Harnessing Insights from Indicators-Based Resilience Assessment for Enhancing Sustainability in the Gurage Socio-Ecological Production Landscape of Ethiopia

Abstract

Even though the mosaic of different land-use/land-cover types has long contributed to the resilience of socio-ecological production landscapes and seascapes in Ethiopia, recent data indicate that their sustainability is under threat. This study aims to evaluate landscape resilience by adopting a set of indicators for enhancing sustainability in the Gurage socio-ecological production landscape in Ethiopia. The authors employed a toolkit of indicators in the production landscape through a community-based scoring approach (1–5 Likert scale). The information from household surveys, land-use/land-cover analysis, and satellite-based drought incidents assessment was integrated with the ranking analysis to support the evaluations. The results revealed that landscape diversity, ecosystem protection, local governance, and social equity indicators had the highest landscape resilience ranks. In contrast, lower ranks are associated with knowledge, innovation, livelihoods, and well-being indicators. The overall resilience of the Gurage socio-ecological production landscape was estimated to be below average. Thus, strategies that enhance the resilience and sustainability of this socio-ecological landscape are essential. The findings could help draw the attention of policymakers and natural resource managers to building and strengthening the resilience of the landscape. This study demonstrates that indicators could aid in evaluating landscape resilience status along with other ancillary information, particularly in data-sparse regions. Methods of assessing resilience must be creative in such regions, and this paper may inform such efforts. In addition, the study recommends that landscape resilience indicators be improved by reducing subjective matter and including spatial-explicit dimensions for evaluating resilience.

Introduction

In the course of human history, local communities throughout the world have created and sustainably managed diverse landscapes by adapting and benefiting from their surrounding environment (Ellis et al. 2021). Such landscapes include socio-ecological production landscapes and seascapes (SEPLS), which are dynamic mosaics of natural and human-induced land uses that have long been shaped over time (Saito et al. 2020). People and nature interact closely in these landscapes and contribute to maintaining biodiversity and producing goods and services (Duraiappah et al. 2012). Moreover, these landscapes comprise ecological and social systems that provide essential ecosystem services to society (Binder et al. 2013).

The socio-ecological systems are often subject to unprecedented changes (Rockström et al. 2009). Building adaptive capacity in socio-ecological systems is necessary for sustainability to react to the changes now and in the future (Price 2003; Rodríguez et al. 2018). Emergency response agencies, non-governmental organizations, and several others have been working tirelessly to secure lives in response to increasing environmental threats (Ward et al. 2017; Marchese et al. 2018). These efforts have increased interest in developing resilience and sustainability frameworks (Redman 2014). Resilience thinking provides a sustainable analytical framework for operating socio-ecological systems at various spatiotemporal scales (Folke 2016).

In the field of interdisciplinary sciences, resilience is employed to emphasize the functioning of a landscape that involves interlinked or coupled systems of people and nature, which is essential to the health of ecosystems, human well-being, and resource equitability (Walker and Salt 2006; Nelson et al. 2007; Ciftcioglu 2017). The response of systems (including environmental, social, and economic systems) to severe disturbances and persistent stress is the focus of resilience (Folke et al. 2016). Simultaneously, sustainability emphasizes improving the quality of life for current and future generations in terms of environmental, social, and economic aspects (Collier et al. 2013). Because of this joint focus on system survivability, sustainability and resilience share common research methodologies, such as life-cycle analysis, structural analysis, and socioeconomic analysis (Bocchini et al. 2014; Marchese et al. 2018).

Resilience is a vital foundation principle of biodiversity strategies (McDonald et al. 2016). Significant efforts are underway to improve the resilience of biodiversity and ecological function in the face of extreme events and directional change across all landscapes, from intact natural systems to highly modified landscapes such as cities and agricultural regions (Beller et al. 2019). The concept of resilience is increasingly embedded in global, regional, and national development policy (Brown 2015). For example, Aichi Biodiversity Target 15 of the CBD commits signatory countries to take action so that by 2020 “ecosystem resilience and the contribution of biodiversity to carbon stocks has been enhanced, through conservation and restoration” (CBD 2010).

Research on complex socio-ecological systems provides a valuable lens for moving forward with more dynamic and systemic monitoring systems (Selomane et al. 2019). Despite significant improvements in data availability over the last decade, there are still significant gaps in the supply of reliable, timely, and actionable information that could be applied to inform policies (Fraisl et al. 2020). Combining many types of knowledge can help researchers, stakeholders, and policymakers better understand socio-ecological systems and manage them sustainably (Sterling et al. 2017). Incorporating the knowledge and wisdom of local users and interest groups and understanding ecosystem dynamics are crucial for managing socio-ecological resilience. Linking top-down and bottom-up approaches contributes to complementarity and thus fits between locally-based monitoring most relevant to decision-makers and community planners and large-scale observations (Eicken et al. 2021). Linking these approaches could also effectively transition scientist-driven research observations into operational monitoring programs that inform action and contribute to sustaining observing and monitoring efforts over time (Danielsen et al. 2021)

Evaluation tools such as “Toolkits for indicators of resilience in SEPLS” are essential for depicting a complex environmental phenomenon and can be utilized to assess resilience from a local perspective (United Nations University Institute for the Advanced Study of Sustainability (UNU-IAS), Bioversity International, Institute for Global Environmental Strategies (IGES), and United Nations Development Program (UNDP) 2018; Sterling et al. 2017). Such evaluation tools are also helpful for assessing environmental conditions or providing an early warning signal of environmental changes (Ciftcioglu 2017). They could aid in gaining the attention of policymakers and natural resource managers to build and strengthen the resilience of SEPLS.

Large numbers of people on the African continent live in rural landscapes close to nature, where the socio-ecological systems support human well-being and development (Parrott and Meyer 2012). These landscapes are found in various countries, including Ethiopia, and are hotspots for biodiversity. According to Moran and Kanemoto (2017), Ethiopia is one of the hotspots for species threats from global supply chains, particularly related to the consumption footprint of the European Union. One example of the interaction between humans and nature is the Gurage socio-ecological production landscape in Ethiopia, where people reside in village settlements according to ecological conditions (Sahle and Saito 2021a). Natural and plantation forests, sacred forests, home garden agroforests, cereal crops, grasslands, woodlots, wetlands, surface water, Jefoure roads, and human settlements make up the Gurage socio-ecological production system, characterized as a mosaic landscape (Sahle et al. 2021a, b). The Jefoure roads are grass-covered, and the long, wide streets run through the middle of Gurage villages, creating a resilient landscape in the present and past (Sahle and Saito 2021b). Households have backyards, incorporating a home garden agroforestry system often with enset, the staple food crop in the region, alongside other perennial and annual crops (Sahle et al. 2022).

