Resilience and development: Mobilizing for transformation

In 2014, the Third International Conference on the resilience of social-ecological systems chose the theme “resilience and development: mobilizing for transformation.” The conference aimed specifically at fostering an encounter between the experiences and thinking focused on the issue of resilience through a social and ecological system perspective, and the experiences focused on the issue of resilience through a development perspective. In this perspectives piece, we reflect on the outcomes of the meeting and document the differences and similarities between the two perspectives as discussed during the conference, and identify bridging questions designed to guide future interactions. After the conference, we read the documents (abstracts, PowerPoints) that were prepared and left in the conference database by the participants (about 600 contributions), and searched the web for associated items, such as videos, blogs, and tweets from the conference participants. All of these documents were assessed through one lens: what do they say about resilience and development? Once the perspectives were established, we examined different themes that were significantly addressed during the conference. Our analysis paves the way for new collective developments on a set of issues: (1) Who declares/assign/cares for the resilience of what, of whom? (2) What are the models of transformations and how do they combine the respective role of agency and structure? (3) What are the combinations of measurement and assessment processes? (4) At what scale should resilience be studied? Social transformations and scientific approaches are coconstructed. For the last decades, development has been conceived as a modernization process supported by scientific rationality and technical expertise. The definition of a new perspective on development goes with a negotiation on a new scientific approach. Resilience is presently at the center of this negotiation on a new science for development. (Résumé d'auteur

Samförvaltning av interagerande ekosystemtjänster i Helgeåns avrinningsområde

Det stora genombrott som ekosystemtjänstbegreppet har fått öppnar upp nyamöjligheter för att på ett sammanhållet vis arbeta med hållbar utveckling. Menför att operationalisera begreppet i den här kontexten krävs att vi jobbar medbegreppet på ett mer holistiskt, dynamiskt och inkluderande sätt än vad somhittills varit praxis. Den här strävan har utgjort grundbulten i forskningsprojektetsom beskrivs i rapporten. Syftet har varit att, tillsammans meden rad lokala aktörer, tolka landskapet runt Helgeån genom en ekosystemtjänstlins,och gemensamt utforska vägar till en mer hållbar framtid somkaraktäriseras av ett multifunktionellt landskap.I samverkansprocessen första fas gjorde vi ett gemensamt urval av 15 olikaförsörjande, reglerande och kulturella ekosystemtjänster att inkludera i analysen,varpå vi utförde en rumslig analys av produktion av tjänsterna, en jämförandeanalys av efterfrågan i relation till produktionen, samt en så kalladknippesanalys som visade hur tjänsterna förhåller sig till varandra. I samverkansprocessenandra fas utvecklade vi en vision för framtiden som beskrevett mer multifunktionellt landskap, genomförde en systemdynamisk analys somförklarar tre nyckelfrågor relaterat till ekosystemtjänsterna i landskapet sommåste lösas för att kunna nå visionen, och identifierade en rad förvaltningsåtgärdersom gör att det möjligt att närma sig visionen.Den deltagande och iterativa process som användes för att analyseraekosystemtjänsterna i området förbättrade kvaliteten på resultaten avsevärt,jämfört med mer konventionella approacher. Metoden gav en snabb överblickav hur landskapet är sammansatt från ett social-ekologiskt perspektiv ochden bygger på offentliga data, vilket gör den resurseffektiv. Vad det gällerknippesanalysen fann vi att förekomsten av de olika ekosystemtjänsterna ärtydligt aggregerade på en större skala än kommunnivå, med den urbaniseradeslättlandsbyggden i sydväst, det mer varierade produktionslandskapet i sydost,och det av skogsbruk präglade rurala landskapet i norr.Även om vår samverkansprocess inte var knuten till någon formell beslutsprocess,så skapade arbetet med en gemensam vision och utforskandet avsystemdynamik en samsyn mellan deltagarna, som såg ekosystemtjänstersom ett bra begrepp att samlas kring. Arbetet med att identifiera åtgärderutifrånsystemdynamiken resulterade också i en rad innovativa idéer somunder andra omständigheter skulle kunna omsättas i en faktisk aktionsplan.Under resans gång har vi stött på vissa svårigheter med begreppet där vidareutvecklingskulle behövas, bland annat relaterat till tillgång på data och tillhur vi ser på kulturellatjänster. En viktig fråga att ställa sig här är hur långtekosystemtjänstbegreppettar oss i arbetet med hållbar utveckling, och vilkentyp av frågor det inte hjälper oss att svara på

Assessment of ecosystem services and benefits in village landscapes – A case study from Burkina Faso

