Sustainability Assessment of Smallholder Agroforestry Indigenous Farming in the Amazon: A Case Study of Ecuadorian Kichwas

In the Amazon, the Yasuní Biosphere Reserve (YBR) is considered a natural and cultural diversity hotspot. It is populated by several indigenous groups, including the Kichwa, who are characterized by their traditional systems of production, which are a means of subsistence and socio-ecological integration. The objective of this research was to evaluate the sustainability of small farmers who use a traditional agroforestry system (chakra) within the buffer, transition, and core zones of the YBR. We conducted 133 interviews with Kichwa heads of households. The socio-demographic structure and distribution were identified, and the response-inducing sustainability evaluation (RISE) methodology was used to evaluate chakra sustainability according to social, economic, and ecological dimensions, expressed using 10 indicators from 50 parameters, valued from 0 (worst case) to 100 (best case). The results are expressed in a polygon, defined by the areas: (1) good performance, (2) medium performance, and (3) poor performance. We employed the multivariate classification hierarchical cluster technique and analysis of variance (ANOVA) to identify dissimilarities between groups of chakras and the existence of statistical differences, respectively. Among the studied indigenous Kichwas, a pyramidal structure progressive type was identified, which is characteristic of young populations and the nonexistence of significant differences between the RISE indicators and chakras. The lowest-scoring indicators using the RISE guidelines were: use of materials and environmental protection, animal production, economic viability and chakra administration. We provide suggestions for decision makers who support Kichwa populations in socio-productive management with sustainability goals. We to taking actions on the indicators identified with high priority to improve the sustainability in the chakras and sociodemographic dynamics.


Introduction
The biological and cultural richness of the tropics is recognized globally. Worldwide, it is estimated that there are approximately 300 million indigenous people who belong to 5000 different cultures, Development Goals for the period 2000-2015, which only directly affected developing countries. This new agenda is for everyone and for a global world. This means that in the coming years, all political actions and business strategies, and especially private ones, must be aligned with the achievement of those objectives. In the field of agriculture, agricultural and environmental policies will be aligned with the agenda, especially in the field of sustainability. The specific related goals include SDG 15: Life of terrestrial ecosystems, in which the Amazon biome is a main exponent; the scope of SDG 1: End poverty in all its forms; and SDG 2: Zero hunger should be allowed, in coexistence with local populations [43]. Assessing agricultural sustainability is one of these responses. Although capturing the systemic complexity of sustainability through assessment is difficult, it is warranted by the attention of policy makers beyond crop productivity to include dimensions of human well-being and ecological soundness [44,45]. Sustainability is a multidimensional concept [46] of a dignified life for the present without compromising a dignified life for future generations or threatening the natural environment and endangering the global ecosystem [47]; its evaluation is an important process in promoting the concept of sustainable agricultural systems [48,49].
To understand the transition toward more sustainable production, a variety of tools have been developed to obtain information on the sustainability performance of production [50,51]. Indicator-based sustainability assessment tools require the management of a wide variety of information types, parameters, and uncertainties [52], and vary in scope (geographic and sectorial), target group (farmers or policy makers), selection of indicators, aggregation, weighting methods, and time required for their execution [50,51,53]. Although many emphasize the importance of integrating social, economic, and environmental issues into sustainability assessment tools, environmental issues and tools generally receive more attention [50,51,[54][55][56]. The results of sustainability assessment tools should be seen as a starting point for discussion, reflection, and learning [57].
Several tools are available for the evaluation of sustainability based on indicators: farm sustainability indicators (IDEA) [58], sustainability assessment of food and agriculture systems (SAFA) [59], response-inducing sustainability evaluation (RISE) [60], and others [61,62]. The IDEA tool was developed in France in 1998. Its analysis is at the farm level and it represents an approach based on principles; methodological indicators can be added [58]. SAFA is an open process methodology. According to the guidelines of the Food and Agriculture Organization of the United Nations (FAO), it is used as a self-assessment tool for food producers and manufacturers [59]. The justifications for the selection of indicators have been documented, and the integration problems between scales have been considered. It is not possible to add indicators, and the validation of the indicators is based on comparison and expert evaluation [63]. RISE is an easy-to-use tool that covers all dimensions of sustainability [57] and uses principles-based approaches; RISE presents both numerical and graphical results [51]. RISE is the best compared to other tools for sustainability assessment in terms of scientific robustness, feasibility, utility, influence, spatial applicability, and adaptability [52]. RISE has been used in various countries such as Poland, Spain, Kenya, and Canada, and in different evaluation scenarios (Table 1). Sustainability assessment tools can provide support for decision making in production systems and may, therefore, significantly impact their sustainable development [53,72]. The availability and quality of data, time and budget requirements, as well as factors related to unknown terminology and ease of use of use and accessibility of the tool, influence the perception of small producers about the relevance of the tool and, consequently, whether they decide to use it [53,73,74].
In this study, our aim was to assess the sustainability of small farms using the traditional agroforestry system (chakra) in the Ecuadorian Amazon, with the objective of understanding traditional knowledge about the farming system and to explore and discuss possible improvements.

