Species composition of the international shark fin trade assessed through a retail‐market survey in Hong Kong

The shark fin trade is a major driver of shark exploitation in fisheries all over the world, most of which are not managed on a species‐specific basis. Species‐specific trade information highlights taxa of particular concern and can be used to assess the efficacy of management measures and anticipate emerging threats. The species composition of the Hong Kong Special Administrative Region of China, one of the world's largest fin trading hubs, was partially assessed in 1999–2001. We randomly selected and genetically identified fin trimmings (n = 4800), produced during fin processing, from the retail market of Hong Kong in 2014–2015 to assess contemporary species composition of the fin trade. We used nonparametric species estimators to determine that at least 76 species of sharks, batoids, and chimaeras supplied the fin trade and a Bayesian model to determine their relative proportion in the market. The diversity of traded species suggests species substitution could mask depletion of vulnerable species; one‐third of identified species are threatened with extinction. The Bayesian model suggested that 8 species each comprised >1% of the fin trimmings (34.1–64.2% for blue [Prionace glauca], 0.2–1.2% for bull [Carcharhinus leucas] and shortfin mako [Isurus oxyrinchus]); thus, trade was skewed to a few globally distributed species. Several other coastal sharks, batoids, and chimaeras are in the trade but poorly managed. Fewer than 10 of the species we modeled have sustainably managed fisheries anywhere in their range, and the most common species in trade, the blue shark, was not among them. Our study and approach serve as a baseline to track changes in composition of species in the fin trade over time to better understand patterns of exploitation and assess the effects of emerging management actions for these animals.     

Evaluating the outcomes of genetic rescue attempts

Augmenting gene flow is a powerful tool for the conservation of small, isolated populations. However, genetic rescue attempts have largely been limited to populations at the brink of extinction, in part due to concerns over negative outcomes (e.g., outbreeding depression). Increasing habitat fragmentation may necessitate more proactive genetic management. Broader application of augmented gene flow will, in turn, require rigorous evaluation to increase confidence and identify pitfalls in this approach. To date, there has been no assessment of best monitoring practices for genetic rescue attempts. We used genomically explicit, individual-based simulations to examine the effectiveness of common approaches (i.e., tests for increases in fitness, migrant ancestry, heterozygosity, and abundance) for determining whether genetic rescue or outbreeding depression occurred. Statistical power to detect the effects of gene flow on fitness was high (≥0.8) when effect sizes were large, a finding consistent with those from previous studies on severely inbred populations. However, smaller effects of gene flow on fitness can appreciably affect persistence probability but current evaluation approaches fail to provide results from which reliable inferences can be drawn. The power of the metrics we examined to evaluate genetic rescue attempts depended on the time since gene flow and whether gene flow was beneficial or deleterious. Encouragingly, the use of multiple metrics provided nonredundant information and improved inference reliability, highlighting the importance of intensive monitoring efforts. Further development of best practices for evaluating genetic rescue attempts will be crucial for a responsible transition to increased use of translocations to decrease extinction risk.     

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.