Most methods to assess ecosystem services have been developed on large scales and depend on secondary data. Such data is scarce in rural areas with widespread poverty. Nevertheless, the population in these areas strongly depends on local ecosystem services for their livelihoods. These regions are in focus for substantial landscape investments that aim to alleviate poverty, but current methods fail to capture the vast range of ecosystem services supporting livelihoods, and can therefore not properly assess potential trade-offs and synergies among services that might arise from the interventions. We present a new method for classifying village landscapes into social-ecological patches (landscape units corresponding to local landscape perceptions), and for assessing provisioning ecosystem services and benefits to livelihoods from these patches. We apply the method, which include a range of participatory activities and satellite image analysis, in six villages across two regions in Burkina Faso. The results show significant and diverse contributions to livelihoods from six out of seven social-ecological patches. The results also show how provisioning ecosystem services, primarily used for subsistence, become more important sources of income during years when crops fail. The method is useful in many data poor regions, and the patch-approach allows for extrapolation across larger spatial scales with similar social-ecological systems

Maps of social-ecological patches for study area 1 and 2.

<p>Urban land and water is a land cover, but not a social-ecological patch.</p

Schematic of the generalizability of the social-ecological patches.

<p>The dashed arrows indicate suggested new social-ecological patches that were not included by Sinare and colleagues [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192019#pone.0192019.ref023" target="_blank">23</a>]. The crossed arrow connected to fallow indicates the failure to extrapolate this patch using remotely sensed data (for explanation see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192019#sec008" target="_blank">Results</a>). Social-ecological patches in dashed boxes were not mapped in the current study, either because they are additions to the original categorization or because it was impossible with the available data.</p

Schematic of work flow for the developed hybrid classification method.

<p>The data layers used include the red, near infrared and mid-infrared bands of the Landsat 8 OLI scenes (bands 4, 5 and 7); Normalized difference vegetation index (NDVI; [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192019#pone.0192019.ref052" target="_blank">52</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192019#pone.0192019.ref053" target="_blank">53</a>]); and Tasseled Cap Transformation (TCT), an index that compresses multispectral Landsat data into the three bands brightness, greenness and wetness [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192019#pone.0192019.ref054" target="_blank">54</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192019#pone.0192019.ref055" target="_blank">55</a>]. To define the spectral signatures of some of the social-ecological patches, we used mean and standard deviations (st.d.) as well as the M statistic (a measure of spectral separability between classes; [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192019#pone.0192019.ref056" target="_blank">56</a>,<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192019#pone.0192019.ref057" target="_blank">57</a>]) for the different patch calibration points in all data layers. For implementation of the method, three GIS softwares were used: ArcMap [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192019#pone.0192019.ref058" target="_blank">58</a>], ENVI [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192019#pone.0192019.ref043" target="_blank">43</a>] and Google Earth.</p

Description of social-ecological patches and their contribution to livelihood benefits.

<p>a) Social-ecological patches and characteristics of their ecosystem services generation; b) Relative contribution of the social-ecological patches found in the current study to the five identified livelihood benefits. Original scores are means from 36 focus groups conducted by Sinare and colleagues [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192019#pone.0192019.ref023" target="_blank">23</a>]. Scores here are adapted from the original work, based on feedback during fieldwork conducted for this paper, to better represent per unit area contribution of social-ecological patches (for detailed description, see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192019#pone.0192019.s005" target="_blank">S1 Text</a>). Figure partly based on Sinare and colleagues [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192019#pone.0192019.ref023" target="_blank">23</a>] under a CC BY license, with permission from the authors, original copyright 2016.</p

Overview maps.

<p>Maps of the study areas and villages where fieldwork was conducted. Study areas indicate extent of analyzed remote sensing images. Points show location of villages included in this study (blue) and mapped by Sinare and colleagues [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192019#pone.0192019.ref023" target="_blank">23</a>] (yellow). Boundary data is from Natural Earth [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192019#pone.0192019.ref041" target="_blank">41</a>] and location of villages and towns collected with GPS during fieldwork.</p

Percentage of landscape covered by each social-ecological patch and their relative accuracies¹.

<p>Percentage of landscape covered by each social-ecological patch and their relative accuracies<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0192019#t002fn001" target="_blank">¹</a>.</p

The spatial distribution of livelihood benefits.

<p>Maps of the distribution of the five livelihood benefits (a-e) in study area 1 and study area 2 were generated using the social-ecological patch maps and the weighted livelihood benefit scores. The heat maps (f) were generated by adding all separate livelihood benefit maps into one composite map. The heat maps show the provision of multiple livelihood benefits, with high scores suggesting highly multifunctional parts of the landscape.</p