Dataset of long-term monitoring of ground-dwelling ants (Hymenoptera: Formicidae) in the influence areas of a hydroelectric power plant on the Madeira River in the Amazon Basin

Background

Biodiversity loss is accelerating rapidly in response to increasing human influence on the Earth’s natural ecosystems. One way to overcome this problem is by focusing on places of human interest and monitoring the changes and impacts on the biodiversity. This study was conducted at six sites within the influence area of the Santo Antônio Hydroelectric Power Plant in the margins of the Madeira River in Rondônia State. The sites cover a latitudinal gradient of approximately 100 km in the Brazilian Amazon Basin. The sampling design included six sampling modules with six plots (transects) each, totaling 30 sampling plots. The transects were distributed with 0 km, 0.5 km, 1 km, 2 km, 3 km and 4 km, measured perpendicularly from the river margin towards the interior of the forest. For sampling the ground-dwelling ants, the study used the ALL (ants of the leaf litter) protocol, which is standardized globally in the inventories of ant fauna. For the purpose of impact indicators, the first two campaigns (September 2011 to November 2011) were carried out in the pre-filling period, while campaigns 3 to 10 (February 2012 to November 2014) were carried out during and after the filling of the hydroelectric reservoir. A total of 253 events with a total of 9,165 occurrences were accounted during the monitoring. The ants were distributed in 10 subfamilies, 68 genera and 324 species/morphospecies. The impact on ant biodiversity during the periods before and after filling was measured by ecological indicators and by the presence and absence of some species/morphospecies. This is the first study, as far as we know, including taxonomic and ecological treatment to monitor the impact of a hydroelectric power plant on ant fauna.

New information

Until recently, most studies conducted on hydroelectric plants, located in the Amazon Basin, were carried out after the implementation of dams in order to assess their impacts on the environment and biodiversity (Benchimol and Peres 2015, Latrubesse et al. 2017, Sá-Oliveira et al. 2015). Recent studies on dam impacts have begun to be conducted prior to dam implementation (e.g. Bobrowiec and Tavares 2017, Fraga et al. 2014, Moser et al. 2014), thus providing a better overview of the impact and a better assessment of its magnitude.

Evidence-Based Causal Chains for Linking Health, Development, and Conservation Actions

Sustainability challenges for nature and people are complex and interconnected, such that effective solutions require approaches and a common theory of change that bridge disparate disciplines and sectors. Causal chains offer promising approaches to achieving an integrated understanding of how actions affect ecosystems, the goods and services they provide, and ultimately, human well-being. Although causal chains and their variants are common tools across disciplines, their use remains highly inconsistent, limiting their ability to support and create a shared evidence base for joint actions. In this article, we present the foundational concepts and guidance of causal chains linking disciplines and sectors that do not often intersect to elucidate the effects of actions on ecosystems and society. We further discuss considerations for establishing and implementing causal chains, including nonlinearity, trade-offs and synergies, heterogeneity, scale, and confounding factors. Finally, we highlight the science, practice, and policy implications of causal chains to address real-world linked human-nature challenges.

Barriers and Solutions to Conducting Large International, Interdisciplinary Research Projects

Global environmental problems such as climate change are not bounded by national borders or scientific disciplines, and therefore require international, interdisciplinary teamwork to develop understandings of their causes and solutions. Interdisciplinary scientific work is difficult enough, but these challenges are often magnified when teams also work across national boundaries. The literature on the challenges of interdisciplinary research is extensive. However, research on international, interdisciplinary teams is nearly non-existent. Our objective is to fill this gap by reporting on results from a study of a large interdisciplinary, international National Science Foundation Partnerships for International Research and Education (NSF-PIRE) research project across the Americas. We administered a structured questionnaire to team members about challenges they faced while working together across disciplines and outside of their home countries in Argentina, Brazil, and Mexico. Analysis of the responses indicated five major types of barriers to conducting interdisciplinary, international research: integration, language, fieldwork logistics, personnel and relationships, and time commitment. We discuss the causes and recommended solutions to the most common barriers. Our findings can help other interdisciplinary, international research teams anticipate challenges, and develop effective solutions to minimize the negative impacts of these barriers to their research.

A social-ecological database to advance research on infrastructure development impacts in the Brazilian Amazon

Recognized as one of the world's most vital natural and cultural resources, the Amazon faces a wide variety of threats from natural resource and infrastructure development. Within this context, rigorous scientific study of the region's complex social-ecological system is critical to inform and direct decision-making toward more sustainable environmental and social outcomes. Given the Amazon's tightly linked social and ecological components and the scope of potential development impacts, effective study of this system requires an easily accessible resource that provides a broad and reliable data baseline. This paper brings together multiple datasets from diverse disciplines (including human health, socio-economics, environment, hydrology, and energy) to provide investigators with a variety of baseline data to explore the multiple long-term effects of infrastructure development in the Brazilian Amazon.