Geographical Location
We focused on the Kichwa populations settled along the Napo River, in the north of the Yasuní Biosphere Reserve (YBR). This indigenous group is the result of inter-ethnic relations with ancestral populations in the area: Quijos, Záparos, Omaguas, Tucanos, Shuar, Achuar, Siona, Secoya, and Highland Kichwas and Peruvian Quechuas [36]. The Kichwa of this region are the most numerous indigenous populations in the EAR (60,000 inhabitants) [37,38]. Those residing in the Yasuní National Park (YNP) present a type of grouping based on associations that cohabit communal territories, associations, and federations [39]. They speak Runa Shimi, a dialect based on Kichwa and Spanish. Their identities are complex and overlap with other indigenous and white settler groups.
The study was conducted in two sectors, A and B, located in the YBR, which is considered one of the areas with the greatest biological and cultural biodiversity on the planet [75][76][77][78], including the YNP, Waorani Ancestral Territory (WAT), Tagaeri Taromenane Intangible Zone (TTIZ), and the Fringe of Diversity and Life (FDL), located in the EAR. Ecuador is 1 of 17 megadiverse countries [79,80] (Figure 1). The YBR was announced by UNESCO in 1989; it is located in the provinces of Orellana (51.96%), Pastaza (39.40%), and Napo (8.64%), between the Napo and Curaray Rivers [81]. The predominant ecosystem is lowland evergreen forest in the Napo-Curaray (BsTa02) [82], the temperature ranges from 24 to 27 • C, rainfall is 3200 mm/year, relative humidity ranges from 80% to 94%, and the soils are relatively young and are generated by fluvial sediments from the erosion of the Andes [83].
Atmosphere 2020, 11,1356 3 of 13 of this limitation, AOD is widely used to examine the role of aerosols on atmospheric phenomena because of a reliable satellite dataset for a long period of time [22,36,37,47,48]. A dataset of monthly precipitation was obtained from the Global Precipitation Climatology Project (GPCP) version 2.3 (https://www.esrl.noaa.gov/psd/data/gridded/data.gpcp.html) for the period 2000-2017 [49]. We analyzed surface net solar radiation (SSRD), 2m surface air temperature (SAT), surface latent heat flux, u-and v-component wind speed, specific humidity, and mean sea level pressure (SLP) from the European Centre for Medium-Range Weather Forecasts interim (ERA-interim) reanalysis monthly data (https://apps.ecmwf.int/datasets/) [50] to estimate their relationship with AA concentration.
To explore the variability of AA concentration in East Asia during the premonsoon season (April-May-June, hereafter, AMJ), we introduced the AOD index defined as an area-averaged AOD in East Asia (110.5-122.5 • E, 22.5-40.5 • N; a green box in Figure 1a). The normalized AOD index during AMJ was also used in the composite analysis to estimate the relationship with other atmospheric variables. The normalized AOD index during AMJ is defined as follows: where µ (AOD index) and σ (AOD index) indicate the time mean of the AOD index and one standard deviation of the AOD index, respectively. We selected the high-and low-AOD years during AMJ based on a 0.75 standard deviation of the

