Progress 02/28/17 to 09/30/21
Outputs
Target Audience:We have reported on target audiences in previous reports. For this final reporting period we reached the following: About 40 people (of which 35 were World Bank staff) through an invited seminar presentation onForests, Trees and Poverty Alleviation in Africaat the World Bank, September 2021 (Virtual). About 50 people as akeynote speaker onForests, Trees and Poverty Alleviation in Africa: An Expanded Policy Brief. Side event for the UNHigh-Level Political Forum on the 2030 Sustainable Development Agenda. July 2021 (Virtual). Changes/Problems:We have been successful in empirically validating PPIs in non-U.S. settings, but the U.S. work was delayed due to negotiations over data sharing with the USFS and the University of Illinois and then personnel turnover (key post-doc leaving) and the COVID-19 pandemic.We were able to complete the work as promised but for U.S. application.Our outreach was affected by the pandemic and we were not as able to reach as many U.S.-focused audiences as we had planned. We hope to change this in the post-project period as the work is still very relevant. What opportunities for training and professional development has the project provided?The project has supported post-graduate, graduate, and undergraduate students who work closely with the project lead and other experts (e.g. the IUFRO Global Expert Panel, members of FLARE (the Forests and Livelihoods:Assessment and Research Engagement network),the forestry Extension specialist at Dixon Springs for the University of Illinois) to advance their training and knowledge in relating to novel approaches to understanding the long term social-ecological impacts of forest programs.The project has also supported professional development primarily in the form of participation in conferences/professional meetings. How have the results been disseminated to communities of interest?Results have been disseminated through peer-reviewed journal articles,invited workshops and high-level fora,conference presentations,discussions with key stakeholders (e.g. in Southern Illinois and internationally via IUFRO, the FLARE network, and other means), in the classroom (e.g. undergraduate and graduate courses in NRES at University of Illinois); and social media (e.g. twitter posts and discussion). What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
We have now completed the work proposed to reach the overall goal of the project "to advance knowledge of the long-term environmental and socio-economic impacts of forest conservation and management".Our overall assessment is that we have met or exceeded our expectations for this project. Work under the project helped establish the reputation of the PI Miller such that he was recognized as a global expert in the socio-economic dimensions of forests such that he was selected to lead a major global assessment on forests, trees and the eradication of poverty supported by IUFRO as well as the Forests and Livelihoods: Assessment Research and Engagement (FLARE) network. These achievements have allowed for the wide dissemination of the ideas and the research behind the core innovations of this project on predictive proxy indicators (PPIs) in the forestry sector. In all, research under this project has helped to support a dissertation, two MS theses, and six peer-reviewed journal articles. The peer-review and public availability of our findings and data is a major impact of this work. The project has supported several undergraduate students in research, two master's students, a PhD student, and two post-docs. Without this support their academic progress and degrees would not have been possible, a notable impact itself. Accomplishments - Objective 1: Analytical approach for assessing the long-term social-ecological impacts of forest conservation and management and empirically validating PPIs. Major Activities Completed: 1) Publication of two review papers on the need for and concept of PPIs; 2) Publication of two MS thesis on long-term impacts (one focused on Bhutan and one on Benin). Data Collected: For Activity 1, data were derived from a review of the scholarly literature on the topic; for Activity 2 data were collected on funding for forest conservation in the two countries along with survey data related to perceptions of key stakeholders, such as forestry practitioners and local communities. Summary Statistics and Discussion of Results:The main result is that this work has catalyzed awareness of PPIs as a concept and a tool for tracking long-term impacts in the forestry sector and, more generally, of the need for considering long-term social-ecological outcomes in the first place. Key Outcomes or Other Accomplishments Realized: See assessment above. Accomplishments - Objective 2: To use the approach in specific geographic and programmatic contexts in theUnited States and abroad to empirically validate a set of PPIs. Major Activities Completed: 1) Publication of three empirical papers focused on the Indian Himalayas that successfully validated PPIs empirically; 2) Submission of a proposal to further extend this work to US context (to USFS and to USDA). Data Collected: We have previously reported on the data collected, which derive from both publicly available biophysical and socioeconomic datasets relating to India but also original data collected from field research in the Indian Himalaya. Summary Statistics and Discussion of Results:We have reported on previous results and summary statistics for work under this objective in previous publications and in our most recent publication (Rana and Miller, 2021). We identified PPIs for community-oriented tree-planting efforts in northern India. We used process-tracing and qualitative comparative analysis methods to find that clusters of PPIs explained vegetation growth trajectories and other outcomes over more than a decade in 23 randomly selected public forest plantations in the study area. PPIs relating to property rights and local livelihood benefits, community-led monitoring and enforcement, and seedling survival rate, together, were associated with successful long-term forest plantation outcomes, including more tree cover and socio-economic benefits for local communities. The causal pathways identified in this study suggest that measuring and comparing indicator values in specific spatial and temporal contexts can help to assess the likelihood and directionality of the long termsocial and ecological impacts of forest plantations. In addition to the empirical contribution it makes, this study also demonstrateda novel approach to understanding long-term impacts of public forest plantations relevant to country contexts around the world. Key Outcomes or Other Accomplishments Realized: See assessment above.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2021
Citation:
Rana, P. and Miller, D.C. 2021. Predicting the long-term social and ecological impacts of tree-planting programs: Evidence from northern India. World Development 140: 105367.