Even though the mosaic of different land uses has long contributed to the resilience of the Gurage socio-ecological landscape, recent data indicates that the sustainability of the landscape is at risk (Sahle and Yeshitela 2018; Aneseyee et al. 2020a, b). Agricultural production in the Gurage socio-ecological landscape is predominantly rain-fed and is thus susceptible to climate change and extreme events (Sahle et al. 2019; Dendir and Simane 2019; Yirga 2021). Moreover, there is pressure on natural resources due to population growth and traditional agricultural practices, likely leading to deforestation and land degradation (Sahle and Yeshitela 2018; Sahle et al. 2018).

Landscape resilience requires proper management that secures the capacity of ecosystems to sustain societal development and ensures progress with essential ecosystem services. In changing socio-ecological systems such as the Gurage socio-ecological production landscape, resilience assessment would help understand a landscape’s overall performance, identify hotspots, and draw strategies for biodiversity conservation, sustainable agricultural production, and livelihood development. This study aims to analyze the resilience status of the Gurage socio-ecological landscape using resilience indicators by engaging the local community and other stakeholders to establish a strategy for sustainable landscape management.

Materials and Methods

Resilience Assessment Approaches

Overview of resilience assessment approaches

Resilience assessment indicators are strategic tools to measure and evaluate changes in landscape systems (Ciftcioglu 2017). Since the turn of the century, several resilience assessment approaches have been developed to operationalize this idea and reduce uncertainties (Peacock et al. 2010; Dakos et al. 2015; Sharifi 2016; Doorn 2017; Walpole et al. 2021). A critical analysis of 36 selected community resilience assessment tools is provided by Sharifi (2016). This review indicates that the assessment tools addressing many facets of resilience, taking into account cross-scale linkages, capturing temporal dynamism, dealing with uncertainties, utilizing participatory ways, and creating action plans are a few of these. Similarly, the National Institute of Standards and Technology identified 56 frameworks and methods for assessing community resilience for the resilience indicator inventory (Walpole et al. 2021). Each tool and framework lists a different amount of indications. For instance, Scherzer et al. (2019), following Susan et al. (2014), employed 47 indicators while adhering to the methodology described by the Baseline Resilience Indicators for Communities in Norway. By creating a similarity matrix, Assarkhaniki et al. (2020) compared the resilience characteristics that have been commonly discussed in the literature with the periphery dimensions. The main components include social, economic, institutional, infrastructural, and environmental resilience. However, the majority of assessment tools are designed for usage in urban or pre-urban settings, and it is uncommon to find assessment frameworks or methods that address all aspects of resilience in cultural or socio-ecological landscapes or seascapes environments (Sharifi 2016; Ciftcioglu 2017; Scherzer et al. 2019; Abelson et al. 2022). Because SEPLS are complex systems, they should be studied utilizing as many factors as is practical (Ciftcioglu 2017).

Toolkit for indicators of resilience in socio-ecological production landscapes and seascapes

The “Toolkit for Indicators of Resilience in SEPLS” is among the resilience assessment tools and has a set of 20 indicators for communities to assess the socio-ecological resilience of the production landscapes and seascapes at the local scale on which they rely for their livelihoods and well-being (Bergamini et al. 2013). It was developed jointly by Bioversity International, UNU-IAS, IGES, and UNDP under the International Satoyama Initiative (UNU-IAS, Bioversity International, IGES, and UNDP 2014). The Toolkit for Indicators of Resilience in SEPLS is designed for communities to develop projects supporting the various benefits of managing biodiversity within their traditional production systems (Bergamini et al. 2013). The indicators intended to facilitate communication between local communities and “outsiders” by providing a common framework for assessing resilience and exchanging information across SEPLS (Dublin and Natori 2020). In addition, the indicators anticipated for supporting researchers, conservationists, and development agencies to identify hotspot areas where support could be provided to community-based management and adaptation to increase resilience and welfare benefits in critical biocultural landscapes (Bergamini et al. 2013). In accordance with the Toolkit for Indicators of Resilience in SEPLS, Ciftcioglu (2017) created appropriate resilience assessment indicators for the SEPLS of the Lefke Region in Cyprus. We took the toolkit for indicators of resilience in SEPLS into account the indicators for our case study’s socio-ecological landscape by tailoring the tools to the situation because obtaining methodologically well-defined instruments for SEPLS is difficult.

In addition to the toolkit for indicators of resilience in SEPLS, a complementing indicator called City Biodiversity Index (CBI) is available, focusing on urban areas (Kohsaka et al. 2013). The CBI, also known as the Singapore Index on Cities’ Biodiversity, is a tool designed to allow cities to monitor and evaluate their progress and performance related to conserving and enhancing biodiversity and ecosystem services (Kohsaka et al. 2013, Elmqvist et al. 2013). However, because this study case site is dominated by the agricultural landscape and the urban coverage area is minimal, we have not focused on the CBI indicators.

The 20 sets of the toolkit for indicators of resilience in SEPLS work to assess the essential resilience attributes of the target SEPLS collectively and are divided into five categories: (1) landscape/seascape biodiversity and ecosystem protection; (2) biodiversity (including agricultural biodiversity); (3) knowledge and innovation; (4) governance and social equity; and (5) livelihoods and well-being (UNU-IAS, Bioversity International, IGES and UNDP 2014) (Table 1). These indicators are initially intended to be used for assessment by individual participants at the workshop first and then collectively among all participants, on a scale from 1–5, with one meaning the situation is least likely to be conducive to resilience and five indicating the most favorable situation.

Table 1.

List of indicators of resilience in SEPLS (UNU-IAS, Bioversity International, IGES and UNDP 2014)