Sampling and Data Collection
In the sectors identified, sampling was performed using the reference chain or snowball methodology [84], given the difficulty of constructing a sampling frame due to the scarcity of demographic information in the intervention zone and the complex logistics for traveling to and mobilization through the communities. This method begins with one interviewee, who gives the researcher the name of at least one other potential interviewee. This interviewee, in turn, provides the name of at least one other potential interviewee, etc., with the sample growing like a rolling snowball if more than one reference is provided per interviewee [85,86]. In the initial phase of the survey, participants expressed their concern that local and international institutions would cut social and agricultural programs due to participation in the study. In this situation, a signed informed consent form was not used, but with the support of the German Agency for Development Cooperation (GIZ-Ecuador), all approaches were made to producers and the principles of ethical research were explicitly applied [87], discussing the objectives, risks, methodology, and schedule of the study with members of each community. One of the pillars of our positive relationship with the participants was the presentation of the results of the questionnaire. The restitution of results is an ethical duty that is often overlooked when conducting research on human beings, especially when indigenous communities participate [88,89].
We studied the Kichwa population structure and its distribution by sex and age from a population pyramid (statistical representation) [90] to examine its implications with traditional production systems [91]. We calculated the following indices: (1) proportion of young population (<14 years) (P young people ); (2) proportion of adult population (between 15 and 64 years, P adults ); (3) ratio of children to women, defined as the number of children under 5 years of age for each woman of reproductive age (R); (4) the ratio of men, consisting of the ratio of men for every 100 women in a given population, considered as the first indicator for analyzing the distribution by sex in the population (R.M.); (5) youth dependency ratio, which is the relationship between the potentially dependent age population (<15 years) and the potentially active age population (between 15 and 64 years, (I t dj ); (6) the structure index of the active age population, which is the relationship between the population from 40 to 64 years and the population from 15 to 39 years (I r ); and (7) the rate of change of the active age population (I t r ), which is the relationship between the population from 60 to 64 years and the population from 15 to 19 years [90][91][92][93][94], as follows:

Assessment of Agricultural Sustainability
The RISE methodology was applied to holistically evaluate the sustainability of the traditional agroforestry system (chakra). The dimensions considered were economic, social, and ecological [95][96][97][98][99], which allowed us to analyze and compare the degree of sustainability between the chakras. This methodological tool is characterized by the balance between the simplicity of the analysis, the complexity of reality and the transparency of the results [60,97]. RISE seeks to create a tangible evaluation based on science that allows for the beginning of the creation of measures to improve sustainability [98,99] and to initiate a constructive dialogue between producers and processors to spread the philosophy of sustainable production [96][97][98]. The methodological process began with an interview of the owner of a chakra. The RISE questionnaire was designed with three types of questions: open, drop-down list, and Boolean. The structural index of the questionnaire was divided into three stages: (A) preparation of the field visit to the chakras, containing general questions; (B) questions for the field visit, containing questions with qualitative and quantitative data that were collected during the RISE interview; and (C) comments, a space where notes can be transcribed about the questions or observations during the visit to the chakra. The duration of the questionnaire was 95 min [98].
For the systematization and analysis of the data of the conglomerate of the communities and the holistic evaluation, we used RISE 3.0 Software [99], developed by the Swiss College of Agriculture (SHL), based on the 10 standard indicators according to 50 parameters (Table 2), valued from 0 (worst case) to 100 (best case). As a result, a sustainability polygon was issued, defined by the following areas: (1) good yield, green coloration (66.66-100); (2) average yield, yellow coloration (33.34-66.65); and (3) bad yield, red coloration (0-33.33). The qualification values in the RISE method are fixed and cannot be changed. The red line superimposed on the polygon indicates the degree of sustainability per indicator, which is based on the arithmetic average of four to seven parameters that have the same weight [98].  Each indicator contains parameters that describe the state of the system (S) and the driving force (D) within the system, leading it in a certain direction of development. S indicates the current condition of each specific indicator, and D is a measure of estimated pressure exerted by the agricultural system on the specific indicator [60]. The state parameters have a value between 0 (worst case) and 100 (best case). The driving force parameters are also calculated using a range of 0 to 100, but since they are valued as a negative pressure in the system, 0 represents the best case and 100 the worst case (the highest pressure).
The degree of sustainability (DS) is calculated as the difference between the state (S) and the driving force (D); DS = S-D ( Figure 2). Considering the S and D parameters not only allows for the creation of a static picture of the current situation; it reveals the development trends of the system. Therefore, the RISE evaluation provided an analytical snapshot of the chakra situation while describing some aspects of the dynamics that change the system over time. The assessment of the driving force allowed us to understand and highlight the trends and threats that can be decisive for the concept of operational sustainability.