- Type:
Theses/Dissertations
Status:
Published
Year Published:
2021
Citation:
Christhel Sonia Jesugnon Padonou. 2021. Tracking and assessing the socio-economic impacts of conservation funding in Benin over the long term. MS Thesis, Department of Natural Resources and Environmental Sciences, University of Illinois.
|
Progress 10/01/19 to 09/30/20
Outputs
Target Audience:During this fourth reporting period, we reached at least fifty people from different audiences, notably international audiences at the World Bank, IUFRO, the World Agroforestry Center (ICRAF) and the Indian Forest Service, but also the academic research community and the general public as follows: About 25 people at the World Bank in Washington, DC for a seminar on "Do Forest Property Rights Interventions Reduce Poverty? Results from a Systematic Literature Review" in October 2019. Twenty people as a workshop participant and Chair, Meeting of the Global Expert Panel on Forests and Poverty, January 2020. International Union of Forest Research Organizations (IUFRO) andICRAF, Nairobi, Kenya. At least tenpeople through meetings at the Indian Forest Service on the idea of predictive proxy indicators (October-December 2019). Finally, social media posts related to the research and dissemination via article publication will have also reached broader audiences. Changes/Problems:There have been no major changes and we have been able to proceed largely as planned. However, the U.S.-focused work has been delayed due to negotiations over data sharing with the USFS and the University of Illinois. Remaining issues have been resolved and we will have the data as planned for the next period. We have also not been able to travel since February due to COVID-19 and this is beginning to hamper our work, notably by limiting options to disseminate it but also possible fieldwork in Southern Illinois and elsewhere in the U.S. What opportunities for training and professional development has the project provided?The project has supported post-graduate and graduate students who work closely with the project lead and other experts (e.g. the forestry Extension specialist at Dixon Springs for the University of Illinois and staff of the USFS) to advance their training and knowledge in several areas, notably in developing a framework and innovative analytical approach to identifying predictive proxy indicators for the long-term impacts of forest conservation and management interventions. The project has also supported professional development primarily in the form of participation in conferences/professional meetings. This includes participation by the PI and two post-docs in key relevant meetings. How have the results been disseminated to communities of interest?Results have been disseminated through one journal article (in review), one MS thesis, and several meetings with international organizations as described above, as well as through Twitter and other social media. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
Key impacts during this reporting period are further demonstrating the viability of the approach of using Predictive Proxy Indicators (PPIs) toassess the long-term social-ecological impacts of forest conservation and management, disseminating results from recent research and placement of two former project members in new positions where they will continue to promote and develop the approach. We have a new study (revised and resubmitted to World Development) demonstrating a novel approach to understanding long-term impacts of forest plantations. This approach combined process-tracing and qualitative comparative analysis to identify a set of PPIs that explained observed long-term vegetation growth trajectories public forest plantations in the Indian Himalaya. It has broad relevance to forest plantations in other contexts, including parts of the United States. We found that PPIs relating to strong property rights and local livelihood benefits, community-led monitoring and enforcement, and higher intermediate tree growth outcomes, together, led to successful long-term plantation outcomes, including more tree cover and socio-economic benefits for local communities. The causal pathways identified in this study suggest that measuring and comparing indicator values in specific contexts can help to assess the likelihood and