Indicators	Sub-indicators	Questions for scoring
Landscape/seascape diversity and ecosystem protection	(1) Landscape/seascape diversity	Is the landscape/seascape composed of diverse natural ecosystems (terrestrial and aquatic) and land uses?
	(2) Ecosystem protection	Are there areas in the landscape or seascape where ecosystems are protected under formal or informal forms of protection?
	(3) Ecological interactions between different components of the landscape/seascape	Are ecological interactions between different components of the landscape or seascape considered while managing natural resources?
	(4) Recovery and regeneration of the landscape/seascape	Does the landscape or seascape have the ability to recover and regenerate after extreme environmental shocks?
Biodiversity (including agricultural biodiversity)	(5) Diversity of local food system	Does the community consume a diversity of locally-produced food?
	(6) Maintenance and use of local crop varieties and animal breeds	Are different local crops, varieties and animal breeds conserved and used in the community?
	(7) Sustainable management of common resources	Are common resources managed sustainably?
Knowledge and innovation	(8) Innovation in agriculture and conservation practices	Does the community develop, improve and adopt new agricultural, fisheries, forestry, and conservation practices and/or revitalize traditional ones to adapt to changing conditions, including climate change?
	(9) Traditional knowledge related to biodiversity	Are local knowledge and cultural traditions related to biodiversity transmitted from elders and parents to young people in the community?
	(10) Documentation of biodiversity-associated knowledge	Is agricultural biodiversity, and associated knowledge documented
	(11) Women’s knowledge	Are women’s knowledge, experiences and skills recognized and respected at household, community and landscape levels?
Governance and social equity	(12) Rights in relation to land/water and other natural resource management	Does the community have customary and/or formally recognized rights over land, (seasonal) pastures, water and natural resources?
	(13) Community-based landscape/seascape governance	Is there a multistakeholder landscape/seascape platform or institution able to effectively plan and manage landscape resources?
	(14) Social capital in the form of cooperation across the landscape/seascape	Is there connection, coordination and cooperation within and between communities for the management of natural resources?
	(15) Social equity (including gender equity)	Is access to opportunities and resources fair and equitable for all community members, including women, at household, community and landscape level?
Livelihoods and well-being	(16) Socioeconomic infrastructure	Is the socioeconomic infrastructure adequate for the needs of the community?
	(17) Human health and environmental conditions	What is the general health situation of local people also considering the prevailing environmental conditions?
	(18) Income diversity	Are households in the community involved in a variety of sustainable, income-generating activities?
	(19) Biodiversity-based livelihoods	Does the community develop innovative use of the local biodiversity for its livelihoods?
	(20) Socio-ecological mobility	Are households and communities able to move around between different production activities and locations as necessary?

Research-based policy and action to address complex environmental issues could be developed by incorporating local viewpoints and values into global indicator development efforts (Yang et al. 2020). The Indicators of Resilience in SEPLS were developed to be utilized with local communities instead of higher-level national- and global-scale indicators (UNU-IAS, Bioversity International, IGES, and UNDP 2014). The indicators can be adaptable in the selection and use through local engagement in light of regional circumstances and requirements (Nishi et al. 2022).

The evaluation is based on opinions and firsthand local community knowledge (Bergamini et al. 2013). Depending on the circumstances of each unique landscape or seascape and the communities they are related to, it is possible to choose indications from the entire set (Yang et al. 2020). The approach promoted community participation in decision-making and adaptive landscape management (Dublin and Natori 2020). The indicators let stakeholders communicate in a common language and improve knowledge of how people and nature interact (Lee and Yan 2019). The 20 indicators’ dimensions assist the assessment of institutional, socioeconomic, and ecological SEPLS situations and can be used to develop sustainable landscape strategies.

The toolkit for indicators of resilience in SEPLS has been used in more than 40 countries to assess SEPLS resilience and to monitor and evaluate project interventions on resilience and biodiversity conservation (Dublin and Natori 2020; Dunbar et al. 2020). In order to examine the use of resilience assessment workshops as a biocultural strategy for conservation management in Xinshe SEPLS (Taiwan), Lee et al. (2020) took into consideration this indicator. Additionally, in Yanuo Village (China), a plan for the sustainable management of landscapes has been developed in collaboration with the local community using the indicators of resilience in SEPLS (Yang et al. 2020). Lee and Yan (2019) examine the process and outcomes of an indigenous rice paddy cultural landscape through collaborative planning and participatory monitoring by considering the toolkit indicators in Taiwan. These studies considered the toolkits by adapting indicators according to the landscape and socioeconomic context.

Case Study Landscape

The Gurage socio-ecological landscape is situated in south-central Ethiopia, ~110 or 155 km southwest of the capital, Addis Ababa (Fig. 1), covering an area of 5932 km². The Awash River basin borders the Gurage socio-ecological production landscape to the north, the Gibe River (a large tributary of the Omo–Gibe basin) to the southwest, the Rift Valley basin to the east, and the Bilate River catchment to the south. The landscape is semi-mountainous, with elevations ranging from 968 m to 3593 m above sea level (a.s.l) (Fig. 1). The topography of the region is separated into three categories. The mountainous highland is represented by the Gurage Mountain chain that divides the landscape from east to west, with the highest peak at 3593 m a.s.l. Much of the central region is formed by plateau flatlands, with elevations ranging from 1500 to 3000 m a.s.l. The lowest area, the western fringes of the Wabe–Gibe valley, has an elevation from 968 to 1500 m a.s.l. The elevation differences cause diverse climatic conditions with warm-humid, tepid-humid, and cool-moist conditions in different landscape parts. The agroecological pattern follows the rainfall distribution, ranging from 700 to 1600 mm annually. Large parts of the landscape are covered with a terrestrial ecosystem except for small lakes in the highlands.

Fig. 1.

Location map of the Gurage socio-ecological production landscape in southern Ethiopia. The dots indicate the sample villages employed for evaluating the resilience of the landscape. (Source: Compiled by the authors based on the shapefiles obtained from the Central Statistical Agency of Ethiopia (district boundary), Ministry of Agriculture (agro-ecological zones), and UN-OCHA (East African countries boundary). The background elevation map for the study area is clipped from the Shuttle Radar Topography Mission Digital Elevation Model. The open streets map has been used as a base map to indicate where Ethiopia is located)

The Gurage Zone has a population of 1,279,646 (622,078 men and 657,568 women) based on the 2007 census conducted by the CSA, with the vast majority of the population (92.4%) living in rural areas and engaging in agricultural production (CSA 2009). Settled agriculture has occurred in the area for at least a millennium (Tadesse 2009), with many Gurage settlements emerging around the cultivation of enset, a starchy root and tuber crop (also known as the false banana), which is a staple food among the Gurage people (Sahle et al. 2018, 2021b). The landscape communities adopted an enset-based home garden agroforestry system, similar to other regions in the south, south-central, and southwestern Ethiopia (Sahle et al. 2022) (Fig. 2). As a result, they produce abundant enset, integrated with or without other crops such as coffee, khats, and fruits according to agroecological zones, as well as annual food crops such as pulses and cereals in the outer fields (Sahle et al. 2022).

Fig. 2.

Illustration showing the Gurage socio-ecological production landscape settlement pattern following Jefoure roads (Source: Gurage Zone Tourism Culture and Sports Office 2019; Sahle et al. 2021b)

Despite the fact that a mosaic of different land uses has long contributed to the resilience of the Gurage socio-ecological landscape, recent data indicates that the landscape’s sustainability is under threat (Sahle and Yeshitela 2018; Aneseyee et al. 2020a, b). Compared to the previous date, recently, several studies were conducted to manage the landscape focusing on a specific ecosystem services management or socioeconomic development based on a scholarly perspective. However, landscape resilience requires proper management that secures the capacity of ecosystems to sustain societal development and ensures progress with essential ecosystem services in an integrated manner.

