Understanding complex drivers of wildlife crime to design effective conservation interventions

In conservation understanding the drivers of behavior and developing robust interventions to promote behavioral change is challenging and requires a multifaceted approach. This is particularly true for efforts to address illegal wildlife use, where pervasive—and sometimes simplistic—narratives often obscure complex realities. We used an indirect questioning approach, the unmatched count technique, to investigate the drivers and prevalence of wildlife crime in communities surrounding 2 national parks in Uganda and combined scenario interviews and a choice experiment to predict the performance of potential interventions designed to tackle these crimes. Although poverty is often assumed to be a key driver of wildlife crime, we found that better-off households and those subject to human–wildlife conflict and those that do not receive any benefits from the parks’ tourism revenue sharing were more likely to be involved in certain types of wildlife crime, especially illegal hunting. The interventions predicted to have the greatest impact on reducing local participation in wildlife crime were those that directly addressed the drivers including, mitigating damage caused by wildlife and generating financial benefits for park-adjacent households. Our triangulated approach provided insights into complex and hard-to-access behaviors and highlighted the importance of going beyond single-driver narratives.     

Long‐distance flights and high‐risk breeding by nomadic waterbirds on desert salt lakes

Understanding and conserving mobile species presents complex challenges, especially for animals in stochastic or changing environments. Nomadic waterbirds must locate temporary water in arid biomes where rainfall is highly unpredictable in space and time. To achieve this they need to travel over vast spatial scales and time arrival to exploit pulses in food resources. How they achieve this is an enduring mystery.  We investigated these challenges in the colonial‐nesting Banded Stilt (Cladorhynchus leucocephalus), a nomadic shorebird of conservation concern. Hitherto, Banded Stilts were hypothesized to have only 1–2 chances to breed during their long lifetime, when flooding rain fills desert salt lakes, triggering mass‐hatching of brine shrimp. Over 6 years, we satellite tagged 57 individuals, conducted 21 aerial surveys to detect nesting colonies on 14 Australian desert salt lakes, and analyzed 3 decades of Landsat and MODIS satellite imagery to quantify salt‐lake flood frequency and extent. Within days of distant inland rainfall, Banded Stilts flew 1,000–2,000 km to reach flooded salt lakes. On arrival, females laid over half their body weight in eggs. We detected nesting episodes across the species’ range at 7 times the frequency reported during the previous 80 years. Nesting colonies of thousands formed following minor floods, yet most were subsequently abandoned when the water rapidly evaporated prior to egg hatching. Satellite imagery revealed twice as many flood events sufficient for breeding‐colony initiation as recorded colonies, suggesting that nesting at remote sites has been underdetected. Individuals took risk on uncertain breeding opportunities by responding to frequent minor flood events between infrequent extensive flooding, exemplifying the extreme adaptability and trade‐offs of species exploiting unstable environments. The conservation challenges of nest predation by overabundant native gulls and anthropogenic modifications to salt lakes filling frequencies require investigation, as do the physiological and navigational mechanisms that enable such extreme strategies.     

Crop uptake of heavy metals in response to the environment and agronomic practices on land near mine tailings in the Zambian Copperbelt Province

Environmental Geochemistry and Health - A field experiment was undertaken on farmers’ fields adjacent to a large mine tailings dam in the Zambian mining town of Kitwe. Experimental plots were...     

Effects of seascape connectivity on reserve performance along exposed coastlines

Seascape connectivity (landscape connectivity in the sea) can modify reserve performance in low-energy marine ecosystems (e.g., coral reefs, mangroves, and seagrass), but it is not clear whether similar spatial linkages also shape reserve effectiveness on high-energy, exposed coastlines. We used the surf zones of ocean beaches in eastern Australia as a model system to test how seascape connectivity and reserve attributes combine to shape conservation outcomes. Spatial patterns in fish assemblages were measured using baited remote underwater video stations in 12 marine reserves and 15 fished beaches across 2000 km of exposed coastline. Reserve performance was shaped by both the characteristics of reserves and the spatial properties of the coastal seascapes in which reserves were embedded. Number of fish species and abundance of harvested fishes were highest in surf-zone reserves that encompassed >1.5 km of the surf zone; were located < 100 m to rocky headlands; and included pocket beaches in a heterogeneous seascape. Conservation outcomes for exposed coastlines may, therefore, be enhanced by prioritizing sufficiently large areas of seascapes that are strongly linked to abutting complementary habitats. Our findings have broader implications for coastal conservation planning. Empirical data to describe how the ecological features of high-energy shorelines influence conservation outcomes are lacking, and we suggest that seascape connectivity may have similar ecological effects on reserve performance on both sheltered and exposed coastlines.     