directionality of long-term social and ecological outcome trajectories for forest plantations. We have engaged with important international audiences (e.g. World Bank, IUFRO, ICRAF-World Agroforestry Center, and the Indian Forest Service) regarding this work and work already completed under this project, which can thereby amplify its ultimate impacts. A near-term impact of this project is support for two post-docs, one who has left to take a senior position in the Indian Forest Serviceand another who joined during this reporting period, and three graduate students as research assistants. One graduate student completed her MS thesis, graduated and now has a staff positionat IUFRO, where she will continue to work on issues related to this project. The first post-doc has also promoted the idea of PPIs in the Indian Forest Service and, given his experience and seniority, it is likely to be used in within that agency. Finally, we have completed a formal MOU with the USFS to use data from their Forest Inventory and Analysis (FIA) and National Woodland Owner Survey (NWOS) to apply the approaches tested in India to the U.S. context. Accomplishments - Objective 1: To develop an analytical approach for assessing the long-term social-ecological impacts of forest conservation and management and empirically validating PPIs. Major Activities Completed: 1) Revised and resubmitted paper on a novel approach to identify a set of PPIs that explained observed long-term vegetation growth trajectories public forest plantations in the Indian Himalaya, and 2) Completion of MS thesis on role of funding and gender in explaining long-term forest conservation outcomes in Bhutan. 2) Data Collected: We compiled a database of geo-spatial information on variables that may be PPIs or affect how PPIs operate in context. The database includes various social and biophysical factors for 202 forest management units in a large area of northern India. We also collected survey data in the field from 23 different forest plantations, which has led to a database we used in the study we have discussed above. Interviews with key conservation actors in Bhutan were conducted and transcribed to form the basis of the MS thesis.We have also collected data on similar variables for forest landowners in Southern Indiana and Southern Illinois. We expect to expand this to the whole United States during the next reporting period. 3) Summary Statistics and Discussion of Results: Results have been described under impacts above. 4) Key Outcomes or Other Accomplishments Realized: We have raised awareness of this work among academic audiences, policymakers, and the public in the U.S. and internationally and produced two publications as well as helping to support the graduate education of three students and the research of two post-docs. Accomplishments - Objective 2: To use the approach in specific geographic and programmatic contexts in the United States and abroad to empirically validate a set of PPIs. 1) Major Activities Completed: 1) We validated a set of PPIs inNorthern India based on survey data in the field from 23 different forest plantations,2) Collected interview and secondary data in Bhutan for the MS thesis as described above,and 3) Have access to USFS NWOS data as mentioned above that can be used to realize Objective 2. 2) Data Collected: Same as described under Objective 1 as well as the NWOS data. 3) Summary Statistics and Discussion of Results: The India study demonstrated that secure community property rights and level of monitoring and supervision in the near- or medium-term after tree planting, together, can together act as a potential PPI cluster to provide understanding of long term vegetation trajectories in that context. By contrast, the lack of secure community property rights, lack of community participation in the choice of planted tree species, inadequate maintenance after planting trees, and the absence of community-led monitoring were PPIs for degraded forest landscapes. 4) Key Outcomes or Other Accomplishments Realized: Same as Objective 1.
Publications
- Type:
Other
Status:
Under Review
Year Published:
2020
Citation:
Rana, P. and D.C. Miller. 2020. Predicting the long-term social and ecological impacts of tree planting programs: Evidence from northern India. World Development (Revision in Review).