In changing socio-ecological systems such as the Gurage socio-ecological production landscape, opinions and firsthand local community knowledge are required to manage the landscape from various perspectives. Therefore, considering the indicators such as toolkit indicators for resilience in SEPLS in this landscape by engaging the local community and other stakeholders is helpful to establish a strategy for sustainable landscape management. Furthermore, because toolkit indicators for resilience in SEPLS examine the social and ecological systems in nearly equal depth (UNU-IAS, Bioversity International, IGES and UNDP 2014) and the various advantage mentioned above, we took the toolkit by adapting to the context to evaluate the resilience of the Gurage socio-ecological landscape in Ethiopia. This study focuses on the western catchment of Gurage, where the traditional farming system and landscape management have been sustained for a long time.

Landscape Resilience Assessment in the Gurage Socio-Ecological Landscape

Site selection

This study considered a multistage stratified and random sampling method to conduct resilience assessment. Thirteen sites were chosen from 2770 villages (CSA 2009) to represent the various configurations of the Gurage socio-ecological production landscape (Fig. 1). The landscape comprises cool-moist (998 villages), tepid-humid (1392 villages), and warm-humid (280 villages) agroecological zones (AEZ); accordingly, the landscape has been categorized based on its existing AEZ zones. Based on the area coverage, two samples in warm-humid AEZ, six in tepid-humid AEZ, and five in cool-moist AEZ have been considered. Differences in settlement histories (long-term and relatively new) and management practices were considered as additional criteria in consultation with zone-specific Tourism Culture and Sports offices to identify the study sites. Since large parts of the landscape area have over 100 years of settlement history, most of the samples (nine) were selected from long-term settlement areas.

The land use/land cover (LULC) is not uniform throughout the landscape, and sites were selected to represent the various mixed LULCs. The sample locations were then adjusted to represent the administrative districts in the landscape. These selection criteria led to the discovery of specific sample kebeles/ sub-districts. Finally, one locality was randomly selected in each sub-district since most of the localities in the sub-districts share similar characteristics. During data collection, conducting group meetings was difficult due to COVID-19, and samples were not taken in the three districts of Kebena, Geta, and Endagan. The authors expected that the neighboring district sample sites representing not-covered areas and missed sites would not significantly change the results of this study.

Community-based resilience assessment using indicators

Researchers conducted a workshop per site with local experts as facilitators, whose roles involved planning, organizing, and following up. The 20 indicators for assessing resilience in SEPLS were translated from English into the Amharic language for the participants. Interpretation and explanation of the indicators were conducted so that residents could understand the meaning of the indicators. Following the preparation phase, a 1-day resilience assessment workshop took place with the community representatives in each of the 13 selected villages between February and March 2020. Six to nine people representing the elderly, middle-aged, youth, women, sub-district chairpersons, and development agent workers participated in each workshop (Table 2).

Table 2.

Sample participants’ profiles in selected sites involved in the scoring of landscape resilience (N = 98)

Sites	Sex		Age		Local role
	Male	Female	<40	≥40	Elder	Religious servant	Youth	Sub-district chairperson	Development agent
Agera	5	3	2	6	3	1	2	1	1
Abiret	4	3	3	4	2	1	2	1	1
Anzere	5	2	4	3	4	–	1	1	1
Boqeta	5	2	2	7	3	–	2	1	1
Cheret	4	2	2	4	2	1	1	1	1
Yadazer Yezera	4	2	2	4	3	–	1	1	1
Debesa	7	2	2	7	5	1	1	1	1
Desene	6	2	3	5	4	–	2	1	1
Ener Gedam	5	2	2	5	3	1	1	1	1
Geharad	6	3	2	7	4	1	2	1	1
Inagera	5	2	2	5	3	1	1	1	1
Kotergedera	6	2	2	6	4	1	1	1	1
Luqe	7	2	4	5	5	–	2	1	1

The majority of the participants were chosen in consultation with the development agent workers and the chairpersons of each village’s sub-districts. We communicated with them to set a date for their visit and asked them to arrange a representative consisting of at least two elders, two women, one youth, and one religious servant on that day. Visiting the sites and holding the workshops, and other data collections schedule were arranged with this prior information. Additional participants were chosen randomly from the available community members in the workshop areas after being asked about their willingness, most of whom were elders and women. We considered a maximum of nine participants to run the workshop smoothly.

Except for development agents, all selected participants are farmers, and the other local roles are community-assigned responsibilities. We chose participants from the communities because the selected site communities rely on agriculture, and the study aimed to understand the local perspective. The development agents were included because they are government staff who support local communities and are expected to know the sites well.

The workshop has included the sub-district chairpersons to add the perspective of local leaders on evaluating the landscape’s resilience status. Even though religious leaders are farmers, we included them to provide additional religious perspectives. In those villages where religious institutes were not available nearby, it was difficult to find representatives and conduct the workshops without their participation.

The number of women participants has been lower than that of men in each selected site. Because women were preoccupied with domestic and market activities, engaging them in workshops was difficult. Aside from that, the main reason was that communities rarely assigned women to additional activities such as chairperson, religious activities, and elder members.

A score-based approach was considered to assign all indicators based on the explanation of resilience in SEPLS, with a 1–5-point linear scale. Higher scores indicate better landscape performance. For instance, five points mean the landscape performs remarkably well in the measured indicator. By contrast, one point means inferior performance. Methods to allocate a score and trend for each indicator were presented to the participants in each workshop. Each participant was given a form to complete. Participants were shown how a score for each indicator represents the current situation and that the direction of the arrow represents an ongoing trend. The resilience indicator scores were then collected, and participants discussed the average scores for each category.

The five main categories of resilience mean data for the 13 sites were interpolated from ArcGIS 10.7 tools to visualize the scoring result in the landscape. As a result, six maps, including the cumulative mean data, have been created and classified as low, medium, high, and very high.

Ancillary Data for Landscape Resilience Assessment

Household characteristics

During February and March 2020, researchers conducted 130 household surveys to understand household features and to support further the landscape resilience evaluated by the community. Ten households were systematically identified in the same village where a community-based resilience assessment was undertaken. Two data collectors or surveyors carried out household interviews. The first surveyor randomly selected one household from the nearest homesteads at the beginning of the Jefoure road in each village. The second surveyor counted ten homesteads down the opposite side of the road and interviewed the households living there. The interviews were conducted face-to-face and were based on a structured questionnaire. The surveyors had experience working with households and spoke the local language. In this manner, five household interviews were performed on each side of the road in selected villages.

