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Landscape ecologists have long suggested that pest abundances increase in simplified, monoculture landscapes. However, tests of this theory often fail to predict pest population sizes in real-world agricultural fields. These failures may arise not only from variation in pest ecology, but also from the widespread use of categorical land-use maps that do not adequately characterize habitat-availability for pests. We used 1163 field-year observations of Lygus hesperus (Western Tarnished Plant Bug) densities in California cotton fields to determine whether integrating remotely-sensed metrics of vegetation productivity and phenology into pest models could improve pest abundance analysis and prediction. Because L. hesperus often overwinters in non-crop vegetation, we predicted that pest abundances would peak on farms surrounded by more non-crop vegetation, especially when the non-crop vegetation is initially productive but then dries down early in the year, causing the pest to disperse into cotton fields. We found that the effect of non-crop habitat on pest densities varied across latitudes, with a positive relationship in the north and a negative one in the south. Aligning with our hypotheses, models predicted that L. hesperus densities were 35 times higher on farms surrounded by high versus low productivity non-crop vegetation (EVI area 350 vs. 50) and 2.8 times higher when dormancy occurred earlier versus later in the year (May 15 vs. June 30). Despite these strong and significant effects, we found that integrating these remote-sensing variables into land-use models only marginally improved pest density predictions in cotton compared to models with categorical land cover metrics alone. Together, our work suggests that the remote sensing variables analyzed here can advance our understanding of pest ecology, but not yet substantively increase the accuracy of pest abundance predictions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Mangrove forests support unique biodiversity and provide a suite of ecosystem services (ES) that benefit people. Decades of continual mangrove loss and degradation have necessitated global efforts to protect and restore this important ecosystem. Generating and evaluating asset maps of biodiversity and ES is an important precursor to identifying locations that can deliver conservation outcomes across varying scales, such as maximising the co-occurrence of specific ES. We bring together global datasets on mangrove-affiliated biodiversity, carbon stocks, fish and invertebrate production, and coastal protection to provide insight into potential trade-offs, synergies and opportunities from mangrove conservation. We map opportunities where high ES provision co-occurs with these areas that could be leveraged in conservation planning, and identify potential high-value opportunities for single ES that might otherwise be missed with a biodiversity focus. Hotspots of single ES, co-occurrence of multiple ES, and opportunities to simultaneously leverage biodiversity and ES occurred throughout the world. For example, efforts that focus on conserving or restoring mangroves to store carbon can be targed to deliver multiple ES benefits. Some nations, such as Vietnam, Oman, Ecuador and China, showed consistent (although not necessarily strong) correlations between ES pairs. A lack of clear or consistent spatial trends elsewhere suggests that some nations will likely benefit more from complementarity-based approaches that focus on multiple sites with high provision of different services. Individual sites within these nations, however, such as Laguna de Terminos in Mexico still provide valuable opportunities to leverage co-benefits. Ensuring that an ES focused approach is complemented by strategic spatial planning is a priority, and our analyses provide a precursor towards decisions about where and how to invest., Competing Interests: Declaration of competing interest The authors declare no conflicts of interest., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Mangrove ecosystems are among the most economically and ecologically valuable marine environments in the world. Mangroves are effective at long-term carbon storage within their sediments and are estimated to hold 12 billion metric tons of carbon worldwide. These ecosystems are therefore vitally important for carbon sequestration and, by extension, climate change mitigation. As part of the Paris Agreement, participating countries agree to provide plans to reduce their carbon emissions, or nationally determined contributions (NDCs). However, despite mangroves being recognized as important nature-based solutions, many countries still lack national data on carbon stocks and must use global or regional averages, which may not be sufficiently accurate. Here, we present the national carbon