- Type:
Theses/Dissertations
Status:
Published
Year Published:
2020
Citation:
Devkota, Dikshya. 2020. Understanding biodiversity conservation funding and the diffusion of transnational gender norms in Bhutan. MS thesis. Department of Natural Resources and Environmental Sciences. University of Illinois at Urbana-Champaign.
|
Progress 10/01/18 to 09/30/19
Outputs
Target Audience:During this third reporting period, we reached at least fifty people from different audiences, including the U.S. Forest Service, the academic research community, policymakers, and the general public as follows: About 25 people at theForests and Livelihoods: Assessment, Research, and Engagement (FLARE)Network Conference inCopenhagen, Denmark in a presentationon "Predicting long-term social and ecological impacts of forest plantations in the Indian Himalayas." Four people at U.S. Forest Service in the Northern Research Station and theNational Woodland Owner Survey through teleconferences and in-person meetings. Twenty people as a workshop participant and Chair, Meeting of the GlobalExpert Panel on Forests and Poverty, August 2019.International Union of Forest Research Organizations (IUFRO), Ann Arbor, MI.. Research results were also disseminated to reach broader audiences through a press release, which was picked up by at least sixdifferent audiences, including a feature-length article in Mongabay:https://india.mongabay.com/2019/02/artificial-intelligence-spotlights-the-importance-of-forest-communities-in-afforestation/. One published paper (in Environmental Research Letters) ranks in the top 5%of all research outputs scored by Altmetric, a widely used indicator for the attention research receives. Finally, social media posts related to the research and dissemination via article publication will have also reached broader audiences. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?The project has supported post-graduate and graduate students who work closely with the project lead and other experts (e.g.the forestry Extension specialist at Dixon Springs for the University of Illinois) to advance their training and knowledge inseveral areas, notably in developing a framework and innovative analytical approach to identifying predictive proxy indicatorsfor the long-term impacts of forest conservation and management interventions.The project has also supported professional development primarily in the form of participation in conferences/professionalmeetings. This includes participation by the PI and a post-doc in key relevant meetings. How have the results been disseminated to communities of interest?Results have been communicated through two peer-reviewed journal articles, onemeetingwith the U.S. Forest Service and one with the IndianForest Service staff, and two international conferences, as well as through twitter and othersocial media. Research results were also highlighted in a press release that was picked up by at least sixdifferent international news outlets. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
Key impacts during this reporting period are through two major publications demonstrating feasibility of the approach we are developing for predicting and understand long term impacts in the forestry sector.We have now developed and tested the approach in the context of the Indian Himalaya and plan to extend it to other locations even as we also deepen its application in the Indian Himalaya. Research results were also disseminated to reach broader audiences through a press release, which was picked up by at least sixdifferent news organizations, including a feature-length article in Mongabay:https://india.mongabay.com/2019/02/artificial-intelligence-spotlights-the-importance-of-forest-communities-in-afforestation/. One published paper (in Environmental Research Letters) ranks in the top 5%of all research outputs scored by Altmetric, a widely used indicator for the attention research receives. To advance knowledge of long-term impacts and tools to help understand them, we have made major progress in using new artificial intelligence (machine learning) tools to shed light on the causal impacts of community forest management in the Indian Himalaya.We found that neither of the two programs we evaluated (using a Causal Tree approach) had a major impact on tree cover on average, but there was important heterogeneity in effects conditional on local contextual conditions.Knowledge of this heterogeneity can be used to help decision makers and forest program designers to better tailor programs to have more positive effects.The significance of this work is that it demonstrates that machine learning approaches can make a valuable contribution to understanding natural resource policy and that it is increasingly possible to use them in this field. Our approach can be applied in other contexts around the world and we have developed a proposal to USDA to extend it to the U.S. to look at the impacts of private family forest landowner participation in forest management programs. Another major advance in this work was development of an approach to analyzing long-term outcome trajectories in social-ecological systems (SESs). Again, we demonstrated this approach using data from the Indian Himalaya. We used a SES framework to identify a set of factors likely to shape long-term ecological outcome trajectories in the region. We then charted observed outcome trajectories over a fifteen-year period and constructed structural counterfactuals for these trajectories using new statistical approaches (nested optimization