A strategy for the next decade to address data deficiency in neglected biodiversity

Measuring progress toward international biodiversity targets requires robust information on the conservation status of species, which the International Union for Conservation of Nature (IUCN) Red List of Threatened Species provides. However, data and capacity are lacking for most hyperdiverse groups, such as invertebrates, plants, and fungi, particularly in megadiverse or high-endemism regions. Conservation policies and biodiversity strategies aimed at halting biodiversity loss by 2020 need to be adapted to tackle these information shortfalls after 2020. We devised an 8-point strategy to close existing data gaps by reviving explorative field research on the distribution, abundance, and ecology of species; linking taxonomic research more closely with conservation; improving global biodiversity databases by making the submission of spatially explicit data mandatory for scientific publications; developing a global spatial database on threats to biodiversity to facilitate IUCN Red List assessments; automating preassessments by integrating distribution data and spatial threat data; building capacity in taxonomy, ecology, and biodiversity monitoring in countries with high species richness or endemism; creating species monitoring programs for lesser-known taxa; and developing sufficient funding mechanisms to reduce reliance on voluntary efforts. Implementing these strategies in the post-2020 biodiversity framework will help to overcome the lack of capacity and data regarding the conservation status of biodiversity. This will require a collaborative effort among scientists, policy makers, and conservation practitioners.     

Saving power to conserve your reputation? The effectiveness of private versus public information

Environmental damage is often an unseen byproduct of other activities. Disclosing environmental impact privately to consumers can reduce the costs and/or increase the moral benefits of conservation behaviors, while publicly disclosing such information can provide an additional motivation for conservation - cultivating a green reputation. In a unique field experiment in the residence halls at the University of California – Los Angeles, we test the efficacy of detailed private and public information on electricity conservation. Private information was given through real-time appliance level feedback and social norms over usage, and public information was given through a publicly visible conservation rating. Our analysis is based on 7,120 daily observations about energy use from heating and cooling, lights and plug load for 66 rooms collected over an academic year. Our results suggest that while private information alone was ineffective, public information combined with private information motivated a 20 percent reduction in electricity consumption achieved through lower use of heating and cooling. Public information was particularly effective for above median energy users.     

Monitoring and reporting attacks on education in the Democratic Republic of the Congo and Somalia

The United Nations' Monitoring and Reporting Mechanism is charged with documenting six grave violations against children in a time of conflict, including attacks on schools. Many of these incidents, however, remain unreported across the globe. This study explores whether or not a local knowledge base of education and child protection actors in North and South Kivu Provinces, Democratic Republic of the Congo, and in Mogadishu, Somalia, could contribute to a more complete record of attacks on education in those areas. Hundreds of semi‐structured interviews were conducted with key informants across the three settings, and in total 432 attacks on education were documented. Purposive samples of these reports were verified and a large majority was confirmed. Local non‐governmental organisations and education institutions were most knowledgeable about these incidents, but most never reported them to a monitoring authority. The study concludes that attack surveillance and response were largely insufficient, and recommends investing in mechanisms that utilise local knowledge to address these shortcomings.     

Driver Workload Response to In-Vehicle Device Operations

A central concern of Intelligent Transportation Systems (ITS) is the effect of in-vehicle devices (e.g., cell phones, navigation systems, radios, etc.) on driver performance and safety. As diverse and innovative technologies are designed and implemented for in-vehicle use, questions regarding the presence and use of these devices assume progressively greater importance. Further concerns for advanced driver training require us to develop and validate reliable and effective procedures for assessing such effects. This work examines a number of candidate procedures, in particular the evaluation of change in cognitive workload as a strategy by which such goals might be achieved.     

Spatial distribution of enhanced atrazine degradation across northeastern Colorado cropping systems

Reports of enhanced atrazine degradation and reduced residual weed control have increased in recent years, sparking interest in identifying factors contributing to enhanced atrazine degradation. The objectives of this study were to (i) assess the spatial distribution of enhanced atrazine degradation in 45 commercial farm fields in northeastern Colorado (Kit Carson, Larimer, Logan, Morgan, Phillips, and Yuma counties) where selected cultural management practices and soil bio-chemo-physical properties were quantified; (ii) utilize Classification and Regression Tree (CART) Analysis to identify cultural management practices and (or) soil bio-chemophysical attributes that are associated with enhanced atrazine degradation; and (iii) translate our CART Analysis into a model that predicts relative atrazine degradation rate (rapid, moderate, or slow) as a function of known management practices and (or) soil properties. Enhanced atrazine degradation was widespread within a 300-km radius across northeastern Colorado, with approximately 44% of the fields demonstrating rapid atrazine degradation activity (laboratory-based dissipation time halflife [DT50] < 3 d). The most rapid degradation rates occurred in fields that received the most frequent atrazine applications. Classification and Regression Tree Analysis resulted in a prediction model that correctly classified soils with rapid atrazine DT50 80% of the time and soils with slow degradation (DT50 > 8 d) 62.5% of the time. Significant factors were recent atrazine use history, soil pH, and organic matter content. The presence/absence of atzC polymerase chain reaction (PCR) product was not a significant predictor variable for atrazine DT50. In conclusion, enhanced atrazine degradation is widespread in northeastern Colorado. If producers know their atrazine use history, soil pH, and OM content, they should be able to identify fields exhibiting enhanced atrazine degradation using our CART Model.     