Integrated landscape approaches to managing social and environmental issues in the tropics: learning from the past to guide the future

Poverty, food insecurity, climate change and biodiversity loss continue to persist as the primary environmental and social challenges faced by the global community. As such, there is a growing acknowledgement that conventional sectorial approaches to addressing often inter-connected social, environmental, economic and political challenges are proving insufficient. An alternative is to focus on integrated solutions at landscape scales or 'landscape approaches'. The appeal of landscape approaches has resulted in the production of a significant body of literature in recent decades, yet confusion over terminology, application and utility persists. Focusing on the tropics, we systematically reviewed the literature to: (i) disentangle the historical development and theory behind the framework of the landscape approach and how it has progressed into its current iteration, (ii) establish lessons learned from previous land management strategies, (iii) determine the barriers that currently restrict implementation of the landscape approach and (iv) provide recommendations for how the landscape approach can contribute towards the fulfilment of the goals of international policy processes. This review suggests that, despite some barriers to implementation, a landscape approach has considerable potential to meet social and environmental objectives at local scales while aiding national commitments to addressing ongoing global challenges.

Anticipatory governance for social-ecological resilience

Anticipation is increasingly central to urgent contemporary debates, from climate change to the global economic crisis. Anticipatory practices are coming to the forefront of political, organizational, and citizens' society. Research into anticipation, however, has not kept pace with public demand for insights into anticipatory practices, their risks and uses. Where research exists, it is deeply fragmented. This paper seeks to identify how anticipation is defined and understood in the literature and to explore the role of anticipatory practice to address individual, social, and global challenges. We use a resilience lens to examine these questions. We illustrate how varying forms of anticipatory governance are enhanced by multi-scale regional networks and technologies and by the agency of individuals, drawing from an empirical case study on regional water governance of Mälaren, Sweden. Finally, we discuss how an anticipatory approach can inform adaptive institutions, decision making, strategy formation, and societal resilience.

The transparency, reliability and utility of tropical rainforest land-use and land-cover change models

Land-use and land-cover (LULC) change is one of the largest drivers of biodiversity loss and carbon emissions globally. We use the tropical rainforests of the Amazon, the Congo basin and South-East Asia as a case study to investigate spatial predictive models of LULC change. Current predictions differ in their modelling approaches, are highly variable and often poorly validated. We carried out a quantitative review of 48 modelling methodologies, considering model spatio-temporal scales, inputs, calibration and validation methods. In addition, we requested model outputs from each of the models reviewed and carried out a quantitative assessment of model performance for tropical LULC predictions in the Brazilian Amazon. We highlight existing shortfalls in the discipline and uncover three key points that need addressing to improve the transparency, reliability and utility of tropical LULC change models: (1) a lack of openness with regard to describing and making available the model inputs and model code; (2) the difficulties of conducting appropriate model validations; and (3) the difficulty that users of tropical LULC models face in obtaining the model predictions to help inform their own analyses and policy decisions. We further draw comparisons between tropical LULC change models in the tropics and the modelling approaches and paradigms in other disciplines, and suggest that recent changes in the climate change and species distribution modelling communities may provide a pathway that tropical LULC change modellers may emulate to further improve the discipline. Climate change models have exerted considerable influence over public perceptions of climate change and now impact policy decisions at all political levels. We suggest that tropical LULC change models have an equally high potential to influence public opinion and impact the development of land-use policies based on plausible future scenarios, but, to do that reliably may require further improvements in the discipline.

Environmental change and the carbon balance of Amazonian forests

Extreme climatic events and land-use change are known to influence strongly the current carbon cycle of Amazonia, and have the potential to cause significant global climate impacts. This review intends to evaluate the effects of both climate and anthropogenic perturbations on the carbon balance of the Brazilian Amazon and to understand how they interact with each other. By analysing the outputs of the Intergovernmental Panel for Climate Change (IPCC) Assessment Report 4 (AR4) model ensemble, we demonstrate that Amazonian temperatures and water stress are both likely to increase over the 21st Century. Curbing deforestation in the Brazilian Amazon by 62% in 2010 relative to the 1990s mean decreased the Brazilian Amazon's deforestation contribution to global land use carbon emissions from 17% in the 1990s and early 2000s to 9% by 2010. Carbon sources in Amazonia are likely to be dominated by climatic impacts allied with forest fires (48.3% relative contribution) during extreme droughts. The current net carbon sink (net biome productivity, NBP) of +0.16 (ranging from +0.11 to +0.21) Pg C year(-1) in the Brazilian Amazon, equivalent to 13.3% of global carbon emissions from land-use change for 2008, can be negated or reversed during drought years [NBP = -0.06 (-0.31 to +0.01) Pg C year(-1) ]. Therefore, reducing forest fires, in addition to reducing deforestation, would be an important measure for minimizing future emissions. Conversely, doubling the current area of secondary forests and avoiding additional removal of primary forests would help the Amazonian gross forest sink to offset approximately 42% of global land-use change emissions. We conclude that a few strategic environmental policy measures are likely to strengthen the Amazonian net carbon sink with global implications. Moreover, these actions could increase the resilience of the net carbon sink to future increases in drought frequency.

