Portugal and Spain. Current and future species distributions were modelled and projected under three CLUC scenarios. Range changes were analysed for each species and IUCN category, considering climate versus land-use change models, and the trade-offs between them. Results: Overall, our results depict consistent trends in the distribution of the targeted species under CLUC. The results also highlight potential extinction for some of the targeted species under climate change. However, under land-use change, 10 species are likely to expand their suitable habitat. Conclusions: Our research advances existing knowledge on how climate and land-use change may impact species of conservation concern in the Iberian Peninsula. Such knowledge is essential if further losses of species of conservation concern are to be proactively anticipated. Ultimately, such information can be useful to support data-driven conservation programmes and decision-making in the future. [ABSTRACT FROM AUTHOR]

Across the globe, invasive alien species cause severe environmental changes, altering species composition and ecosystem functions. So far, mountain areas have mostly been spared from large-scale invasions. However, climate change, land-use abandonment, the development of tourism and the increasing ornamental trade will weaken the barriers to invasions in these systems. Understanding how alien species will react and how native communities will influence their success is thus of prime importance in a management perspective. Here, we used a spatially and temporally explicit simulation model to forecast invasion risks in a protected mountain area in the French Alps under future conditions. We combined scenarios of climate change, land-use abandonment and tourism-linked increases in propagule pressure to test if the spread of alien species in the region will increase in the future. We modelled already naturalized alien species and new ornamental plants, accounting for interactions among global change components, and also competition with the native vegetation. Our results show that propagule pressure and climate change will interact to increase overall species richness of both naturalized aliens and new ornamentals, as well as their upper elevational limits and regional range-sizes. Under climate change, woody aliens are predicted to more than double in range-size and herbaceous species to occupy up to 20% of the park area. In contrast, land-use abandonment will open new invasion opportunities for woody aliens, but decrease invasion probability for naturalized and ornamental alien herbs as a consequence of colonization by native trees. This emphasizes the importance of interactions with the native vegetation either for facilitating or potentially for curbing invasions. Overall, our work highlights an additional and previously underestimated threat for the fragile mountain flora of the Alps already facing climate changes, land-use transformations and overexploitation by tourism. [ABSTRACT FROM AUTHOR]

In a world facing rapid environmental changes, anticipating their impacts on biodiversity is of utmost relevance. Remotely-sensed Ecosystem Functional Attributes (EFAs) are promising predictors for Species Distribution Models (SDMs) by offering an early and integrative response of vegetation performance to environmental drivers. Species of high conservation concern would benefit the most from a better ability to anticipate changes in habitat suitability. Here we illustrate how yearly projections from SDMs based on EFAs could reveal short-term changes in potential habitat suitability, anticipating mid-term shifts predicted by climate-change-scenario models. We fitted two sets of SDMs for 41 plant species of conservation concern in the Iberian Peninsula: one calibrated with climate variables for baseline conditions and projected under two climate-change-scenarios (future conditions); and the other calibrated with EFAs for 2001 and projected annually from 2001 to 2013. Range shifts predicted by climate-based models for future conditions were compared to the 2001–2013 trends from EFAs-based models. Projections of EFAs-based models estimated changes (mostly contractions) in habitat suitability that anticipated, for the majority (up to 64%) of species, the mid-term shifts projected by traditional climate-change-scenario forecasting, and showed greater agreement with the business-as-usual scenario than with the sustainable-development one. This study shows how satellite-derived EFAs can be used as meaningful essential biodiversity variables in SDMs to provide early-warnings of range shifts and predictions of short-term fluctuations in suitable conditions for multiple species. [ABSTRACT FROM AUTHOR]