Ecosystem-inspired model and artificial intelligence predicts pollutant consumption capacity by coagulation in drinking water treatment

Conventional methods for water and wastewater treatment are energy-intensive, notably at the stage of coagulation–flocculation, calling for new strategies to predict pollutant reduction because the amount of energy consumed is related to how much of the pollutant is treated. Here we developed a model, named Bio-logic, inspired by ecosystems, where pollutants represent organisms, coagulants are food, and the wider environmental conditions are the living environment. Artificial intelligence was used to learn the biological behavior, which enabled an accurate prediction of the amount of pollutant reduction. Results show that pseudo-biological objects that have a strong affinity for biological food, such as turbidity, total phosphorus, ammonia nitrogen and the potassium permanganate index, induced a strong correlation, between measured pollutant consumption capacity and predicted values. For instance, R² correlation coefficients are 0.97 for turbidity and 0.92 for the potassium permanganate index in the laboratory; and 0.99 for turbidity, 0.90 for total phosphorus, 0.75 for ammonia nitrogen and 0.63 for the potassium permanganate index in water treatment plants. Overall, our findings demonstrate that artificial intelligence can use the water Bio-logic model to predict the pollutant consumption capacity.

     

A call to action for climate change research on Caribbean dry forests

Regional Environmental Change - Tropical dry forest (TDF) is globally one of the most threatened forest types. In the insular Caribbean, limited land area and high population pressure have resulted...     

Uncovering blind spots in urban carbon management: the role of consumption-based carbon accounting in Bristol,UK

The rapid urbanisation of the twentieth century, along with the spread of high-consumption urban lifestyles, has led to cities becoming the dominant drivers of global anthropogenic greenhouse gas emissions. Reducing these impacts is crucial, but production-based frameworks of carbon measurement and mitigation—which encompass only a limited part of cities’ carbon footprints—are much more developed and widely applied than consumption-based approaches that consider the embedded carbon effectively imported into a city. Frequently, therefore, cities are left blind to the importance of their wider consumption-related climate impacts, while at the same time left lacking effective tools to reduce them. To explore the relevance of these issues, we implement methodologies for assessing production- and consumption-based emissions at the city-level and estimate the associated emissions trajectories for Bristol, a major UK city, from 2000 to 2035. We develop mitigation scenarios targeted at reducing the former, considering potential energy, carbon and financial savings in each case. We then compare these mitigation potentials with local government ambitions and Bristol’s consumption-based emissions trajectory. Our results suggest that the city’s consumption-based emissions are three times the production-based emissions, largely due to the impacts of imported food and drink. We find that low-carbon investments of circa £3 billion could reduce production-based emissions by 25% in 2035. However, we also find that this represents <10% of Bristol’s forecast consumption-based emissions for 2035 and is approximately equal to the mitigation achievable by eliminating the city’s current levels of food waste. Such observations suggest that incorporating consumption-based emission statistics into cities’ accounting and decision-making processes could uncover largely unrecognised opportunities for mitigation that are likely to be essential for achieving deep decarbonisation.

     

Dominance rank differences in the energy intake and expenditure of female Bwindi mountain gorillas

Socioecological models predict that contest competition for clumped foods can lead to higher energy intake and lower energy expenditure for higher-ranking individuals. Here, we examine the relationships between dominance rank and energy intake and expenditure of female mountain gorillas in Bwindi Impenetrable National Park, Uganda (Gorilla beringei beringei). Bwindi gorillas have weak dominance relationships, feed on nonreproductive plant parts throughout the year, and consume fruit when it is seasonally available. We used behavioral observations on one group of gorillas and nutritional analysis of their major food items to calculate energy intake rates and estimated energy expenditure. Using linear mixed models, we found a significant positive relationship between dominance rank and energy intake rates, due to higher-ranking females having faster ingestion rates, rather than consuming foods with higher energy concentrations. Lower-ranking females did not spend significantly more time feeding to compensate for their lower energy intake rates. Lower-ranking females spent significantly more time traveling than higher-ranking females, leading to a negative relationship between dominance rank and energy expenditure. The combined results revealed a significant positive relationship between dominance rank and energy balance. Higher-ranking females did not spend longer feeding on fruit than lower-ranking ones, and the relationship between dominance rank and energy intake rates was not stronger when fruit was available. According to socioecological models, these results suggest that contest competition may be occurring with both fruit and nonreproductive plant parts, which would be consistent with growing evidence that nonreproductive plant parts can be contestable.     

Agroecosystem energy transitions in the old and new worlds: trajectories and determinants at the regional scale

Energy efficiency in biomass production is a major challenge for a future transition to sustainable food and energy provision. This study uses methodologically consistent data on agroecosystem energy flows and different metrics of energetic efficiency from seven regional case studies in North America (USA and Canada) and Europe (Spain and Austria) to investigate energy transitions in Western agroecosystems from the late nineteenth to the late twentieth centuries. We quantify indicators such as external final energy return on investment (EFEROI, i.e., final produce per unit of external energy input), internal final EROI (IFEROI, final produce per unit of biomass reused locally), and final EROI (FEROI, final produce per unit of total inputs consumed). The transition is characterized by increasing final produce accompanied by increasing external energy inputs and stable local biomass reused. External inputs did not replace internal biomass reinvestments, but added to them. The results were declining EFEROI, stable or increasing IFEROI, and diverging trends in FEROI. The factors shaping agroecosystem energy profiles changed in the course of the transition: Under advanced organic and frontier agriculture of the late nineteenth and early twentieth centuries, population density and biogeographic conditions explained both agroecosystem productivity and energy inputs. In industrialized agroecosystems, biogeographic conditions and specific socio-economic factors influenced trends towards increased agroecosystem specialization. The share of livestock products in a region’s final produce was the most important factor determining energy returns on investment.