procedures developed for synthetic control matching) to identify key factors predictive of long-term ecological outcomes. The approach was highly successful in identifying these factors and explaining outcomes over this relatively long-term period.No single factor was crucial, but instead a series of biophysical (e.g. baseline vegetation, temperature, soil quality) and socioeconomic (e.g. number of households and level of literacy) factors explained observed outcomes for each year during the study period. Results suggest that our approach can enable identification of critical enabling factors for long-term ecological and social outcome trajectories in other SESs. Such knowledge can contribute to theoretical and empirical understanding of sustainable governance in SESs and help inform policies to improve livelihoods and conservation outcomes. A near-term impact of this project is support for one post-doc and two graduate students. Finally, a key outcome is that we have used our experience working with data from the Indian Himalaya to develop more general approaches that we have now proposed for application in the U.S. and elsewhere.Specifically, we have submitted to other research proposals on this topic, one was successfully funded for Benin and the other is in development for resubmission to USDA-NIFA and would support application of our approach to Illinois and nationally in the US. Related to this work we have established a formal MOU with the USFS to use data from theirForest Inventory and Analysis (FIA) and National Woodland Owner Survey (NWOS). Accomplishments - Objective 1:To develop an analytical approach for assessing the long-term social-ecological impacts of forest conservation and management and empirically validating PPIs. 1) Major Activities Completed:1) Publishing a paper on novel methods for causal impact evaluation in the forest sector (machine learning based causal trees); and 2) Publishing a paper on approach for analyzing long-term outcome trajectories in social-ecological systems. 2) Data Collected:We compiled a database of geo-spatial information on variables that may be PPIs or affect how PPIs operate in context. The database includes various social and biophysical factors for 202 forest management units in a large area of northern India.We have also collected data on similar variables for forest landowners in Southern Indiana and Southern Illinois.We expect to expand this to the whole United States during the next reporting period. 3) Summary Statistics and Discussion of Results: Results have been described under impacts above. 4) Key Outcomes or Other Accomplishments Realized: We have raised awareness of this work among academic audiences, policymakers, and the public in the U.S. and internationally and produced two peer-reviewed journal articles as well as helping to support the graduate education of one student and the research of one post-doc. Accomplishments - Objective 2:To use the approach in specific geographic and programmatic contexts in the United States and abroad to empirically validate a set of PPIs. 1) Major Activities Completed: 1) We collected data from the Northern India context as described above and have begun to collect data from southern Illinois and southern Indiana; 2) We also collected survey data in the field from 23 different forest plantations, which has led to a database and working paper; and 3) The social ecological system/synthetic control matching approach we developed as led to identification of what look to be PPIs in the northern India context (see impact statement above and below and published paper). 2) Data Collected: Same as described under Objective 1 as well as additional data from 23 forest plantation areas in Northern India. 3) Summary Statistics and Discussion of Results: Potential predictive proxy indicators identified through the India case study are as follows.The numberof households and level of literacy in forest management areas were the social factors with the highest ability to predict the observed vegetation growth trajectories.Population and livelihood changes in the region over the past two decades suggest a shift toward lower dependence on agriculture and forests, which may help explain increasing vegetation growth.Governance factors were also important in predicting positive vegetation outcome trajectories in the region. Together, our three governance indicators - forest area planted, percentage of broadleaf species planted, and number of nurseries - predicted 8% of the vegetation change seen over the study period.Greater community involvement in forest management led to local support that has ultimately spurred positive vegetation growth trajectories in the region.Finally, key biophysical predictors for the region were soil quality and baseline vegetation, which was thestrongest determinant of long-term positive vegetation growth. 4) Key Outcomes or Other Accomplishments Realized: As for Objective 1, we have raised awareness of this work and helped to support the graduate education of two students and the research of one post-doc.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Rana, P. and D.C. Miller. 2019. Machine Learning to Analyze the Social-Ecological Impacts of Natural Resource Policy: Insights from Community Forest Management in the Indian Himalaya. Environmental Research Letters. 14:2.
- Type:
Journal Articles
Status:
Published
Year Published:
2019
Citation:
Rana, P. and D.C. Miller. 2019. Explaining Long-Term Outcome Trajectories in Social⿿Ecological Systems. PLOS ONE. 14(4): e0215230.
