Thresholds for adding degraded tropical forest to the conservation estate

Logged and disturbed forests are often viewed as degraded and depauperate environments compared with primary forest. However, they are dynamic ecosystems1 that provide refugia for large amounts of biodiversity2,3, so we cannot afford to underestimate their conservation value4. Here we present empirically defined thresholds for categorizing the conservation value of logged forests, using one of the most comprehensive assessments of taxon responses to habitat degradation in any tropical forest environment. We analysed the impact of logging intensity on the individual occurrence patterns of 1,681 taxa belonging to 86 taxonomic orders and 126 functional groups in Sabah, Malaysia. Our results demonstrate the existence of two conservation-relevant thresholds. First, lightly logged forests (68%) of their biomass removed, and these are likely to require more expensive measures to recover their biodiversity value. Overall, our data confirm that primary forests are irreplaceable5, but they also reinforce the message that logged forests retain considerable conservation value that should not be overlooked

Sparring dynamics and individual laterality in male South African giraffes

Abstract: Sparring by male giraffes has been commonly reported since its first description in 1958 and is believed to play a role in establishing male dominance hierarchies. However, despite being often documented, quantitative investigations of sparring behaviour are currently lacking. Here, we investigate the factors affecting the frequency, duration and intensity of sparring bouts in a population of giraffes Giraffa camelopardalis giraffa living on a private fenced reserve in Limpopo, South Africa. We show that sparring bouts were most frequently observed in young adults, and between males that were more evenly matched in size. Sparring bouts between males of similar body size were also characterised by being of high intensity and of short duration. Taken together, these results support the suggestion that sparring functions principally to provide maturing males a means of testing their competitive ability without escalating to full‐scale fights. Additionally, mature bulls intervened on young adults possibly to disable any winner effect achieved by the latter, with the most dominant bull being responsible for the majority of interventions. For the first time, we also show that individuals displayed strong laterality when engaged in sparring: individuals consistently preferred delivering blows from either their left or right side, and these preferences dictated the orientation of sparring bouts (whether head‐to‐head or head‐to‐tail). Lastly, we show that sparring displayed a seasonal peak which coincided with the onset of the wet season and possibly reflected the increased aggregation of males at this time. A more nuanced understanding of how social and environmental factors shape interactions among individuals, such as sparring, will improve our understanding and management of this charismatic animal

Sparring dynamics and individual laterality in male South African giraffes

Sparring by male giraffes has been commonly reported since its first description in 1958 and is believed to play a role in establishing male dominance hierarchies. However, despite being often documented, quantitative investigations of sparring behaviour are currently lacking. Here, we investigate the factors affecting the frequency, duration and intensity of sparring bouts in a population of giraffes Giraffa camelopardalis giraffa living on a private fenced reserve in Limpopo, South Africa. We show that sparring bouts were most frequently observed in young adults, and between males that were more evenly matched in size. Sparring bouts between males of similar body size were also characterised by being of high intensity and of short duration. Taken together, these results support the suggestion that sparring functions principally to provide maturing males a means of testing their competitive ability without escalating to full-scale fights. Additionally, mature bulls intervened on young adults possibly to disable any winner effect achieved by the latter, with the most dominant bull being responsible for the majority of interventions. For the first time, we also show that individuals displayed strong laterality when engaged in sparring: individuals consistently preferred delivering blows from either their left or right side, and these preferences dictated the orientation of sparring bouts (whether head-to-head or head-to-tail). Lastly, we show that sparring displayed a seasonal peak which coincided with the onset of the wet season and possibly reflected the increased aggregation of males at this time. A more nuanced understanding of how social and environmental factors shape interactions among individuals, such as sparring, will improve our understanding and management of this charismatic animal

Estimating animal density for a community of species using information obtained only from camera-traps