stock estimate of mangrove ecosystems for the NDC of Belize, acquired through a collaborative approach involving government agencies and NGOs. We conducted a comprehensive sampling of mangroves across the country, including a range of mangrove ecotypes. The mean total ecosystem carbon stock (TECS) for the nation was 444.1 ± 21.0 Mg C ha -1 , with 74.4 ± 6.2 Mg C ha -1 in biomass stocks, and 369.7 ± 17.7 Mg C ha -1 in sediment stocks. Combining these data with a recent mapping effort, we provide the first national comprehensive mangrove carbon stock estimate of 25.7 Tg C. The national mean from this study varies from previous global analyses, which can under- or overestimate TECS by as much as 0.6 Tg C and 16.5 Tg C, respectively, depending on the study. These data supported the NDC update of Belize, and can be used to inform the country's mangrove protection and restoration commitments. The collaborative approach of this work should serve as a blueprint for other countries seeking to conserve natural blue carbon sinks as a strategy to achieve their climate targets., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Indonesia is embarking on an ambitious relocation of its capital city to Kalimantan, Borneo, bringing with it major urban and road infrastructure. Yet, despite being one of the world's most biologically diverse regions, the potential implications of this development for wildlife have yet to be fully assessed. We explored the potential impacts of the capital relocation, and road expansion and upgrades to critical habitat for medium-large mammals (>1 kg) using camera trap data from 11 forested landscapes. We applied Bayesian multi-species occupancy models to predict community and species-level responses to anthropogenic and environmental factors. We extrapolated spatial patterns of occupancy and species diversity across the forests of Kalimantan and identified "critical habitats" as the top 20 th percentile of occupancy and species richness values. We subsequently overlapped these critical habitat layers with infrastructure impact zones to estimate the area that could potentially be affected by direct or secondary impacts. At both the community and species-level, distance to primary roads had the strongest negative influence on habitat-use. Occupancy was also influenced by forest quality and multidimensional poverty conditions in adjacent villages, demonstrating the sensitivity of biodiversity to socio-ecological pressures. Less than 1 % of the critical habitat for the threatened mammal community lay within the direct impact zone (30 km radius) of the capital relocation. However, approximately 16 % was located within 200 km and could potentially be affected by uncontrolled secondary impacts such as urban sprawl and associated regional development. The often-overlooked secondary implications of upgrading existing roads could also intersect a large amount of critical habitat for lowland species. Mitigating far-reaching secondary impacts of infrastructure development should be fully incorporated into environmental impact assessments. This will provide Indonesia with an opportunity to set an example of sustainable infrastructure development in the tropics., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Landscape scale wetland conservation requires accurate, up-to-date wetland maps. The most useful approaches to creating such maps are automated, spatially generalizable, temporally repeatable, and can be applied at large spatial scales. However, mapping wetlands with predictive models is challenging due to the highly variable characteristics of wetlands in both space and time. Currently, most approaches are limited by coarse resolution, commercial data, and geographic specificity. Here, we trained a deep learning model and evaluated its ability to automatically map wetlands at landscape scale in a variety of geographies. We trained a U-Net architecture to map wetlands at 1-meter spatial resolution with the following remotely sensed covariates: multispectral data from the National Agriculture Imagery Program and the Sentinel-2 satellite system, and two LiDAR-derived datasets, intensity and geomorphons. The full model mapped wetlands accurately (94 % accuracy, 96.5 % precision, 95.2 % AUC) at 1-meter resolution. Post hoc model evaluation showed that the model correctly predicted wetlands even in areas that had incorrect label/training data, which penalized the recall rate (90.2 %). Applying the model in a new geography resulted in poor performance (precision = ~80 %, recall = 48 %). However, limited retraining in this geography improved model performance substantially, demonstrating an effective means to create a spatially generalizable model. We demonstrate wetlands can be mapped at high-resolution (1 m) using free data and efficient deep-learning models that do not require manual feature