|
Progress 10/01/17 to 09/30/18
Outputs
Target Audience:During this second reporting period, we reached more than 130 people from different audiences, including the U.S. Forest Service, the academic research community, and the general public, as follows: About 30 people at the 2018 World Congress of Environmental and Resource Economists in Gothenberg, Sweden in June 2018 on "Explaining long-term outcome trajectories in social-ecological systems." 4 people at U.S. Forest Service in the Northern Research Station and the National Woodland Owner Survey through teleconferences and in-person meetings. About 50 People in oral and poster presentations at the Bloomberg Data for Good Exchange Conference, September 2018, New York City (on Machine Learning to Analyze the Social-Ecological Impacts of Natural Resource Policy and Network Analysis as a Tool for Shaping Conservation and Development Policy, both based on cases studies of forest management from northern India). About 60 people through presentations in July 2018 at the two leading universities in Benin on the long-term socio-economic impacts of conservation funding for forest protected areas in Benin. In addition, social media posts related to the research and dissemination via article publication will have also reached broader audiences. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?The project has supported a post-graduate and a graduate student to work closely with the project lead and other experts (e.g. the head of the National Woodland Owner Survey from the USFS and the forestry Extension specialist at Dixon Springs for the University of Illinois) to advance their training and knowledge in several areas, notably in developing a framework and innovative analytical approach to identifying predictive proxy indicators for the long-term impacts of forest conservation and management interventions. The project has also supported professional development primarily in the form of participation in conferences/professional meetings. This includes participation by the PI, post-doc and graduate student in key relevant meetings. How have the results been disseminated to communities of interest?Results have been communicated through three peer-reviewed journal articles (one published, two in review), two meetings with U.S. forest service staff,one international conference, one domestic conference, and two invited international seminars as well as through social media. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
This reporting period covers the first full year of the project and we have made substantial progress. Key impacts are through publications and we expect this to be more substantial in the next reporting period as two major publications are completed but still under review at the time of reporting. We published a major review on protected areas and the sustainable governance of forest resources, which synthesized current knowledge on long-term impacts of different kinds of protected areas. We found that quantitative impact evaluations link protected area governance to conservation and human well-being outcomes, but that qualitative studies provide detailed analysis of governance dimensions without linking it to outcomes. Neither literature devotes significant attention to impacts over long time periods, highlighting the continued need for research on this topic. To advance knowledge of long-term impacts and tools to help understand them, we have made major progress in using new artificial intelligence (machine learning) tools to shed light on the causal impacts of community forest management in the Indian Himalaya. We found that neither of the two programs we evaluated (using Causal Tree approach) had a major impact on tree cover on average, but there was important heterogeneity in effects conditional on local contextual conditions. Knowledge of this heterogeneity can be used to help decision-makers and forest program designers to better tailor programs to have more positive effects. The significance of this work is that it demonstrates that machine learning approaches can make a valuable contribution to understanding natural resource policy and that it is increasingly possible to use them in this field. Our approach can be applied in other contexts around the world and we have developed a proposal to USDA to extend it to the U.S. to look at the impacts of private family forest landowner participation in forest management programs. Another major advance in this work was development of an approach to analyzing long-term outcome trajectories in social-ecological systems (SESs). Again, we demonstrated this approach using data from the Indian Himalaya. We used a SES framework to identify a set of factors likely to shape long-term ecological outcome trajectories in the region. We then charted observed outcome trajectories over a 15-year period and constructed structural counterfactuals for these trajectories using new statistical approaches (nested optimization procedures developed for synthetic control matching) to identify key factors predictive of long-term ecological outcomes. The approach was highly successful in identifying these factors and explaining outcomes over this relatively long-term period. No single factor was crucial, but instead a series of biophysical (e.g. baseline vegetation, temperature, soil quality) and socioeconomic (e.g. number of households and level of literacy) factors explained observed outcomes for each year outcomes for each year during the study period. Results suggest that our approach can enable identification of critical enabling factors for long-term ecological and social outcome trajectories in other SESs. Such knowledge can contribute to theoretical and empirical understanding of sustainable governance in SESs and help inform policies to improve