1. Animal density is a fundamental parameter in ecology and conservation, and yet has remained difficult to measure. For terrestrial mammals and birds, camera-traps have dramatically improved our ability to collect systematic data across a large number of species, but density estimation (except for species with natural marks) is still faced with statistical and logistical hurdles, including the requirement for auxiliary data, large sample sizes, and an inability to incorporate covariates. 2. To fill this gap in the camera-trapper’s statistical toolbox, we extended the existing Random Encounter Model (REM) to the multi-species case in a Bayesian framework. This multi-species REM can incorporate covariates and provides parameter estimates for even the rarest species. As input to the model, we used information directly available in the camera-trap data. The model outputs posterior distributions for the REM parameters – movement speed, activity level, the effective angle and radius of the camera-trap detection zone, and density – for each species. We applied this model to an existing dataset for 35 species in Borneo, collected across old-growth and logged forest. Here, we added animal position data derived from the image sequences in order to estimate the speed and detection zone parameters. 3. The model revealed a decrease in movement speeds, and therefore day-range, across the species community in logged compared to old-growth forest, whilst activity levels showed no consistent trend. Detection zones were shorter, but of similar width, in logged compared to old-growth forest. Overall, animal density was lower in logged forest, even though most species individually occurred at higher density in logged forest. However, the biomass per unit area was substantially higher in logged compared to old-growth forest, particularly among herbivores and omnivores, likely because of increased resource availability at ground level. We also included body mass as a variable in the model, revealing that larger-bodied species were more active, had more variable speeds, and had larger detection zones. 4. Caution is warranted when estimating density for semi-arboreal and fossorial species using camera-traps, and more extensive testing of assumptions is recommended. Nonetheless, we anticipate that multi-species density estimation could have very broad application

High resolution age-structured mapping of childhood vaccination coverage in low and middle income countries

BackgroundThe expansion of childhood vaccination programs in low and middle income countries has been a substantial public health success story. Indicators of the performance of intervention programmes such as coverage levels and numbers covered are typically measured through national statistics or at the scale of large regions due to survey design, administrative convenience or operational limitations. These mask heterogeneities and ‘coldspots’ of low coverage that may allow diseases to persist, even if overall coverage is high. Hence, to decrease inequities and accelerate progress towards disease elimination goals, fine-scale variation in coverage should be better characterized.MethodsUsing measles as an example, cluster-level Demographic and Health Surveys (DHS) data were used to map vaccination coverage at 1 km spatial resolution in Cambodia, Mozambique and Nigeria for varying age-group categories of children under five years, using Bayesian geostatistical techniques built on a suite of publicly available geospatial covariates and implemented via Markov Chain Monte Carlo (MCMC) methods.ResultsMeasles vaccination coverage was found to be strongly predicted by just 4–5 covariates in geostatistical models, with remoteness consistently selected as a key variable. The output 1 × 1 km maps revealed significant heterogeneities within the three countries that were not captured using province-level summaries. Integration with population data showed that at the time of the surveys, few districts attained the 80% coverage, that is one component of the WHO Global Vaccine Action Plan 2020 targets.ConclusionThe elimination of vaccine-preventable diseases requires a strong evidence base to guide strategies and inform efficient use of limited resources. The approaches outlined here provide a route to moving beyond large area summaries of vaccination coverage that mask epidemiologically-important heterogeneities to detailed maps that capture subnational vulnerabilities. The output datasets are built on open data and methods, and in flexible format that can be aggregated to more operationally-relevant administrative unit levels

A spatial regression model for the disaggregation of areal unit based data to high-resolution grids with application to vaccination coverage mapping