Hierarchical Cluster Analysis
The statistical analysis was conducted using the multivariate classification hierarchical cluster technique. This is a mathematical method that is included in multivariate statistics. Multivariate analysis is the branch of statistical analysis that studies, analyzes, represents, and interprets the data resulting from the observation of p > 1 statistical variables on a sample of n individuals. It focuses on the simultaneous investigation of two or more characteristics (variables), measured on a set of individuals [100]. Hierarchical cluster analysis is mainly used for the formation of groups starting with the basic unit of the objective (BUO), according to the similar characteristics from the similarities or dissimilarities that are presented between pairs of these BUOs in the evaluated characteristics [101]. The hierarchical methodology deals with the grouping of clusters to form a new group, starting with groups as existing individuals in the study and grouping them to form all the cases in the same group [102].
All the sustainability variables defined by the RISE evaluation framework were used, applying the Euclidean squared distance as a similarity criterion, which is a measurement that is affected by the differences in metrics between the variables [100]. It is a measurement of dissimilarity: its minimum value is 0, but it has no maximum value [101]. We also employed the Ward grouping method for hierarchically forming the groups and agglomerates by minimizing the intra-group variation. It tends to generate small but very balanced conglomerates [103] and, at each step of the agglomeration process, uses the distance between classes that meets the objective of joining [104,105].
The data were organized in an Excel spreadsheet (version 19.0, Microsoft, Redmond, United States), using the SPSS version 22 statistical software (IBM, Armonk, United States) [106] to evidence the history of clusters, where the groups to be formed were selected according to the dissimilarity index. The resulting dendrograms are presented for analysis of the sectors in an individual and united way according to the owner of the chakra and analysis of variance (ANOVA) was used to identify the existence of significant differences (0.05) between groups of means.

Sociodemographic and Agricultural Characterization
The Kichwa population in the study area was 48.5% men and 51.5% women (726 total). The average age for men was 27 years and the average for women was 29. The proportion of young men was 17.7% and women, 22.8%; adult men comprised 30.7% and women, 28.6% (Figure 3). The ratio of children to women was 0.45%, while the ratio of men was 48%. The youth dependency index was 68%, the structural index of the working age population was 40%, and the rate of change of the working age population was 4%.
The following pattern was found in the evaluated sites: in sector A, the household composition varied between four and six people. In this sector, the Pompeya and Itaya communities reported at least one household with 10 individuals. In sector B, the household composition ranged from four to seven (Table 3) and the Sinchi Chicta Cari community reported a household with 11 individuals. The average household size in the communities studied was five individuals.
The average age of the heads of household was 42 years. The youngest head of the household (25 years) lived in the Sinchi Chicta Cari community. The youngest age range was between 25 and 34 years. In the communities of Pompeya, Chiru Isla, and San Vicente resides, the oldest head of the household was 60 years. The oldest age ranged from 44 to 60 years.
In the communities of Pompeya and Chiru Isla EL 8.57% and 3.23%, respectively, completed the third level of education. In Itaya and San Vicente, 8.33% of the heads of household entered the third level of education but had not finished it. In sectors A and B, 19 (31.31%) and 28 (38.24%) heads of household had completed secondary education, respectively; in sectors A and B, 43 and 32 heads of household had completed basic education, respectively.
With regards to land tenure, of the 133 heads of household surveyed, 88% (117 Kichwa indigenous) had deeds (legal land tenure) to their chakras. In the community of Santa Elena (sector A), all had deeds, whereas in the Chiru Isla community (sector B), 23% did not have legal documentation for their land. On average in sectors A and B, 4% and 8% of the chakra owners, respectively, did not have deeds to their lands.

Values in Sector A
Using the indicators resulting from the evaluation of the sustainability of traditional agroforestry systems (chakra) in sector A using hierarchical cluster analysis, three groups were obtained in a dendrogram ( Figure 4) with a Euclidean distance (measurement of association): in groups 1 and 2, we gathered 24 chakras; in group 3, there were 13 chakras.
In the three groups (Table 4)   The overall sustainability indicator in the three groups was medium. The best score was obtained in group 3, whose differences between group 2 and group 1 were 1.52 and 2.41, respectively. Sustainability dynamics by group and color were blue for group 1, orange for group 2, and red for group 3 ( Figure 5).