Predictive modelling of contagious deforestation in the Brazilian Amazon

Tropical forests are diminishing in extent due primarily to the rapid expansion of agriculture, but the future magnitude and geographical distribution of future tropical deforestation is uncertain. Here, we introduce a dynamic and spatially-explicit model of deforestation that predicts the potential magnitude and spatial pattern of Amazon deforestation. Our model differs from previous models in three ways: (1) it is probabilistic and quantifies uncertainty around predictions and parameters; (2) the overall deforestation rate emerges “bottom up”, as the sum of local-scale deforestation driven by local processes; and (3) deforestation is contagious, such that local deforestation rate increases through time if adjacent locations are deforested. For the scenarios evaluated–pre- and post-PPCDAM (“Plano de Ação para Proteção e Controle do Desmatamento na Amazônia”)–the parameter estimates confirmed that forests near roads and already deforested areas are significantly more likely to be deforested in the near future and less likely in protected areas. Validation tests showed that our model correctly predicted the magnitude and spatial pattern of deforestation that accumulates over time, but that there is very high uncertainty surrounding the exact sequence in which pixels are deforested. The model predicts that under pre-PPCDAM (assuming no change in parameter values due to, for example, changes in government policy), annual deforestation rates would halve between 2050 compared to 2002, although this partly reflects reliance on a static map of the road network. Consistent with other models, under the pre-PPCDAM scenario, states in the south and east of the Brazilian Amazon have a high predicted probability of losing nearly all forest outside of protected areas by 2050. This pattern is less strong in the post-PPCDAM scenario. Contagious spread along roads and through areas lacking formal protection could allow deforestation to reach the core, which is currently experiencing low deforestation rates due to its isolation.

Operationalizing a One Health approach to global health challenges

The One Health approach, which recognizes the interconnectedness of human, animal and ecosystem health, encourages collaboration between diverse disciplines to address complex health problems. The advantages and challenges posed by these interdisciplinary collaborations are described in this review. Learning networks where diverse participants can openly share processes, best practices, and case studies are discussed as a strategy for conducting transdisciplinary One Health research and tackling complex global health problems. The 11 papers in this special issue are also introduced as they illustrate how a One Health approach can be applied to better understand and control zoonotic pathogens, engage community stakeholders in One Health research and utilize wildlife species, most notably sea otters and birds, as sentinels of ecosystem health. Collaboration is rarely without complications; however, drawing on these insights may benefit the process of operationalizing the One Health approach to address today's global health challenges.

A social and ecological assessment of tropical land uses at multiple scales: the Sustainable Amazon Network

Science has a critical role to play in guiding more sustainable development trajectories. Here, we present the Sustainable Amazon Network (Rede Amazônia Sustentável, RAS): a multidisciplinary research initiative involving more than 30 partner organizations working to assess both social and ecological dimensions of land-use sustainability in eastern Brazilian Amazonia. The research approach adopted by RAS offers three advantages for addressing land-use sustainability problems: (i) the collection of synchronized and co-located ecological and socioeconomic data across broad gradients of past and present human use; (ii) a nested sampling design to aid comparison of ecological and socioeconomic conditions associated with different land uses across local, landscape and regional scales; and (iii) a strong engagement with a wide variety of actors and non-research institutions. Here, we elaborate on these key features, and identify the ways in which RAS can help in highlighting those problems in most urgent need of attention, and in guiding improvements in land-use sustainability in Amazonia and elsewhere in the tropics. We also discuss some of the practical lessons, limitations and realities faced during the development of the RAS initiative so far.

Quantifying the impact and relevance of scientific research

Qualitative and quantitative methods are being developed to measure the impacts of research on society, but they suffer from serious drawbacks associated with linking a piece of research to its subsequent impacts. We have developed a method to derive impact scores for individual research publications according to their contribution to answering questions of quantified importance to end users of research. To demonstrate the approach, here we evaluate the impacts of research into means of conserving wild bee populations in the UK. For published papers, there is a weak positive correlation between our impact score and the impact factor of the journal. The process identifies publications that provide high quality evidence relating to issues of strong concern. It can also be used to set future research agendas.