Limitations of recreational camera traps for wildlife management and conservation research: A practitioner’s perspective

The availability of affordable ‘recreational’ camera traps has dramatically increased over the last decade. We present survey results which show that many conservation practitioners use cheaper ‘recreational’ units for research rather than more expensive ‘professional’ equipment. We present our perspective of using two popular models of ‘recreational’ camera trap for ecological field-based studies. The models used (for >2 years) presented us with a range of practical problems at all stages of their use including deployment, operation, and data management, which collectively crippled data collection and limited opportunities for quantification of key issues arising. Our experiences demonstrate that prospective users need to have a sufficient understanding of the limitations camera trap technology poses, dimensions we communicate here. While the merits of different camera traps will be study specific, the performance of more expensive ‘professional’ models may prove more cost-effective in the long-term when using camera traps for research.     

Patterns of catch and trophic signatures illustrate diverse management requirements of coastal fisheries in Solomon Islands

Coastal fisheries are a critical component of Pacific island food systems; they power village economies and provide nutritious aquatic foods. Many coastal women and men actively fishing in this region rely on multi-species fisheries, which given their extraordinary diversity are notoriously difficult to both characterize, and to manage. Understanding patterns of fishing, diversity of target species and drivers of these patterns can help define requirements for sustainable management and enhanced livelihoods. Here we use a 12-month data set of 8535 fishing trips undertaken by fishers across Malaita province, Solomon Islands, to create fisheries signatures for 13 communities based on the combination of two metrics; catch per unit effort (CPUE) and catch trophic levels. These signatures are in turn used as a framework for guiding suitable management recommendations in the context of community-based resource management. While a key proximate driver of these patterns was fishing gear (e.g. angling, nets or spearguns), market surveys and qualitative environmental information suggest that community fishing characteristics are coupled to local environmental features more than the market value of specific species they target. Our results demonstrate that even within a single island not all small-scale fisheries are equal, and effective management solutions ultimately depend on catering to the specific environmental characteristics around individual communities.Supplementary InformationThe online version contains supplementary material available at 10.1007/s13280-021-01690-z.     

Mapping ground water vulnerability to pesticide leaching with a process-based metamodel of EuroPEARL

To support EU policy, indicators of pesticide leaching at the European level are required. For this reason, a metamodel of the spatially distributed European pesticide leaching model EuroPEARL was developed. EuroPEARL considers transient flow and solute transport and assumes Freundlich adsorption, first-order degradation and passive plant uptake of pesticides. Physical parameters are depth dependent while (bio)-chemical parameters are depth, temperature, and moisture dependent. The metamodel is based on an analytical expression that describes the mass fraction of pesticide leached. The metamodel ignores vertical parameter variations and assumes steady flow. The calibration dataset was generated with EuroPEARL and consisted of approximately 60,000 simulations done for 56 pesticides with different half-lives and partitioning coefficients. The target variable was the 80th percentile of the annual average leaching concentration at 1-m depth from a time series of 20 yr. The metamodel explains over 90% of the variation of the original model with only four independent spatial attributes. These parameters are available in European soil and climate databases, so that the calibrated metamodel could be applied to generate maps of the predicted leaching concentration in the European Union. Maps generated with the metamodel showed a good similarity with the maps obtained with EuroPEARL, which was confirmed by means of quantitative performance indicators.     

Optimization of capture–recapture monitoring of elusive species illustrated with a threatened grasshopper

Information on population sizes and trends of threatened species is essential for their conservation, but obtaining reliable estimates can be challenging. We devised a method to improve the precision of estimates of population size obtained from capture–recapture studies for species with low capture and recapture probabilities and short seasonal activity, illustrated with population data of an elusive grasshopper (Prionotropis rhodanica). We used data from 5 capture–recapture studies to identify methodological and environmental factors affecting capture and recapture probabilities and estimates of population size. In a simulation, we used the population size and capture and recapture probability estimates obtained from the field studies to identify the minimum number of sampling occasions needed to obtain unbiased and robust estimates of population size. Based on these results we optimized the capture–recapture design, implemented it in 2 additional studies, and compared their precision with those of the nonoptimized studies. Additionally, we simulated scenarios based on thresholds of population size in criteria C and D of the International Union for Conservation of Nature (IUCN) Red List to investigate whether estimates of population size for elusive species can reliably inform red-list assessments. Identifying parameters that affect capture and recapture probabilities (for the grasshopper time since emergence of first adults) and optimizing field protocols based on this information reduced study effort (−6% to −27% sampling occasions) and provided more precise estimates of population size (reduced coefficient of variation) compared with nonoptimized studies. Estimates of population size from the scenarios based on the IUCN thresholds were mostly unbiased and robust (only the combination of very small populations and little study effort produced unreliable estimates), suggesting capture–recapture can be considered reliable for informing red-list assessments. Although capture–recapture remains difficult and costly for elusive species, our optimization procedure can help determine efficient protocols to increase data quality and minimize monitoring effort.     