Large-sample-size assessment of socioeconomic predictors of community-level resource management occurrence

Community-level resource management efforts are cornerstones in ensuring sustainable use of natural resources. Yet, understanding how community characteristics influence management practices remains contested. With a sample size of ≥725 communities, we assessed the effects of key community (i.e., socioeconomic) characteristics (human population size and density, market integration, and modernization) on the probability of occurrence of fisheries management practices, including gear, species, and spatial restrictions. The study was based in Solomon Islands, a Pacific Island country with a population that is highly dependent on coastal fisheries. People primarily dwell in small communities adjacent to the coastline dispersed across 6 island provinces and numerous smaller islands. We used nationally collected data in binomial logistic regression models to examine the likelihood of management occurrence, given socioeconomic context of communities. In contrast to prevailing views, we identified a positive and statistically significant association between both human population size and market integration and all 3 management practices. Human population density, however, had a statistically significant negative association and modernization a varied and limited association with occurrence of all management practices. Our method offers a way to remotely predict the occurrence of resource management practices based on key socioeconomic characteristics. It could be used to improve understanding of why some communities conduct natural resource management activities when statistical patterns suggest they are not likely to and thus improve understanding of how some communities of people beat the odds despite limited market access and high population density.     

A stochastic model for estimating sustainable limits to wildlife mortality in a changing world

Human-caused mortality of wildlife is a pervasive threat to biodiversity. Assessing the population-level impact of fisheries bycatch and other human-caused mortality of wildlife has typically relied upon deterministic methods. However, population declines are often accelerated by stochastic factors that are not accounted for in such conventional methods. Building on the widely applied potential biological removal (PBR) equation, we devised a new population modeling approach for estimating sustainable limits to human-caused mortality and applied it in a case study of bottlenose dolphins affected by capture in an Australian demersal otter trawl fishery. Our approach, termed sustainable anthropogenic mortality in stochastic environments (SAMSE), incorporates environmental and demographic stochasticity, including the dependency of offspring on their mothers. The SAMSE limit is the maximum number of individuals that can be removed without causing negative stochastic population growth. We calculated a PBR of 16.2 dolphins per year based on the best abundance estimate available. In contrast, the SAMSE model indicated that only 2.3–8.0 dolphins could be removed annually without causing a population decline in a stochastic environment. These results suggest that reported bycatch rates are unsustainable in the long term, unless reproductive rates are consistently higher than average. The difference between the deterministic PBR calculation and the SAMSE limits showed that deterministic approaches may underestimate the true impact of human-caused mortality of wildlife. This highlights the importance of integrating stochasticity when evaluating the impact of bycatch or other human-caused mortality on wildlife, such as hunting, lethal control measures, and wind turbine collisions. Although population viability analysis (PVA) has been used to evaluate the impact of human-caused mortality, SAMSE represents a novel PVA framework that incorporates stochasticity for estimating acceptable levels of human-caused mortality. It offers a broadly applicable, stochastic addition to the demographic toolbox to evaluate the impact of human-caused mortality on wildlife.     

Postfire response of flood-regenerating riparian vegetation in a semi-arid landscape

Piles of large wood (LW) deposited by major floods in river corridors can interact with naturally occurring wildfires from uplands to impact the regeneration of riparian vegetation. This study examines the spatial and short-term temporal response of riparian vegetation and soil nutrients to fire along the Sabie River, South Africa, with special emphasis on the effects of burned LW piles. At the study site there were 112 species of plants recorded with 28% of species restricted to the burned plots. As expected, vegetation cover was significantly lower in burned plots as compared with the unburned plots 12 months postfire. There was a significant influence of LW on species richness with fewer species recorded in the LW plots. For both fire and LW treatments, plant cover showed a significant change over three years. After an initial increase from 12 to 24 months (postfire) there was a decline in plant cover after 36 months. Species community composition was distinctly different between burned and unburned plots 12 months postfire, and the presence of LW affected species composition for burned plots but not for unburned ones. Time series ordination of LW plots highlighted the changes in species composition over the three years of sampling. Of trees with accumulations of LW within 5 m of their base, 48% had been killed by fire as compared to only 4% with no LW accumulations in close proximity. Soil-available P was significantly higher in the burned plots and even higher with burned LW while there were no effects on soil total N. There was also a significant positive trend between available P in soils and plant vegetation cover. Soil-exchangeable K was also significantly higher and total C significantly lower in the burned and LW plots. Burned plots also had significantly higher soil electrical conductivity (EC) and soil pH. The patchy nature of the studied fire, whose complexity is exacerbated by the distribution of flood deposited LW, acted to create a mosaic of alternate successional states as the riparian community recovers from flooding and the subsequent fire. We suspect that the resultant heterogeneity will increase ecosystem resilience by providing flexibility in the form of more options for a system response to subsequent disturbances.     

The inertial range “outer scale” and optical turbulence

The crucial parameter used to calculate turbulence effects upon light waves propagating through the atmosphere is known as the structure constant, . As Tatarski has shown, this parameter depends upon the “outer scale” of the inertial sub-range of the turbulence. Recently there have been successful predictions of astronomical “seeing” conditions at Mauna Kea Astronomical Observatory which have increased interest in this subject and in the use of the so-called “Dewan Optical Turbulence Model”. In the case of the Air Force, there has been a longstanding need for such optical turbulence prediction, especially in the stratosphere. In the past researchers have used a relation due to Tatarski, (which plays a prominent role in this model) in order to deduce values of the “outer scale” from measurements. When doing this, they have been surprised to find values very much smaller than expected. The goal of the paper is to explain this unexpected result. As we will show, this result can be explained by two factors: (a) the average turbulent layer thicknesses are smaller than originally believed, and, more importantly, (b) only a minor fraction of the stratosphere is turbulent. In order to arrive at this conclusion, we used the high-resolution (10 m) wind profiles that were originally used to formulate the previously mentioned optical turbulence model. The U.S. Government’s right to retain a non-exclusive, royalty-free license in and to any copyright is acknowledged.