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Paragominas has also witnessed a rapid recent expansion of silviculture mostly Eucalyptus spp.

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Both regions are distinct from the agro-industrial frontier in Mato Grosso which is dominated by large-scale mechanized farming primarily for export [ 32 , 33 ]. Although mechanized farming is expanding rapidly in both study regions, in contrast to Mato Grosso, the majority of properties are less than ha. Moreover, local and regional urban centres still provide significant markets for cattle, and landscapes are interspersed with a diverse array of densely populated small-holder colonies and agrarian reform settlements.

These processes have strong support from non-governmental organizations, farmer's unions and local government, and have facilitated the development of RAS by helping us gain trust with local actors and institutions, tailoring the research planning and design towards local priorities and needs, and increasing receptivity towards project results and recommendations. It is not viable to repeat the scale of assessment of the RAS initiative in every tropical forest region around the world.

However, by working at multiple scales and in two differing municipalities that encompass many characteristics of eastern Amazonia and elsewhere, such as large areas of extensive cattle pasture, emergent mechanized agriculture and a population that is highly mobile and dominated by small-holder farmers, we believe that our results provide a suitable laboratory for better understanding many of the risks and opportunities facing the development of more sustainable landscapes across the wider region. By concentrating our efforts in two regions that have received particular attention from existing initiatives in sustainable land use, our results almost certainly will receive greater exposure to, and engagement with, a wide range of decision makers.

Last, a key focus of our work is to employ our uniquely comparable and diverse datasets to identify a subset of cost-effective ecological and social indicators that can help guide applied research and monitoring work in other study regions. The RAS sampling design is based on a sample of 18 third- or fourth-order hydrological catchments ca ha in each region. Sampling at the catchment scale also permits the integration of terrestrial and aquatic information, and the assessment of changes in ecological and socioeconomic variables that are highly correlated at local scales, such as cumulative deforestation, economic activities and human population density.

The 36 study catchments figure 2 ; electronic supplementary material, figures S1 and S2 were selected to capture the full deforestation gradient, while incorporating priority areas identified by members of the municipal governments and farming communities e. Remote-sensing, socioeconomic and environmental data sampled by the Sustainable Amazon Network. Ecological data were collected from a sample of m study transects in every catchment, distributed using a stratified-random sampling design, where a standard density of transects 1 per ha was distributed across the catchment in proportion to the percentage cover of total forest and production areas encompassing agriculture, pasture, fruiticulture and silviculture; figure 2.

For example, if half of the landscape was covered by forest, then half of the transects were allocated to forest. In catchments with very low levels of forest cover we sampled additional forest transects to ensure a minimum sample of three transects in all catchments. Within each of these two land-use categories forest and non-forest , sample transects were distributed randomly with a minimum separation of m to minimize spatial dependence. The use of this stratified-random sampling design provided a balance between the need for: i proportional sampling of forest and non-forest areas, and a sufficient density and coverage of sample points to capture major differences in landscape structure and composition among different catchments; and ii a well-dispersed set of sampling points across forest and non-forest areas that captured important environmental heterogeneities within each catchment and across the region as a whole, helping to minimize problems of pseudo-replication.

Aquatic sampling was conducted across 50 stream sites, each m long in each region, with samples distributed along a gradient of prior human impact based primarily on the amount of remnant forest cover in the upstream catchment and not constrained to terrestrial study catchments.

Socioeconomic data were collected from all rural properties with an ecological study transect. Owing to the stratified design, transects tended to be in larger properties and under-represent smaller farms. Therefore, we mapped all rural producers in each catchment and sub-sampled a maximum of 20 randomly selected properties with at least 1 ha and producing in Given our focus on the producer community, this sample excluded urban and periurban areas, but could include some of the same farms in the transect-based sample.

This combination of sampling techniques enables us to describe the dominant socioeconomic and demographic characteristics of different producers, and to provide a detailed socioeconomic profile of the farming population in each catchment figure 2. Where rural properties had more than one household e. RAS project members conducted a detailed assessment of ecological and socioeconomic patterns and processes in both study regions between April and August table 1 and figure 2 ; electronic supplementary material.