Influence of Chronic Man-made Pollution on Bromus inermis Genome Size

Russian Journal of Ecology - Technogenic pollution can accelerate microevolutionary processes in natural populations. We estimated the nuclear DNA content of 10 Bromus inermis Leyss. samples from...     

Field effectiveness evaluation of advanced driver assistance systems

Abstract

Objective: Advanced driver assistance systems (ADAS) are a class of vehicle technologies designed to increase safety by providing drivers with timely warnings and autonomously intervening to avoid hazardous situations. Though laboratory testing suggests that ADAS technologies will greatly impact crash involvement rates, real-world evidence that characterizes their effectiveness is still limited. This study evaluates and quantifies the association of ADAS technologies with the likelihood of a moderate or severe crash for new-model BMWs in the United States.

Methods: Vehicle ADAS option information for the cohort of model year 2014 and later BMW passenger vehicles sold after January 1, 2014 (n?=?1,063,503), was coded using VIN-identified options data. ADAS technologies of interest include frontal collision warning with autonomous emergency braking, lane departure warning, and blind spot detection. BMW Automated Crash Notification system data (from January 2014 to November 2017) were merged with vehicle data by VIN to identify crashed vehicles (n?=?15,507), including date, crash severity (delta V), and area of impact. Using Cox proportional hazards regression modeling, the study calculates the adjusted hazard ratio for crashing among BMW passenger vehicles with versus without ADAS technologies. The adjusted percentage reduction in moderate and severe crashes associated with ADAS is interpreted as one minus the hazard ratio.

Results: Vehicles equipped with both autonomous emergency braking and lane departure warning were 23% less likely to crash than those not equipped (hazard ratio [HR]?=?0.77; 95% confidence interval [CI], 0.73–0.81), controlling for model year, vehicle size and body type. Autonomous emergency braking and lane departure warning generally occur together, making it difficult to tease apart their individual effects. Blind spot detection was associated with a 14% reduction in crashes after controlling for the presence of autonomous emergency braking and lane departure warning (HR =0.86; 95% CI, 0.744–0.99). Differences were observed by vehicle type and crash type. The combined effect of autonomous emergency braking and lane departure warning was greater in newer model vehicles: Equipped vehicles were 13% less likely to crash (HR =0.87; 95% CI, 0.79–0.95) among 2014 model year vehicles versus 34% less likely to crash (HR =0.66; 95% CI, 0.57–0.77) among 2017 model year vehicles.

Conclusion: This robust cohort study contributes to the growing evidence on the effectiveness of ADAS technologies.     

Polynomial Surrogates for Open-Channel Flows in Random Steady State

Assessing epistemic uncertainties is considered as a milestone for improving numerical predictions of a dynamical system. In hydrodynamics, uncertainties in input parameters translate into uncertainties in simulated water levels through the shallow water equations. We investigate the ability of generalized polynomial chaos (gPC) surrogate to evaluate the probabilistic features of water level simulated by a 1-D hydraulic model (MASCARET) with the same accuracy as a classical Monte Carlo method but at a reduced computational cost. This study highlights that the water level probability density function and covariance matrix are better estimated with the polynomial surrogate model than with a Monte Carlo approach on the forward model given a limited budget of MASCARET evaluations. The gPC-surrogate performance is first assessed on an idealized channel with uniform geometry and then applied on the more realistic case of the Garonne River (France) for which a global sensitivity analysis using sparse least-angle regression was performed to reduce the size of the stochastic problem. For both cases, Galerkin projection approximation coupled to Gaussian quadrature that involves a limited number of forward model evaluations is compared with least-square regression for computing the coefficients when the surrogate is parameterized with respect to the local friction coefficient and the upstream discharge. The results showed that a gPC-surrogate with total polynomial degree equal to 6 requiring 49 forward model evaluations is sufficient to represent the water level distribution (in the sense of the \(\ell _2\) norm), the probability density function and the water level covariance matrix for further use in the framework of data assimilation. In locations where the flow dynamics is more complex due to bathymetry, a higher polynomial degree is needed to retrieve the water level distribution. The use of a surrogate is thus a promising strategy for uncertainty quantification studies in open-channel flows and should be extended to unsteady flows. It also paves the way toward cost-effective ensemble-based data assimilation for flood forecasting and water resource management.     