A large number of questions were incorporated into the questionnaire to explore the general features of the landscape. The questionnaire covered land-use patterns, cropping type, home garden agroforestry systems, and livestock according to AEZ. For each question, the locations, type/variety, size, production, use, consumption, sales, challenges, and other associated questions were asked to each of the interviewed households. The surveyors prompted the householders to answer each question according to their understanding level and documented their responses on the questionnaire form while at the same time recording their voices in recorders after getting permission from the participants. The collected household data were encoded in an Excel sheet, and descriptive analysis was performed using SPSS 20 software.

State of land use/land cover in the landscape

In this study, researchers used orthophoto images obtained from the Ministry of Agriculture and Natural Resources Management in Ethiopia to depict the LULCs of the landscape, which had a 0.15 m spatial resolution with a natural color combination. In ERDAS Imagine 2014, the orthophoto images were classified by applying spectral signature values for each class through the maximum likelihood method of supervised classification. Degraded land, grazing land/pasture, cereal crops, forest, woodland, built-up land, eucalyptus plantations, lakes, Afroalpine vegetation, and enset-based home garden agroforestry were the 10 LULC types identified in this study. An accuracy assessment was executed to ensure the validity of the classified images. The corresponding reference class for each LULC type was gathered employing GPS during field visits and visual interpretation of the raw images with prior knowledge of the study area. In total, 440 reference points were utilized for the assessment, proportional to the area of each LULC. The overall accuracy of the classification was 90.9%.

Growing drought incidents assessment

Satellite imagery-based drought indices can be used to analyze drought occurrence and distribution (Alahacoon et al. 2021). The indices commonly applied for evaluating drought include the normalized difference vegetation index, the enhanced vegetation index, the leaf area index, and the vegetation health index (Yoon et al. 2020). While vegetation-based drought indices have proven valuable for monitoring the general vegetation condition, they are somewhat limited in effectively characterizing the effects of drought on vegetation (Yoon et al. 2020).

This study employed the evaporative stress index (ESI), a drought index formed on evaporation volume, to estimate drought incidents in the landscape. The ESI was established as a new drought index that uses geostationary satellite data to compare evapotranspiration to potential evapotranspiration (Anderson et al. 2011). The ESI is based on the remote sensing model atmosphere–land exchange inverse (ALEXI). The ALEXI model computes the ESI through a two-source energy balance model developed by Reference, and factors (e.g., surface temperature, plant distribution, and solar radiation estimates) are considered in the thermal infrared image obtained by the geostationary operational environmental satellite (GOES) (Yoon et al. 2020).

The ESI is available through SERVIR Global, a joint venture between the National Aeronautics and Space Administration with the United States Agency for International Development. The ESI images provided by the GOES characterize a 7-day cycle with 5 km resolution world images and provide composite images of 4-week data. Anomalous values represent the ESI in most studies, whereby a value <−2 indicates drought and a value >2 signifies wet conditions. ESI images for the past 20 years were downloaded from SERVIR Global databases to estimate the drought incidents in the Gurage socio-ecological landscape. March is the driest month in the landscape. As a result, the ESI images captured in the middle of the month (13th—14th) were used to assess the drought occurrence in the landscape.

Results

Degree of Landscape Diversity and Ecosystem Protection

The landscape has different LULC types: forests, woodlands, eucalyptus plantations, Afroalpine vegetation, home garden agroforestry, cereal cropping, and open grazing lands (Fig. 3). In 2017, the urban environment covered only 0.4% of the landscape, and large parts of the landscape are either covered with vegetation or utilized by diverse land-use practices (Table 3). Large portions of the landscape are utilized for cereal crop cultivation (32.3%), livestock grazing (31.8%), and enset-based agroforestry (10.2%). The elevation of the landscape ranges from 968–3593 m above sea level and has a slope difference between 0° and 66°. The mountain chains give rise to several perennial and annual rivers and streams. Conversely, the number of lakes is tiny and found in the upper catchment, with an area coverage of only 0.1%. The extent of landscape diversity varies in the landscape, and according to the resilience evaluation during the workshops, some sites have a greater diversity of natural ecosystems and land uses than others, with an average score of 3.7- from 5.0 (Table 4). A moderately high score value is due to the natural topographic configurations and the diversity of LULCs in specific sites.

Fig. 3.

The LULC map of the western Gurage socio-ecological landscape. The zoomed maps indicate the sample villages area employed for evaluating the resilience of the landscape. (Source: Compiled by the authors based on an orthophoto mosaic image of the landscape)

Table 3.

LULC areal size in the Gurage socio-ecological landscape

LULC	Area (ha)	%
Enset-based agroforestry	44,252	10.2
Afro-alpine vegetation	3029	0.7
Built up	1694	0.4
Arable land (cereal crops (32.3%) and grassland (31.8%))	276,788	64.1
Grassland	137,172	31.8
Eucalyptus	39,294	9.1
Forest	32,152	7.4
Degraded land	13,073	3.0
Lake	544	0.1
Woodland	20,906	4.8

Table 4.

The community-based score value for the indicators of SEPLS in selected sites in the Gurage Socio-ecological landscape (Color difference shows groups of indicators)

The LULC data analysis shows natural forests, including riverine environments and dry Afromontane forests, covering 32,152 ha (7.4%) (Table 3). The dry Afromontane forests were found in conservation areas, with scattered patches lingering in communal land and religious-centered forests. In the mountain areas, Afroalpine vegetation covered only about 0.7% of the landscape. According to the participants, the increased human population in the landscape caused most natural ecosystems to be converted to agricultural land, including the top mountain agroecosystems (Fig. 3). Currently, most of the natural ecosystems have been discovered in gorges along the riversides. Woodland areas, primarily found at lower landscape elevations, covered 20,906 ha (4.8%). Woodland areas were in the parts of Gibe Sheleko National Park, the only legally protected area at the national level. However, there are some formal and informal conserved patches of forest protected by the government and the community and sacred forests conserved by the traditional and Christian religions. In general, the landscape has a few protected areas that have cultural and ecological significance and their spatial distribution varied. The score for resilience evaluation by the workshop participants ranges from 1.5 in Agera and Desene sites to 4.3 in Abiret and Koter Gedra sites, with the landscape average at a 2.6 score value (Table 4).