Climate and land-use change are expected to substantially alter future plant species distributions leading to higher extinction rates. However, little is known about how plant species ranges, richness and phylogenetic diversity of continents will be affected by these dynamics., We address this gap here by examining the patterns of species' distributions and phylogenetic relationships for 7465 seed plant taxa in North America. An ensemble of species distribution models was used to estimate the potential suitable habitat of species under different sets of climate, land-use and dispersal constraint scenarios. We then evaluated the vulnerability and extinction risk of individual species to changes in climate and land use, and examined whether rare, endangered and evolutionarily distinct species were disproportionally threatened by climate and land-use change., We show that ~2000 species may lose >80% of their suitable habitats under the A1b emission scenario for the 2080s, while ~100 species may experience >80% range expansions (a 20 : 1 ratio of loss to gain). When considering >50% range retraction and expansion, the ratio of loss to gain was 13 : 1. A greater loss of species diversity is expected at low latitudes, while larger gains are expected at high latitudes. Evolutionarily distinct species are predicted to have significantly higher extinction risks than extant species. This suggests a disproportionate future loss of phylogenetic diversity for the North American flora., Synthesis and applications. Our study provides continental-scale evidence of plant species extinction risk caused by future climate and land-use change, and highlights the importance of integrating phylogenetic measures into conservation risk assessments. This work provides insight into the status, trends and threats for a large share of North America's plant species by identifying risks and prioritizing conservation in a rapidly changing world. [ABSTRACT FROM AUTHOR]

Hutchinson defined species' realized niche as the set of environmental conditions in which populations can persist in the presence of competitors. In terms of demography, the realized niche corresponds to the environments where the intrinsic growth rate ( r) of populations is positive. Observed species occurrences should reflect the realized niche when additional processes like dispersal and local extinction lags do not have overwhelming effects. Despite the foundational nature of these ideas, quantitative assessments of the relationship between range-wide demographic performance and occurrence probability have not been made. This assessment is needed both to improve our conceptual understanding of species' niches and ranges and to develop reliable mechanistic models of species geographic distributions that incorporate demography and species interactions. The objective of this study is to analyse how demographic parameters (intrinsic growth rate r and carrying capacity K ) and population density ( N ) relate to occurrence probability ( Pocc ). We hypothesized that these relationships vary with species' competitive ability. Demographic parameters, density, and occurrence probability were estimated for 108 tree species from four temperate forest inventory surveys (Québec, western USA, France and Switzerland). We used published information of shade tolerance as indicators of light competition strategy, assuming that high tolerance denotes high competitive capacity in stable forest environments. Interestingly, relationships between demographic parameters and occurrence probability did not vary substantially across degrees of shade tolerance and regions. Although they were influenced by the uncertainty in the estimation of the demographic parameters, we found that r was generally negatively correlated with Pocc, while N, and for most regions K, was generally positively correlated with Pocc. Thus, in temperate forest trees the regions of highest occurrence probability are those with high densities but slow intrinsic population growth rates. The uncertain relationships between demography and occurrence probability suggests caution when linking species distribution and demographic models. [ABSTRACT FROM AUTHOR]

Aim Conservation planning exercises increasingly rely on species distributions predicted either from one particular statistical model or, more recently, from an ensemble of models (i.e. ensemble forecasting). However, it has not yet been explored how different ways of summarizing ensemble predictions affect conservation planning outcomes. We evaluate these effects and compare commonplace consensus methods, applied before the conservation prioritization phase, to a novel method that applies consensus after reserve selection. Location Europe. Methods We used an ensemble of predicted distributions of 146 Western Palaearctic bird species in alternative ways: four different consensus methods, as well as distributions discounted with variability, were used to produce inputs for spatial conservation prioritization. In addition, we developed and tested a novel method, in which we built 100 datasets by sampling the ensemble of predicted distributions, ran a conservation prioritization analysis on each of them and averaged the resulting priority ranks. We evaluated the conservation outcome against three controls: (i) a null control, based on random ranking of cells; (2) the reference solution, based on an expert-refined dataset; and (3) the independent solution, based on an independent dataset. Results Networks based on predicted distributions were more representative of rare species than randomly selected networks. Alternative methods to summarize ensemble predictions differed in representativeness of resulting reserve networks. Our novel method resulted in better representation of rare species than pre-selection consensus methods. Main conclusions Retaining information about the variation in the predicted distributions throughout the conservation prioritization seems to provide better results than summarizing the predictions before conservation prioritization. Our results highlight the need to understand and consider model-based uncertainty when using predicted distribution data in conservation prioritization. [ABSTRACT FROM AUTHOR]