Values in Sector B
Similarly, the results of the chakras in sector B were obtained and grouped into a dendrogram ( Figure 6) with a Euclidean distance (measurement of association) of 14. Three groups were obtained: in group 1, there were 21 chakras; group 2 had 24; and group 3 had 27. The indicators with good performance (Table 5) from highest to lowest average scores in the three groups were: energy and climate (92.39), water use (80.18), working conditions (75.57), and land use (67.23). The Bbodiversity indicator in group 1 had 2.68 points more than in group 2; the quality of life indicator in group 3 had 12.52 and 7.9 points more than groups 1 and 2, respectively. The indicators with medium performance were: Animal production, which had an average of 37.90 in the three groups; use of materials and environmental protection in group 1 was 15.78 and 14.17 points higher than groups 2 and 3, respectively. In group 3, biodiversity had 4.53 and 1.85 fewer points than groups 1 and 2, respectively. The quality of life indicator in group 2 was 4.62 points higher than group 1, and in management, group 3 had the best score with a difference of 8.48 and 6.12 from groups 1 and 2, respectively. The lowest performing indicators were: economic viability in all three groups, having an average of 29.81. Group 1 had the best score with 5.05 and 2.82 more points than groups 2 and 3, respectively. Materials use and environmental protection was 1.61 points higher in group 3 than in group 2, and management was higher in group 2 than group 1 by 2.36 points. ** There were no significant statistical differences between the evaluated groups.
The overall sustainability indicator in all three groups was medium, with the best score being in group 1, which was 2.11 and 0.34 higher than in groups 2 and 3, respectively. The dynamics of the degree of sustainability by groups and color were blue for group 1, orange for group 2, and red for group 3 (Figure 7).

Discussion
The two aspects that were studied in this research: (1) the population and agricultural dynamics of the Kichwa population, and (2) the indicators of the evaluation of sustainability in the chakras. The maximum size per Kichwa household was 11 people, and of the heads of households, approximately 21% had no educational. In terms of sustainability, the chakras did not present significant differences, although only 5 of the 10 analyzed indicators showed good performance, and the economic viability and administration indicators were performing poorly.

Socio-Demographic and Agricultural Characterization of the Indigenous Kichwa Population
Currently, defining who counts as a resident of the communities is difficult because many young people often come into and out of the study area, mainly for education and marriage, which is a typical dynamic of indigenous people in the north of the Ecuadorian Amazon [107]. Therefore, we describe the socio-demographic characteristics of the population interviewed in 2018. Figure 3 shows that there was little difference (3.03%) in the population proportion of Kichwa men and women (48.48 and 51.51%, respectively). The proportions of youth and adults were 40.63% and 59.37%, respectively. The ratio of Kichwa children to women (0.45%) was much lower than that of Waorani (0.91%) and Shuar (0.98%) indigenous women [108]. The youth dependency population was 28% higher than the working age population, which corroborates the high birth rates in indigenous populations [109]. In the 40-64-year age range (birth year from 1978 to 1958), only 17.1% of the indigenous Kichwa population is of working age; this value may be influenced by migratory processes [107].
The maximum number of people per household (Table 3) ranged between 7 and 11 members including two parents, which is probably related to higher fertility rates [80] driven by the lack of access to family planning and reproductive health services among indigenous peoples in the Amazon [110][111][112]. Although it has been debated whether the high fertility among indigenous populations is linked to pronatalism and the desire to repopulate indigenous lands [113][114][115], the rapid changes in the northern Amazon region have had profound impacts on the demographic dynamics of local indigenous people, including changing patterns of settlement and livelihood strategies, and increasing interactions with markets [116][117][118][119][120][121][122].
The heads of household did not complete higher education, despite starting their higher studies; 35.34% (sector A) and 56.39% (sector B) of the heads of household had completed secondary and basic education, respectively. In the Northern Amazon region of Ecuador, the most educated households are likely to have higher non-agricultural incomes than the least educated households in mostly migrant settler populations [120,121]. Participation in non-agricultural employment may be driven by push factors such as declining soil fertility, low yields, small production areas, and isolation from markets, which negatively affect farm income [122,123].