Choices of sample variables and methods were based on our research priorities, cost-effectiveness and the need to collect a large number of representative samples [ 34 ] table 1. Sampling of terrestrial biodiversity focused on trees and lianas, birds, dung beetles, ants, orchid bees and soil microbes. In a subset of catchments, additional measurements were made of ecosystem functions mediated by beetles and ants including dung burial, seed dispersal and seed predation. Aquatic biodiversity and metrics of aquatic condition consisted of fish and macroinvertebrate assemblages table 1.

Ecosystem service supply was measured for carbon stocks above- and below-ground and the maintenance of soil condition physical and chemical properties. The habitat structure of both terrestrial and aquatic environments was assessed using a combination of measures of canopy openness, vegetation structure, dead wood and leaf litter, and the morphology and substrate of stream channels. Socioeconomic data were collected on the characteristics of study properties such as land cover, legal status and producer households including household demography, producer origins, income, access to services, subjective measures of well-being , costs and productivity of different production systems livestock, arable and perennial crops, silviculture and timber harvesting , fire use and effects, and the benefits and costs of maintaining forest reserves including the extraction of timber and non-timber forest products, and risks of invasion and theft table 1.

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Legacy effects of past human impacts are known to be important for both ecological and social systems, but have been poorly studied to date [ 35 , 36 ]. Remote-sensing analyses were based on a year time series and provide information on changes in land use, forest extent, timing and frequency of forest degradation and age of regeneration see the electronic supplementary material, table S2. These data provide the basis for validating remotely sensed indicators of ecological and land-use change with direct field observations e.

The acquisition of extensive and reliable knowledge about the Amazon is dependent on research networks that can effectively exploit economies of scale in shared resources and technical expertise, recognize and make explicit interconnections and feedbacks among sub-disciplines, and increase the temporal and spatial scale of existing studies [ 22 ]. However, building effective multi-sector and interdisciplinary research programmes at large spatial scales remains one of the most difficult challenges facing sustainability science [ 37 ].

One of the greatest challenges of the RAS project has been developing and maintaining engagement with partners from multiple sectors, institutions, local governments, civil society organizations and farmer associations.

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More than half of the remaining forest in the Amazon lies within private land [ 25 ], and one of the novel aspects of RAS is the collection of data from complex landscapes with multiple owners that encompass a broad spectrum of culture, wealth and education. Establishing contact, building a minimum level of trust, and securing permissions from more than private landowners across the 36 study catchments incurred significant costs in time and resources.

This was especially difficult in areas with a legacy of conflict over deforestation and the exploitation of natural resources. Despite the challenges, most landowners recognized the value of research in strengthening the evidence basis for what are otherwise largely rhetorical and highly politicized debates regarding the effects and drivers of land-use change. The diversity of institutional partners that make up RAS, including local organizations, and those directly concerned with agricultural development and local conservation initiatives, was critically important in building trust.

While the establishment of meaningful partnerships with very different types of landowners including some of the poorest and richest farmers in the study regions was critical for the success of RAS, it was also important to avoid over-promising and over-committing on the benefits to individual land owners from project outcomes.

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Considerable care was taken to manage expectations by distinguishing clearly the purpose of research from rural development and agricultural extension, and presenting realistic timetables for project participation and the dissemination of results. Maintaining a meaningful level of engagement with our network of local partners is critical to help maximize the relevance of our analyses of project data to local sustainability problems [ 23 ]. We are keenly aware that the difficulties inherent in giving adequate attention to the needs and problems facing local communities can increase the chance of drawing inappropriate conservation and development recommendations from our work.

We are wary of presenting and interpreting trade-offs too simply, and we acknowledge that simplified quantitative analyses and narratives that only take account of a limited set of attributes can obscure important dynamics and dimensions of value, often resulting in the marginalization of some interest groups [ 38 ]. Although commonplace in research projects such risks are rarely made explicit.

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Within the RAS research network, we encountered many of the problems faced by other multidisciplinary projects, including the need to overcome differences in values, language and modes of thinking among disciplines [ 22 , 24 ]. There are no easy answers to such challenges, though we have found that co-location of researchers from different disciplines within the same field teams, use of a shared online management platform and group exercises such as participation in conference symposia and writing this paper have all helped promote constructive dialogue.

RAS has its origins in three previously independent research projects that were amalgamated together with more partners and funding sources into a single initiative with shared goals, budget and management structure. While this historical trajectory led inevitably to a more complex funding and communication system, the resulting strong sense of ownership shared by many project members often led to a more open, interactive and democratic decision making process during project planning and execution. Many of the greatest challenges in developing RAS arose from mundane problems of coordinating the collection, processing and analysis of data.