On average, the participant’s score for the degree of ecological interactions in the landscape is 3.7 (Table 4). This value could result from existing preserved natural sites, enset-based home garden agroforestry systems, eucalyptus plantations along riversides, and recent soil and water conservation-restoration activities. Enset-based agroforestry occupied ~10.2% of the landscape. According to the growing potential of the AEZ, home gardens in the landscape had a horizontal structure with enset as the dominant crop, either planted as the only perennial plant or integrated with other crops like khat, coffee, fruit, cabbages, potatoes, and cereal crops. Eucalyptus plantations occupied 39,294 ha (9.1%) as woodlots in household plots (Table 3). Deteriorated land, which was situated in the central parts of the landscape, covered about 13,073 ha (3%) (Fig. 3).

The landscape area is impacted most by flash droughts. In the past 21 years, ESI data revealed that the sign of drought through evapotranspiration stress prevailed nine times (Fig. 4). A value below −2 is indicative of drought, and a value above 2 is indicative of wet conditions. Between -2 and 0 indicates the area is under stress but not categorized as a drought (Fig. 4 and Supplementary Material 1). Out of these years, the highest flash drought prevailed in 2004, 2008, and 2011. The highest magnitude of drought occurred in 2008 due to the disparity in the degree of dispersion. Extreme events do not constantly occur in the same place and vary throughout the period. These events were confirmed during the workshops, and drought incidents had severe human and economic consequences, particularly for smallholder farmers residing in the upper catchment of the landscape. The droughts caused water sources to dry up, leading to severe water shortages for humans, livestock, and agricultural and biomass production.

Fig. 4.

Evapotranspiration stress over the past 21 years in the Gurage socio-ecological production landscape (Source: Compiled by the authors based on ESI images provided by the Geostationary Operational Environmental Satellite with 5 km resolution)

However, the impacts depend on the adaptive capacity of each locality. The lowest score (1.6) is given by the Boqeta site, which could be related to the community’s livelihood being dependent on cereal crop production and the fact that it is located in the lower altitude areas, which do not allow enset-based home garden agroforestry system (Fig. 3). Participants living in the middle catchment areas with mixed land uses scored higher than the upper catchment sampled localities, leading their livelihoods primarily through cereal crop and livestock production. On average, the participants gave a score of 3.1 on the ability of the landscape to recover from drought.

Degree of Biodiversity Maintenance (Including Agricultural Biodiversity)

Participants rated the diversity of local food consumption as “very high,” with an average score of 4.1 (Table 4). This could be due to the typical household’s parcel of land, including enset, khat, coffee, fruit, greens and root vegetables, cereal crops, medicinal plants, and spices. The staple/co-staple food of the community is from the enset crop, and 92% of the surveyed households residing in the workshop’s localities planted this crop. There are numerous varieties/farmers’ landraces of enset, and households identified 3–33 varieties in their home garden. Khat and coffee, perennial stimulant crops, were grown by 43.4% and 38.2% of the examined households, respectively. Cereal crops are cultivated according to the AEZ of the landscape. Cereal crops like barley, peas, and beans were the most frequently grown in highland areas. Wheat, barley, and pea crops were cultivated in the central catchment areas of the landscape. In the lower catchment, cereal crops such as teff (Eragrostis tef), maize (Zea mays), sorghum (Sorghum bicolor), Niger seed (Guizotia abyssinica), chickpeas, red kidney beans, lentils, and peppers were grown. Fruit like avocados and mangoes were grown in the central humid region of the landscape and were found in 39.5% of households. Vegetables, including cabbages and potatoes, were grown in 26.3% and 63.2% of households, respectively. Medicinal plants and spices were grown in 47.4 and 28.9% of the surveyed households, despite their small-scale production and the fact that they are primarily for household consumption. Almost all the sampled households kept livestock and occasionally, beehives had been established in home gardens (11.8%).

The participants ranked 3.0 for the conservation of local crops and breeds. They score an average of 2.2 for maintaining the quality of local seeds and breeds resilience indicator. According to the participants, associations are not available for keeping local seeds, animal breeding groups, and community seed banks; instead, an individual farmer keeps selected varieties of seeds and may share them during shortages. The government extension workers assist communities in providing improved seeds and breeds, particularly cereal crops, which leads to the loss of the local varieties. Even though the national agricultural centers released the improved seeds, they were not well evaluated according to the landscape AEZs and soil conditions. Except for two sites in the middle of the catchment, participants at different localities gave a lower score regarding invasive species replacing local ones. According to participants’ score values, there is some variation in the sustainable management of shared resources among selected research sites. On average, they scored 2.8, with poor management observed mainly in the Anzire and Desene sites. Although the community consumes a diverse range of locally produced food, the quality of biodiversity maintenance, including agricultural biodiversity, is not good (2.8).

Degree of Knowledge and Innovation

The ability of the community to develop, enhance, and adopt new agricultural and conservation techniques and/or revitalize traditional ones to adapt to changing conditions is limited in the landscape. The group ranking ranges from 2.0–2.9 (Table 4). Participants reported that communities are attempting to maintain traditional farming practices such as organic agriculture production in their home gardens and shifting or rotating cereal crops and grazing lands. However, communities rarely carry out measures such as adopting water conservation measures like drip irrigation or water harvesting, diversification of farming systems, planting drought-tolerant crops except for enset crops, and planting acidic soil-improving crops including legumes, terracing farming, or reforestation.

Local knowledge and cultural traditions related to biodiversity are mostly passed down from elders and parents to young people in the community directly through demonstrations or oral traditions. Rarely are they included in the songs, dances, rituals, festivals, and stories with local terminology related to land and biodiversity. For instance, enset is the staple/co-staple food for more than 92% of the interviewed households, but only 21% of them knew any folklore, songs, or stories associated with enset. In addition, information is difficult to locate in educational curricula.

According to the SEPLS resilience indicators, one potential approach for knowledge development is the documentation of biodiversity-associated knowledge, such as traditional knowledge registration, resource classification systems, community biodiversity registers, farmers’ field schools, animal breeding groups, pasture co-management groups, seed exchange networks (animal and seed fairs), and seasonal calendars. The results indicate that documentation of biodiversity-associated knowledge is low, with participants at different localities scoring an average of 2.2. Women in the community are known to manage and produce home garden crops, care for livestock, and prepare diverse foods. However, their knowledge and skills are not well recognized or respected, and participants scored 2.5 on average. Compared to other indicators, the overall score for the degree of knowledge and innovation is relatively low (2.2) in the Gurage socio-ecological landscape (Fig. 5). The lower figure evaluated by the community in the landscape indicates that landscape biodiversity (including agricultural biodiversity) and the correlated knowledge in the landscape are poorly documented and stored for knowledge development.

Fig. 5.