Evaluation of Sustainability Based on the RISE Methodology
According to the ANOVA using the results of the RISE, we found no significant differences between groups and sectors evaluated in the northeast of the YBR. The RISE tool, compared with other frameworks for the evaluation of sustainability, produced the best results in some categories such as scientific soundness, usefulness, adaptability, etc. [52], but it lacks a cultural approach based on the location, which can be detrimental to the communities under evaluation [123,124]. Biocultural approaches are those that start explicitly with and are based on cultural perspectives on the basis of the place and the embodied values, knowledge and needs, and recognize the feedback between the ecological state and human well-being [125,126]. These approaches, in combination with the guidelines of the different sustainability assessment tools, can be used to develop indicators to more accurately depict reality [127]. The exchange between in situ and ex situ actors facilitates the identification of crucial problems and solutions that are currently lacking in many regional and international sustainability tools [126,128,129].
The indigenous populations in this zone are associated with sustainable agricultural practices [130] that have little environmental impact and are compatible with resource conservation [47,131]. This is corroborated by the excellent scores for land use and water use within the Kichwa chakra dynamics, similar to the Shumahuani people (Peruvian Amazon), who keep most of their land in the forest and use sustainable management practices in contrast to the migrant settlers who cut down the forest to establish pastures [132]. In the Ecuadorian Amazon Region, most soils are not suitable for agriculture [133,134] and the settlers tended to compensate for the low fertility by clearing more land for cultivation. As a consequence, deforestation rates in the Ecuadorian Amazon Region are considered one of the highest in the world [135].
Chakras are complex systems that adapt to and resist the effects of climate change and development [104,105], have high structural complexity [136,137], and present high levels of carbon sequestration [28] and tree diversity [30] compared with other forms of land use. Chakras also allow for the sustainable use of forests by combining the cultivation of fine and aromatic Ecuadorian cocoa, controlled wood extraction, production of basic food items, and the conservation of medicinal plants. In Amazonian communities, chakras contribute to food security as well as to the well-being and conservation of the region's high biodiversity [28]. The adequate management of the chakras increases their potential to recover part of the carbon released into the atmosphere due to deforestation [138]. This is contrary to the circumstances in the evaluated chakras, since the indicator for use of materials and environmental protection had critical and average scores, influenced by the poor management of the chakra: (1) nitrogen and phosphorus balance, (2) ammonia emissions, and (3) waste management [63,100,101], as the sustainability objective of the indicator is the use of natural cycles [97]. Inadequate waste management can endanger human, animal, and environmental health. Inherited pollution from oil activity can also harm future generations and, therefore, violates the principle of sustainability [139]., which is influenced by the non-agricultural income received from providing unskilled labor services to oil companies, as well as external assistance from the government and international non-governmental organizations (NGOs). All this results in the chakras not being adequately cared for [140].
The Kichwa people obtain their livelihood mainly from subsistence agriculture, collection of forestry products, hunting, and fishing [141,142], all of which are related to the diversity of species in the chakras, but it had a critical score within the biodiversity indicator [56,57]. Scientific evidence shows that some Kichwa have adopted migrant-settler-style agricultural systems and engage in commercial agriculture, such as cattle ranching, logging, and off-farm wage employment in areas near roads and urban centers [23][24][25]143,144]. The integration of Kichwas into the market economy has received attention in the literature because of its implications for both human well-being and ecological viability. Animal production has often been driven by oil companies and embodied in livestock breeding projects [145], which justifies the low values in the animal production indicator, since it is not part of the socio-productive dynamics of the Kichwa people.
In terms of quality of life, the studied Kichwa population received outstanding and medium scores; the best scores were expressed in the parameters of social relations and personal freedom and values; the worst score was in the parameter of health [95][96][97]. Notably, the studied Kichwa population lives in an area overlapped by oil blocks, and in the period from 2001 to 2011, 464 accidental oil spills were registered [146], resulting in a high level of environmental contamination [147]. In 2018, the presence of 1-hydroxypyrene (1-OHP) and creatinine (chemical products from oil activities) was confirmed in the urine of Kichwa indigenous people (inhabitants of the banks of the Napo River) due to the consumption of contaminated food. In addition, the toxicity of drinking water has been revealed, which has caused health problems ranging from dizziness to cancer [148][149][150]. Within the excellent scores of the working conditions indicator in the chakras, an average score was received for the staff management parameter. An important variable of this parameter is child and adolescent work in the RISE methodology, as established by the Universal Declaration of Human Rights [151], understanding that the RISE guidelines do not consider underage work. This stands in opposition to the Kichwan cultural dynamics in the management of the chakras since, from a social perspective, it is the result of a set of values, deeply ingrained in the Kichwa cosmovision [51], where ancestral knowledge is transmitted from generation to generation through harmonious relationships, based on solidarity and reciprocity [152]. The contributions of indigenous and local knowledge (ILK) to research is increasingly considered in the science of sustainability [153,154]. ILK is defined as a cumulative body of knowledge, practices, and beliefs that have evolved through processes of adaptation and are transmitted from generation to generation by cultural transmission, through the relationship of living beings (including humans) with each other and with their environment [155][156][157]. The precarious economic viability and management of the chakras, which have both been obtained, make it more likely that timber will be sold illegally and that income will be earned outside the farm [158]. Given the dynamic evidence for each group in each sector, there is a need to integrate and promote new economic models and reconfigurations of the territory, which may involve changes in governance systems that generate an integration of essential indigenous rules that positively influence chakra management [159].
The sustainability assessments in the Kichwa chakras showed certain problems related to the dimensions of the RISE methodology, which must be resolved to improve the level of sustainability. There are priorities (high, medium, and low) for the management of the territory that could be adopted by local political agents to support the Kichwa populations and to strengthen the studied indicators (Table 6). Promote talks and courses to improve health conditions in the family.