engineering. Including LiDAR and geomorphons as input data improved model accuracy by 2 %, and where these data are unavailable a simpler model can efficiently map wetlands. Given the dynamic nature of wetlands and the important ecosystem services they provide, high-resolution mapping can be a game changer in terms of informing restoration and development decisions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Despite the detection of a wide range of contaminants in the blood of green turtle populations foraging in three locations of northern Queensland - Upstart Bay, Cleveland Bay and the Howick Group of Reefs, little is known about the effects of these contaminants on turtle health. Newly developed cell-based bioassays using green turtle primary cell cultures provide an ethical, reproducible, and high-throughput method for assessing the risk of chemical exposure sea turtles. In this project, the toxicity of six priority metals (Mn, Co, Mo, As, Sb, Cu) and blood extracts from foraging turtles were tested in two bioassays adapted to green turtle primary skin and liver cells. Cytotoxicity of metals and blood extracts was measured in primary skin fibroblast cells using a resazurin assay. Glutathione-S-transferase (GST) activity was measured in primary skin fibroblasts and primary liver epithelial cells following exposure to metals and blood extracts. Arsenic, molybdenum, cobalt and copper were found to be cytotoxic to green turtle skin cells. Only manganese, cobalt and copper were found to alter GST activity, predominantly in skin cells, indicating a higher sensitivity of green turtle skin cells compared to liver cells. Effect concentrations of metals in both bioassays were above concentrations found in turtle blood. Turtle blood extracts from the three foraging grounds showed differences in cytotoxicity and GST activity. In both assays, blood extracts of turtles from Upstart Bay were the most toxic, followed by those from Cleveland Bay, then the Howick Reefs, suggesting turtles from Upstart Bay and Cleveland Bay may be at risk from current concentrations of organic contaminants. This study demonstrates that species-specific cell-based bioassays can be used effectively to assess chemical risk in sea turtles and their foraging grounds, and could be applied to assess chemical risk in other marine wildlife., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

We develop and link the Integrated Economic-Environmental Modeling (IEEM) Platform to ecosystem services modeling (ESM). The IEEM+ESM Platform is an innovative decision-making framework for exploring complex public policy goals and elucidating synergies and trade-offs between alternative policy portfolios. The IEEM+ESM approach is powerful in its ability to shed light on (i) change in land use and ecosystem services driven by public policy and the supply and demand responses of businesses and households; and (ii) impacts on standard economic indicators of concern to Ministries of Finance such as gross domestic product and employment, as well as changes in wealth and ecosystem services. The IEEM+ESM approach is being adopted rapidly and by the end of 2020, IEEM+ESM Platforms will be implemented for about 25 countries. To demonstrate the insights generated by the IEEM+ESM approach, we apply it to the analysis of alternative green growth strategies in Rwanda, a country that has made strong progress in reducing poverty and enhancing economic growth in the last 15 years. The case of Rwanda is particularly compelling as it faces intense pressure on its natural capital base and ecosystem services, already with the highest population density in Africa, which is projected to double by 2050. In applying IEEM+ESM and comparing the outcomes of Rwanda's green growth policies, increasing fertilization of agricultural crops shows the largest economic gains but also trade-offs in environmental quality reflected through higher nutrient export and reduced water quality. Combining crop fertilization with forest plantations better balances critical ecosystem services and their role in underpinning economic development as Rwanda progresses toward its target of middle-income status by 2035. This application to Rwanda's green growth strategy demonstrates the value-added of the IEEM+ESM approach in generating results that speak to both economic outcomes and impacts on market and non-market ecosystem services., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Collisions between ships and whales raise environmental, safety, and economic concerns. The management of whale-ship collisions, however, lacks a holistic approach, unlike the management of other types of wildlife-vehicle collisions, which have been more standardized for several years now. In particular, safety and economic factors are routinely omitted in the assessment of proposed mitigation solutions to ship