Simulating and delineating future land change trajectories across Europe

Explorations of future land use change are important to understand potential conflicts between competing land uses, trade-offs associated with particular land change trajectories, and the effectiveness of policies to steer land systems into desirable states. Most model-based explorations and scenario studies focused on conversions in broad land use classes, but disregarded changes in land management or focused on individual sectors only. Using the European Union (EU) as a case study, we developed an approach to identifying typical combinations of land cover and management changes by combining the results of multimodel simulations in the agriculture and forest sectors for four scenarios from 2000 to 2040. We visualized land change trajectories by mapping regional hotspots of change. Land change trajectories differed in extent and spatial pattern across the EU and among scenarios, indicating trajectory-specific option spaces for alternative land system outcomes. In spite of the large variation in the area of change, similar hotspots of land change were observed among the scenarios. All scenarios indicate a stronger polarization of land use in Europe, with a loss of multifunctional landscapes. We analyzed locations subject to change by comparing location characteristics associated with certain land change trajectories. Results indicate differences in the location conditions of different land change trajectories, with diverging impacts on ecosystem service provisioning. Policy and planning for future land use needs to account for the spatial variation of land change trajectories to achieve both overarching and location-specific targets.

     

Two sampling strategies for an overview of pesticide contamination in an agriculture-extensive headwater stream

Two headwaters located in southwest France were monitored for 3 and 2 years (Auvézère and Aixette watershed, respectively) with two sampling strategies: grab and passive sampling with polar organic chemical integrative sampler (POCIS). These watersheds are rural and characterized by agricultural areas with similar breeding practices, except that the Auvézère watershed contains apple production for agricultural diversification and the downstream portion of the Aixette watershed is in a peri-urban area. The agricultural activities of both are extensive, i.e., with limited supply of fertilizer and pesticides. The sampling strategies used here give specific information: grab samples for higher pesticide content and POCIS for contamination background noise and number of compounds found. Agricultural catchments in small headwater streams are characterized by a background noise of pesticide contamination in the range of 20–70 ng/L, but there may also be transient and high-peak pesticide contamination (2000–3000 ng/L) caused by rain events, poor use of pesticides, and/or the small size of the water body. This study demonstrates that between two specific runoff events, contamination was low; hence the importance of passive sampler use. While the peak pesticide concentrations seen here are a toxicity risk for aquatic life, the pesticide background noise of single compounds do not pose obvious acute nor chronic risks; however, this study did not consider the risk from synergistic “cocktail” effects. Proper tools and sampling strategies may link watershed activities (agricultural, non-agricultural) to pesticides detected in the water, and data from both grab and passive samples can contribute to discussions on environmental effects in headwaters, an area of great importance for biodiversity.     

A multi-agent simulation model for spatial optimisation of manure allocation

The EU Nitrate Directive has spurred many countries to regulate manure production and manure application. Farmers have three allocation options: spreading manure on their own land, transporting manure to other farmers' land or processing manure. The manure problem can be seen as an allocation problem. To better understand this allocation problem, we have developed the spatial mathematical programming multi-agent simulation (MP-MAS) model. This model has been applied in Flanders, Belgium, a region with a high concentration of livestock. The model evaluates the cost efficiency of policy intervention in the manure market through obliged processing. We propose to further optimise the policy using a regionally differentiated manure pressure indicator, which is directly derived from the dual outcome of the mathematical programme. This indicator increases transparency in the manure and processing market, leading to better decision support about location and type of manure processing.