© The Author(s) 2018. The growing demand for spatially detailed data to advance the Sustainable Development Goals agenda of ‘leaving no one behind’ has resulted in a shift in focus from aggregate national and province-based metrics to small areas and high-resolution grids in the health and development arena. Vaccination coverage is customarily measured through aggregate-level statistics, which mask fine-scale heterogeneities and ‘coldspots’ of low coverage. This paper develops a methodology for high-resolution mapping of vaccination coverage using areal data in settings where point-referenced survey data are inaccessible. The proposed methodology is a binomial spatial regression model with a logit link and a combination of covariate data and random effects modelling two levels of spatial autocorrelation in the linear predictor. The principal aspect of the model is the melding of the misaligned areal data and the prediction grid points using the regression component and each of the conditional autoregressive and the Gaussian spatial process random effects. The Bayesian model is fitted using the INLA-SPDE approach. We demonstrate the predictive ability of the model using simulated data sets. The results obtained indicate a good predictive performance by the model, with correlations of between 0.66 and 0.98 obtained at the grid level between true and predicted values. The methodology is applied to predicting the coverage of measles and diphtheria-tetanus-pertussis vaccinations at 5 × 5 km 2 in Afghanistan and Pakistan using subnational Demographic and Health Surveys data. The predicted maps are used to highlight vaccination coldspots and assess progress towards coverage targets to facilitate the implementation of more geographically precise interventions. The proposed methodology can be readily applied to wider disaggregation problems in related contexts, including mapping other health and development indicators

Estimating animal density for a community of species using information obtained only from camera‐traps

1. Animal density is a fundamental parameter in ecology and conservation, and yet it has remained difficult to measure. For terrestrial mammals and birds, camera-traps have dramatically improved our ability to collect systematic data across a large number of species, but density estimation (except for species with natural marks) is still faced with statistical and logistical hurdles, including the requirement for auxiliary data and large sample sizes, and an inability to incorporate covariates. 2. To fill this gap in the camera-trapper's statistical toolbox, we extended the ex-isting Random Encounter Model (REM) to the multi-species case in a Bayesian framework. This multi-species REM can incorporate covariates and provides pa-rameter estimates for even the rarest species. As input to the model, we used information directly available in the camera-trap data. The model outputs poste-rior distributions for the REM parameters—movement speed, activity level, the effective angle and radius of the camera-trap detection zone, and density—for each species. We applied this model to an existing dataset for 35 species in Borneo, collected across old- growth and logged forest. Here, we added animal position data derived from the image sequences in order to estimate the speed and detection zone parameters. 3. The model revealed a decrease in movement speeds, and therefore day- range, across the species community in logged compared to old- growth forest, whilst activity levels showed no consistent trend. Detection zones were shorter, but of similar width, in logged compared to old- growth forest. Overall, animal density was lower in logged forest, even though most species individually occurred at higher density in logged forest. However, the biomass per unit area was sub-stantially higher in logged compared to old- growth forest, particularly among herbivores and omnivores, likely because of increased resource availability at ground level. We also included body mass as a variable in the model, revealing that larger- bodied species were more active, had more variable speeds, and had larger detection zones

Mapping vaccination coverage to explore the effects of delivery mechanisms and inform vaccination strategies

The success of vaccination programs depends largely on the mechanisms used in vaccine delivery. National immunization programs offer childhood vaccines through fixed and outreach services within the health system and often, additional supplementary immunization activities (SIAs) are undertaken to fill gaps and boost coverage. Here, we map predicted coverage at 1 × 1 km spatial resolution in five low- and middle-income countries to identify areas that are under-vaccinated via each delivery method using Demographic and Health Surveys data. We compare estimates of the coverage of the third dose of diphtheria-tetanus-pertussis-containing vaccine (DTP3), which is typically delivered through routine immunization (RI), with those of measles-containing vaccine (MCV) for which SIAs are also undertaken. We find that SIAs have boosted MCV coverage in some places, but not in others, particularly where RI had been deficient, as depicted by DTP coverage. The modelling approaches outlined here can help to guide geographical prioritization and strategy design.</p

Causes of Noncompliance with International Law: A Field Experiment on Anonymous Incorporation

20110302 into the Experiments on Governance and Politics Registry once that registry was begun at e-gap.org. Of those interventions registered, we report on the FATF, Premium, Corruption, and Terrorism conditions in this article. All other interventions outlined in the registered document are reported in other work. In our registration, we indicated that we would report results dichotomously as compliant or noncompliant, given a response. We still report response and nonresponse followed by a compliance level, but we expanded the set of possible types of compliance (nonresponse, noncompliance, partial compliance, compliance, and refusal). Presenting the information this way is more precise and is also consistent with the registry document because the fuller set of outcomes contains all information the dichotomized measures capture (se