Extrapolation of the resilience status in five categories of indicators scored by local communities from diverse study sites in the Gurage socio-ecological landscape (Source: Compiled by the authors by using data from the results of scoring through Inverse distance weighted interpolation tools of ArcGIS)

Degree of Governance and Social Equity

Participants involved in evaluating the degree of rights related to land/water and other natural resource management gave a high score with an average of 3.8 (Table 4). According to the participants, communities have customary laws regarding utilizing communal resources such as seasonal pastures and water use in each locality. Communities have equal access to public lands, and participants, on average, scored 4.6. However, no solid multistakeholder landscape platform or institution can efficiently plan and manage landscape resources. Formal government rules are applied to conserve natural ecosystems like forests, and co-management arrangements between local people and the government have been witnessed. Individuals within and between communities are correlated and coordinated through local institutions such as edir and mahibber. However, there are no formal associations for managing natural resources in partnership with the government organs, and local government administrative offices take over the conservation roles. On average, social equity, including women’s participation, scored 3.5. At the household, community, and landscape levels, access to opportunities and resources is somehow fair and equitable for all community members. According to the group discussions, even though women participate in local meetings, most decisions are made by men. Women do not have a place in higher official community meetings, such as Yejoka.

Livelihoods and Well-Being

According to the participant scoring, the socioeconomic infrastructure facilities in the landscape are inadequate. Their infrastructure adequacy scores ranged from 1.5 in Cheret to 3.2 in Desene localities, with an average of 2.7 in the landscape. Access to schools, water points, and health posts is insufficient. Even the existing accessible facilities are not of good quality. Electricity is not available except for the communities living in small towns and the surrounding landscape areas. The participants noted that water-borne diseases such as typhoid are common throughout the landscape. Malaria is prevalent in the landscape where there is warm agroecology. The established health institutions do not even have basic facilities and medicine. The community at large in day-to-day activities uses traditional medicine, but people will go to the clinic for more severe symptoms. On average, participants scored 2.6 for the human health and environmental situations in the landscape.

Most communities are engaged in agricultural activities and do not have many diversified income sources; hence, they scored 2.9 on average. The community rarely engages in income-generating activities except for those with access to towns, roads, and markets. According to the participants, communities utilize the local biodiversity for their considered, which are also regarded as traditional customs. However, recent trends demonstrate that traditional materials do not tend to make more use of local biodiversity, and the group participants gave an average score of 2.5. In addition, households have a small parcel of land for practicing agriculture (1.1 ± 0.7 ha on average). As a result, they cannot move about to take advantage of shifts in production opportunities.

Nevertheless, households contemplate shifting cultivation, crop rotation, and livestock herding within their land parcels to avoid land degradation and overexploitation. Except for some landscape sites, there are no communal lands for grazing and other production operations. According to the community participants, communal grazing lands have been converted to cereal crops by the community youth associations and large-scale agricultural investors. As a result, the total graded value for the landscape supporting livelihoods and well-being is 2.7, below the medium scores.

Overall Resilience Status of the Landscape

According to the community assessment, the landscape’s resilience is below the optimum (2.9) (Table 4). Landscape diversity and ecosystem protection (3.3) and governance and social equity (3.8) indicators were given the highest resilience scores. In contrast, lower scores resulted in knowledge and innovation (2.1) and livelihoods and well-being (2.7) indicators. Among the chosen study sites, the lowest resilience score was in Yadazer Yezera (2.3), and the highest was in Geharad (3.3). On the other hand, sites such as Aegera and Boqeta communities ranked their landscape proximate to an average resilience score (3.0).

Yadazer Yezera has the lowest score due to the lower diversity of agroforestry systems, the availability of livelihood and well-being options, and the relatively low level of knowledge and innovation in the specific landscape area. The lower level of knowledge and innovation at this site can be attributed to agro-climatic conditions, soil fertility, and socioeconomic facilities that do not allow for greater innovation. Furthermore, participants on this site gave lower values to indicators such as the conservation of local breeds, maintenance of local seeds and breeds, invasive species replacing local ones, and sustainable management of shared resources. The LULC analysis from the satellite image (Fig. 3) shows that the site and its surrounding area are severely degraded, as observed by the researchers during their visit. However, this study is based on a score based on community perception, and further research may be required to determine the exact reason for it.

Discussion

Socio-Ecological Production Landscapes Resilience Assessment Using Indicators

By helping policymakers better understand how resilient the landscape is, indicators can play an essential part in giving legitimacy to community-level interventions (Dunbar et al. 2020). Applying the resilience indicators makes it possible for policymakers to accept better management actions designed to re-establish and sustain resilience (Sterling et al. 2017). The primary benefit of employing the resilience indicators was to manage local peoples’ perceptions of assisting stakeholders in understanding socio-ecological resilience. Understanding the perceptions could help uncover socio-ecological resilience elements, detect challenges to resilience, and develop potential strategies to maintain the landscape ecosystems and human well-being (Ciftcioglu 2017). Simultaneously, the use of the indicators can aid communities in identifying gaps in their understanding of system complexity and dynamics and thus identify opportunities to leverage synergies (Saito et al. 2020).

Creating legitimate, functional, and vibrant resilience measures in a socio-ecological system usually requires indicators co-created by local stakeholders, practitioners, and knowledge-holders (UNU-IAS, Bioversity International, IGES and UNDP 2014). The development, testing, and implementation of the toolkit of indicators in SEPLS took nearly 10 years of experience and generated a great deal of knowledge on this kind of indicator methodology (Dunbar et al. 2020). The SEPLS resilience assessment utilizing community-based indicator scores can bring about the idea of landscape resilience and provide information to policymakers (Sterling et al. 2017). However, these resilience indicators are limited in some aspects by the subjective nature of perceptions and the difficulty in comparing them over time or among various groups (UNDP 2018; Dunbar et al. 2020). They emphasize the importance of exercising caution when utilizing indicator scores as quantitative measures and the benefit of triangulating indicator findings with information from other objective data sources and other participatory tools. Resilience metrics that surface from local contexts may hinder cross-case comparisons, but with careful hierarchical explanations of terms, common properties of resilience may be weighed and compared across sites, thus enabling multiple knowledge systems to notify results (Tengo et al. 2014; Quinlan et al. 2016). Nevertheless, owing to their subjective nature and changing socio-ecological circumstances, these indicators cannot be utilized to compare different landscapes and seascapes (Dunbar et al. 2020).

This study considered the same group of people residing in various localities. The participants were carefully chosen to represent all communities, including government extension workers. These mechanisms enabled researchers to contrast the landscape resilience status among the localities even though it is complicated to compare with other communities living in different socioeconomic and environmental conditions. In addition, data such as LULC analysis and household surveys were used to support the refinement of the scored data better to understand the resilience status among localities and between indicators. As such, these valuable data increase dependency on indicator-based findings and should be considered in future works to support landscape planners, decision-makers, and policymakers in understanding how to improve resilience capacity according to the landscape and indicator types.