strikes, possibly leading to under-compliance and a lack of acceptance from the stakeholders. In this study, we estimate the probability of ship damage due to a whale-ship collision. While the probability of damage is low, the costs could be important, suggesting that property damages are significant enough to be taken into consideration when assessing solutions. Lessons learned from other types of wildlife-vehicle collisions suggest that the whale-ship collision should be managed as wildlife-aircraft collisions. For several years, the International Civil Aviation Organization (ICAO) manages collisions between aircrafts and wildlife at the international level. We advocate that its United Nations counterpart, namely the International Maritime Organization (IMO), get more involved in the whale-ship collision management. Further research is needed to more precisely quantify the costs incurred to ships from damages caused by whale-ship collisions., Competing Interests: Declaration of competing interest None., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Marine megafauna that forage in proximity to land can be exposed to a diverse mixture of chemicals that - individually or combined - have the potential to affect their health. Characterizing such complex exposure and examining associations with health still poses considerable challenges. The present study summarizes the development and application of novel approaches to identifying chemical hazards and their potential impacts on the health of coastal wildlife, using green sea turtles as model species. We used an epidemiological study approach to collect blood and keratinized scute samples from free-ranging turtles foraging in nearshore areas and an offshore control site. These were analyzed using a combination of non-targeted, effect-based and multi-chemical analytical screening approaches to assess internal exposure to a wide range of chemicals. The screening phase identified a suite of elements (essential and non-essential) as priority for further investigation. Many of these elements are not commonly analyzed in marine wildlife, illustrating that comprehensive screening is important where exposure is unknown or uncertain. In particular, cobalt was present at highly elevated concentrations, in the order of those known to elicit acute effects across other vertebrate species. Several trace elements, including cobalt, were correlated with clinical indicators of impaired turtle health. In addition, biomarkers of oxidative stress (e.g. 3-indolepropionic acid and lipid peroxidation products) identified in the blood of turtles showed significant correlations with clinical health markers (particularly alkaline phosphatase and total bilirubin), as well as with cobalt. To assist interpretation of trace element blood data in the absence of sufficient information on reptile toxicity, we established exposure reference intervals using a healthy control population. In addition, trace element exposure history was investigated by establishing temporal exposure indices using steady-state relationships between blood and scute. Overall, the data provide a strong argument for the notion that trace element exposure is having an impact on the health of coastal sea turtle populations., (Copyright © 2018. Published by Elsevier B.V.)

Green turtles spend a large part of their lifecycle foraging in nearshore seagrass habitats, which are often in close proximity to sources of anthropogenic contaminants. As most biomonitoring studies focus on a limited number of targeted chemical groups, this study was designed to screen for a wider range of hazardous chemicals that may not have been considered in prior studies. Whole blood of sub-adult green turtles (Chelonia mydas) were sampled from three different locations, a remote, offshore 'control' site; and two coastal 'case' sites influenced by urban and agricultural activities on the Great Barrier Reef in North Queensland, Australia. In order to screen blood samples for chemicals across a wide range of K OW 's, a modified QuEChER's extraction method was used. The samples were analysed using a multi-residue gas chromatography with tandem mass spectrometry system (GC-MS/MS method that allowed simultaneous quantification of polychlorinated biphenyls (PCBs), polychlorinated diphenyl ethers (PBDES), organochlorine pesticides (OCPs) and polycyclic aromatic hydrocarbons (PAHs). While PBDEs, PCBs and OCPS were below the limits of quantification, PAHs were detected in all turtle blood samples. However, PAH levels were relatively low (maximum ΣPAH = 13 ng/mL ww) and comparable to or less than those reported from other green turtles globally. The present study provides the first baseline PAH levels in blood samples from green turtles from nearshore and offshore locations in the Southern Hemisphere., (Copyright © 2018. Published by Elsevier B.V.)