There is a need for continual reassessment of the value and purpose of new measurements or additional samples, and the extent to which more data are necessary to address the priority questions. Cost-effectiveness in time and resources are often ignored in conservation research e. The marginal costs of more field data may appear to be little, but they must take account the costs of laboratory and analysis work, and the transaction costs of managing increasing project complexity.

Work to address our first two objectives is ongoing in many disciplines in RAS to assess and better understand the ecological and socioeconomic consequences of land-use and landscape changes, with synthesis analyses of trade-offs and scenarios scheduled from We hope that the outcomes from RAS can help guide improvements in land-use policy and management in several ways. At the simplest level, the quantification of deleterious trends in valued attributes e. A clearer understanding of spatial patterns of ecological and socioeconomic condition is fundamental for understanding the appropriate locations, scale, starting conditions and potential constraints associated with any future changes in management actions [ 40 ].

Such basic information is still lacking for much of the Amazon region.


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RAS datasets can help reconcile social—ecological objectives and reveal trade-offs between farming and conservation at multiple spatial scales by combining data on socioeconomic and ecological values. One prominent debate concerns the effectiveness of alternative approaches for attempting to balance conservation and agricultural activities through changes in agricultural productivity and farming techniques, often referred to as land-sparing versus land-sharing [ 41 ].

Understanding of this general problem is limited by a lack of data on the conservation value of areas of remaining native vegetation available for conservation investment that are in differing stages of degradation or regeneration, farm-scale differences in agricultural productivity and other socioeconomic variables related to human well-being and poverty, and landscape-scale influences on local ecological and socioeconomic properties. Data and results from RAS ultimately aim to contribute towards more sustainable land-use systems in Amazonia in five overlapping areas, namely the development of: i best practice recommendations for sustainable intensification and responsible agriculture, particularly in the cattle-ranching sector; ii cost-effective approaches to achieving compliance with environmental legislation, especially in Brazilian Forest Law; iii strategies for investment in forest conservation and restoration through payment for ecosystem service schemes, and particularly carbon finance; iv strategies for promoting fire-free agriculture; and v municipal-level ecological—economic zoning processes.

We seek to identify potential opportunities and motivations for more sustainable development strategies in eastern Amazonia and elsewhere by combining the quantitative foundation of our sustainability assessment with input from stakeholders and work in the political and social sciences [ 44 ]. We hope that our data will be helpful to assess how changes in management incentives or regulatory conditions will influence relative ecological and socioeconomic costs and benefits. However, we also recognize that win—win solutions are rare and often misleading. Given this, our work seeks to give explicit consideration to possible conflicts, compromises and synergies among multiple objectives, unexpected interactions and feedbacks, and the broader political and institutional context [ 45 ].

Ensuring that the work being undertaken by RAS goes beyond science and successfully bridges the science—policy divide is both extremely challenging and unpredictable. There are at least three areas where we hope that our approach can help to increase opportunities for informing development and conservation decision makers. First, our interdisciplinary, mesoscale and place-based research approach increases the likelihood that our results are relevant and applicable to regional problems.


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  • Second, we believe that to be most effective the process of knowledge exchange should occur across as broad and diverse set of actors as possible. Here, the participation of such a large group of mostly Brazilian students and researchers on the one hand, with a large and diverse array of non-research partners and associates including conservation organizations, farmers groups, government agencies and individual landowners on the other has provided the basis for multiple ongoing dialogues about our research objectives and preliminary findings.

    Knowledge exchange should not be limited to high-level executive summaries for policy makers but must exploit opportunities for shared learning and dissemination of ideas at all levels. Last, we are developing an impact strategy that can help to target the presentation and discussion of key results through appropriate media to specific audiences and demands at local, regional and national levels.

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    Sustainability science needs to balance the often-conflicting timetables of research and policy processes. As scientists we strive to ensure the reliability, intellectual credit and independence of our work; a process that often requires a lot of time. Sepulchral Monuments of the Jews of msterdam in the 17th and 18th Cent The History of Judaism from the Exile, B. Renaissance Philosophy of Science and the Kabalah as Presented in the A History of the Jews of Egypt in the 16th to 18th Centuries.