Similar to the findings of this study, Dunbar et al. (2020) concluded that the indicators of resilience in SEPLS serve as an effective tool for community-based assessment of projects and the overall status of the resilience of landscapes and seascapes. The indicator assessment can document the strengths and resources of the community. The assessment can also foster collaborative partnerships by generating a sense of ownership. Moreover, the assessment generates knowledge that informs project actions for the benefit of all stakeholders and provides a platform for co-learning and empowerment.

Sustainable Land Management for Enhancing Resilience in the Gurage Socio-Ecological Landscape

The diverse ecosystems and biodiversity in the Gurage socio-ecological landscape are not adequately protected and maintained and thus can be improved through community-based management of existing forest-protected areas and by expanding the areas within the landscape for indigenous forest protection (Sahle and Yeshitela 2018; Sahle et al. 2018). Furthermore, the mountains, riversides, and abandoned or degraded areas within the landscape need to be restored, and suitable land-use management systems should be applied to restore ecosystem function and improve productivity. It is also essential to strengthen the existing community landscape restoration programs with a primary focus on planting indigenous trees and modifying the home garden agroforestry to fulfill multifunctional goals. These efforts on landscape diversity and ecosystem protection could enhance the resilience of the landscape. Furthermore, landscape management could also contribute to sustainable development goal (SDG) 15, which focuses on protecting, restoring, and promoting sustainable use of terrestrial ecosystems, as well as to other related global goals (Takahashi and Kozar 2020).

The Gurage socio-ecological landscape reflects a mixed farming system. According to the participants, enset-based home garden agroforestry is responsible for the landscape’s long-term resilience capacity, particularly in relation to the impact of drought. Enset is a perennial keystone crop in the home garden system that provides essential food for humans as well as feed for livestock (Sahle et al. 2018, 2021b). The Gurage socio-ecological landscape area has not been particularly affected by famine, even in the 1980s when large parts of Ethiopia were affected due to the country’s vulnerability to extreme weather events (Brandt et al. 1997; Harrison et al. 2014; Borrell et al. 2019). However, the future is uncertain in the landscape as trends show that home garden production is declining, associated with less government attention and socioeconomic changes (Sahle et al. 2022).

Technological innovations in enset production and food processing, industrial applications, and value addition of products and marketing chains are necessary to boost the resilience capacity of the community. Although farmers strategically use a given parcel of land for their homesteads where they grow staple food, cash crops, vegetables, cereal crops, pastures, and woodlots, there has been a tendency to expand the area for cash crops such as khat, cereal crops, and eucalyptus trees. These changes have caused a decrease in the landscape’s agrobiodiversity. Therefore, it is vital to promote the production of traditional crops by enhancing awareness-raising, supporting information exchange, and creating marketing opportunities. These management activities could support implementing the various SDGs.

In this study, communities had lower knowledge and innovation scores (2.1). The reasons behind this include recent low innovative practices, no local knowledge documentation, and not much recognition of women’s knowledge. Developing and establishing a small-scale community resource center and seed banks in the landscape is essential for knowledge-sharing and innovation. In addition, farming systems within the landscape need to be geared toward food security by employing technological inputs and irrigation systems, maintaining genetic diversity, generating income variety, conserving vital ecosystems, and minimizing greenhouse gases. There is also a need to map out and document the diverse landscape agricultural resources to develop appropriate farm and production plans, explore local food processing opportunities, and enhance local self-sufficiency.

Traditional knowledge documentation activities focused on knowledge held by elders and women within the landscape, and this is crucial to boosting a revival of the landscape through community actions. Women can make significant contributions to modifying the agro-biodiversity system, and as such, they should be empowered to engage in resource production, craft development, and skill enhancement on both traditional and modern commodities. These methods of traditional knowledge documentation and innovation in traditional agricultural activities contribute to various SDG goals.

Even though local communities in the socio-ecological landscape have customary laws and institutions, the local government did not give authority to managing their local resources according to their customs. Therefore, it would be better to support community institutions aiming for self-sufficiency, such as capacity building, leadership, financing, management, communications, monitoring and evaluation, and networking, thereby improving the sustainable management of landscapes. Furthermore, projects engaged in building women’s capacity within the community and ensuring active participation in local community governance and leadership are essential to increase resilience in socio-ecological landscapes, like in Gurage.

Due to the low-quality socioeconomic infrastructure facilities and a lack of income diversity and socio-ecological mobility, the livelihoods and well-being categories of the resilience indicators in Gurage SEPLS are below the relative thresholds. Dendir and Simane (2019) also stated that farm households have inadequate access to basic infrastructure, as well as a low level of diversification and a lack of available technologies. This leads to the community being vulnerable to climate variability changes. Thus, there is a need for infrastructural improvements such as roads, electricity, water sources, quality education, health services, and markets. Such facilities would increase the resilience capacity of the landscape and, at the same time, contribute to the SDGs targets.

Conclusion

The SEPLS resilience indicators are intended to help find priority problems and measures for sustaining SEPLS that benefit livelihoods and well-being, rather than providing precise measurements of resilience in the landscape. The state of resilience in the case study SEPLS (Gurage socio-ecological landscape) is below optimal, mainly because of the lower scores for knowledge and innovation and for livelihoods and well-being options. Resilience strategies that address the root causes of vulnerability in the long-term, and overcome the influence of climate change and other socioeconomic factors through fundamental shifts in states and interactions of people and nature, are vital for the sustainability of socio-ecological landscapes. It is also essential to enhance the synergies between the multi-functions of landscapes, as well as manage challenges that cause trade-offs.

Improved networks and collaborations between and among stakeholders at several levels across various relevant sectors to support local activities can extensively contribute to adaptation to extreme events. Using resilience indicators in SEPLS could enable the collaborative identification of priority activities for adaptive management in the community. Developers and users of indicators need to work together to modify them to have more interlinkages with socio-ecological goals. The toolkit indicators of resilience in SEPLS should see a larger uptake for conservation and enhancing resilience in similar socio-ecological landscapes worldwide.

Author contributions

Conceptualization: MS and OS; methodology: MS; software: MS; validation: MS and OS; formal analysis: MS, investigation: MS; resources: OS; data curation: MS; writing—original draft preparation: MS; writing—review and editing: MS, OS and SMS; visualization: MS; supervision: OS; project administration: MS; funding acquisition: OS. All authors have read and agreed to be published the manuscript.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Compliance with ethical standards

Conflict of interest

The authors declare no competing interests.

Supplementary information

The online version contains supplementary material available at 10.1007/s00267-023-01794-0.