Degradation of freshwater ecosystems and the services they provide is a primary cause of increasing water insecurity, raising the need for integrated solutions to freshwater management. While methods for characterizing the multi-faceted challenges of managing freshwater ecosystems abound, they tend to emphasize either social or ecological dimensions and fall short of being truly integrative. This paper suggests that management for sustainability of freshwater systems needs to consider the linkages between human water uses, freshwater ecosystems and governance. We present a conceptualization of freshwater resources as part of an integrated social-ecological system and propose a set of corresponding indicators to monitor freshwater ecosystem health and to highlight priorities for management. We demonstrate an application of this new framework -the Freshwater Health Index (FHI) - in the Dongjiang River Basin in southern China, where stakeholders are addressing multiple and conflicting freshwater demands. By combining empirical and modeled datasets with surveys to gauge stakeholders' preferences and elicit expert information about governance mechanisms, the FHI helps stakeholders understand the status of freshwater ecosystems in their basin, how ecosystems are being manipulated to enhance or decrease water-related services, and how well the existing water resource management regime is equipped to govern these dynamics over time. This framework helps to operationalize a truly integrated approach to water resource management by recognizing the interplay between governance, stakeholders, freshwater ecosystems and the services they provide., (Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.)

Organisms are exposed to mixtures of both known and unknown chemicals which are diverse and variable, and thus difficult and costly to characterise and monitor using traditional target analyses. The objective of this study was to validate and apply in vitro effect-based methods by which whole blood can be used to screen internal exposure to such complex chemical mixtures. For this study, we used whole blood of green sea turtles (Chelonia mydas). To ensure the chemical mixture in blood is transferred with minimal losses or bias, we tested a modified QuEChERS extraction method specifically developed for multi- and non-target instrument analysis. The extracts were dosed to a battery of in vitro bioassays (AhR-CAFLUX, AREc32, NFκB-bla, VM7Luc4E2, Microtox), each with a different mode of action (e.g., AhR receptor mediated xenobiotics, NrF2-mediated oxidative stress, NFκB mediated response to inflammation, estrogen activity and baseline toxicity oxidative stress, respectively) in order to cover a wide spectrum of chemicals. Results confirmed the absence of interferences of the blood extract with the responses of the different assays, thus indicating the methods' compatibility with effect-based screening approaches. To apply this approach, whole blood samples were collected from green turtles foraging in agricultural, urban and remote areas of the Australian Great Barrier Reef. The effect-based screening revealed significant differences in exposure, with higher induction of AhR-CAFLUX, AREc32 and Microtox assays in turtles from the agricultural foraging ground. Overall, these results corroborated with concurrent health, target and non-target analyses in the same animals performed as part of a larger program. This study provides evidence that the proposed effect-based approach is suitable for screening and evaluating internal exposure of organisms to chemical mixtures. The approach could be valuable for advancing understanding on multiple levels ranging from identification of priority chemicals in effect-directed investigations to exploring relationships between exposure and disease, not only in sea turtles, but in any organism., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Chemical contamination poses a threat to ecosystem, biota and human health, and identifying these hazards is a complex challenge. Traditional hazard identification relies on a priori-defined targets of limited chemical scope, and is generally inappropriate for exploratory studies such as explaining toxicological effects in environmental systems. Here we present a non-target high resolution mass spectrometry environmental monitoring study with multivariate statistical analysis to simultaneously detect biomarkers of exposure (e.g. xenobiotics) and biomarkers of effect in whole turtle blood. Borrowing the concept from clinical chemistry, a case-control sampling approach was used to investigate the potential influence of xenobiotics of anthropogenic origin on free-ranging green sea turtles (Chelonia mydas) from a remote, offshore 'control' site; and two coastal 'case' sites influenced by urban/industrial and agricultural activities, respectively, on the Great Barrier Reef in North Queensland, Australia. Multiple biomarkers of exposure, including sulfonic acids (n=9), a carbamate insecticide metabolite, and other industrial chemicals; and five biomarkers of effect (lipid peroxidation products), were detected in case sites. Additionally, two endogenous biomarkers of neuroinflammation and oxidative stress were identified, and showed moderate-to-strong correlations with clinical measures of inflammation and liver dysfunction. Our data filtering strategy overcomes limitations of traditional a priori selection of target compounds, and adds to the limited environmental xenobiotic metabolomics literature. To our knowledge this is the first case-control study of xenobiotics in marine megafauna, and demonstrates the utility of green sea turtles to link internal and external exposure, to explain potential toxicological effects in environmental systems., (Copyright © 2017 Elsevier B.V. All rights reserved.)