3.
Promote sustainable behavior workshop based on scientific evidence.

Indicators Recommendation Examples Priority
Economic viability 1.
Develop revenues from projects for reducing emissions from deforestation and degradation (REDD+).

2.
Generate opportunities to create marketing chains 3.
Promote the diversification of economic income. [143,177,179] High Administration of the traditional agroforestry system (Chakra) 1.
Encourage the strengthening of field schools for potential of the traditional agroforestry system (chakra) administration. 2.
Identify model chakras for training processes 3.
Help Kichwa people access information 4.
Strengthen capacities to increase strategic alliances among Kichwa people 5.
Identify opportunities for proposing biodiversity conservation areas to generate another type of economic income, e.g., sustainable agro-ecotourism 6.

Conclusions
The average degree of sustainability of the studied Kichwa chakras had a medium score for both sectors. In general terms, we argue that the Kichwa chakras located along the banks of the Napo River have certain weaknesses for the following indicators based on the RISE guidelines: use of materials and environmental protection, animal production, economic viability, and administration of the traditional chakra system. Given the very low values for the economic indicators and for administration in the traditional agroforestry system (chakras), losses are generated compared to the neocolonial models belonging to the migrant settlers and potential structural changes in the landscape agroforestry. However, we also identified strengths in the following indicators: energy and climate, water use, working conditions, biodiversity, land use, and quality of life.
The holistic evaluation of the chakras' sustainability using the RISE tool provides a system of early warning and can be used to help identify potential measures to improve the situation of the indigenous Kichwa people in the Yasuní Biosphere Reserve. In addition, the results provide a scientific basis for the people in charge of formulating public policies to improve strategies for the rescue and management of the chakras. Consequently, this would improve quality of life, strengthen food security and sovereignty, bolster self-employment, and increase the production of sustainable products among Kichwa populations in the Ecuadorian Amazon region.
Although the RISE methodology was not designed to be used as an instrument of certification, it could offer additional value for some process of certification, for example, organic certification of the chakras, conservation of the biodiversity of species in productive spaces, and so on.

Acknowledgments:
We would like to thank the German Development Cooperation Agency (GIZ-Ecuador) for their collaboration in the field logistics. We are also grateful to the Yasuní National Park rangers for their help during the data collection, as well as the 133 Kichwa households who shared valuable information with us during the visits about their socio-demographic characteristics and chakra production systems.

Conflicts of Interest:
The authors declare no conflict of interest.