livelihoods and conservation outcomes. A near-term impact of this project is support for one post-doc and one graduate student. Finally, a key outcome is that we have used our experience working with data from the Indian Himalaya to develop more general approaches that we have now proposed for application in the US and elsewhere. Specifically, we have submitted to other research proposals on this topic, one was successfully funded for Benin and the other is in review at USDA-NIFA and would support application of our approach to Illinois and nationally. Accomplishments - Objective 1: To develop an analytical approach for assessing the long-term social-ecological impacts of forest conservation and management and empirically validating PPIs. 1) Major activities completed: 1) publishing of review on protected areas and sustainable governance of forest resources; 2) completion of paper on novel method for causal impact evaluation in the forest sector (machine learning based causal trees), which is now in review and; 3) completion of paper on approach for analyzing long-term outcome trajectories in social-ecological systems now also in review. 2) Data collected: We identified 40 relevant studies under activity 1 and compiled them in one database. For activities 2 and 3, we used the same basic database. Given personal connections and long in-situ research experience of the post-doc working on this project, Dr. Pushpendra Rana, who has held senior positions in the Indian Forest service, we have collected a wealth of geo-spatial data on variables that may be PPIs or affect how PPIs operate in context. These have been compiled in a database of various social and biophysical factors for 202 forest management units in a large area of northern India. We have also begun to collect data on similar variables for forest landowners in Southern Indiana and Southern Illinois. We expect to expand this to the whole United States during the next reporting period. 3) Summary statistics and discussion of results: Results for each of these three activities have been described under impacts above. 4) Key outcomes or other accomplishments realized: We have raised awareness of this work among academic audiences and produced one peer-reviewed journal article as well as helping to support the graduate education of one student and the research of one post-doc. Accomplishments - Objective 2: To use the approach in specific geographic and programmatic contexts in the United States and abroad to empirically validate a set of PPIs. 1) Major activities completed: 1) we collected data from the Northern India context as described above and have begun to collect data from southern Illinois and southern Indiana; 2) the social ecological system/synthetic control matching approach we developed has led to identification of what look to be PPIs in the northern India context (see impact statement above and below). The paper on this topic is in review. 2) Data collected: Same as activities 2 and 3 described under Objective 1. 3) Summary statistics and discussion of results: Potential predictive proxy indicators identified through the India case study are as follows. The number of households and level of literacy in forest management areas were the social factors with the highest ability to predict the observed vegetation growth trajectories. Population and livelihood changes in the region over the past two decades suggest a shift toward lower dependence on agriculture and forests, which may help explain increasing vegetation growth. Governance factors were also important in predicting positive vegetation outcome trajectories in the region. Together, our three governance indicators--forest area planted, percentage of broadleaf species planted, and number of nurseries--predicted 8% of the vegetation change seen over the study period. Greater community involvement in forest management led to local support that has ultimately spurred positive vegetation growth trajectories in the region. Finally, key biophysical predictors for the region were soil quality and baseline vegetation, which was the strongest determinant of long-term positive vegetation growth. 4) Key outcomes or other accomplishments realized: As for Objective 1, we have raised awareness of this work and helped to support the graduate education of two students and the research of one post-doc.
Publications
- Type:
Conference Papers and Presentations
Status:
Published
Year Published:
2018
Citation:
Rana P. and D.C. Miller. 2018. Machine Learning to Analyze the Social-Ecological Impacts of Natural Resource Policy: Insights from Community Forest Management in the Indian Himalaya. Conference Proceeding: Bloomberg Data for Good Exchange Conference. 16-Sep-2018, New York City, NY, USA.
- Type:
Journal Articles
Status:
Published
Year Published:
2018
Citation:
Miller, D.C. and Katia S. Nakamura. 2018. Protected Areas and the Sustainable Governance of Forest Resources. Current Opinion in Environmental Sustainability. 32: 96-103.
- Type:
Journal Articles
Status:
Under Review
Year Published:
2019
Citation:
Rana, P. and D.C. Miller. 2019. Machine Learning to Analyze the Social-Ecological Impacts of Natural Resource Policy: Insights from Community Forest Management in the Indian Himalaya. Environmental Research Letters.
- Type:
Journal Articles
Status:
Under Review
Year Published:
2019
Citation:
Rana, P. and D.C. Miller. 2019. Explaining Long-Term Outcome Trajectories in SocialEcological Systems. PLOSONE.
|
Progress 02/28/17 to 09/30/17
Outputs
Target Audience:During this first reporting period, we reached primarily academic audiences, as well as some professionals and other forest stakeholders. The total number of people directly reached is estimated to be at about 100 as follows: 35 people at the American Association of Geographers Annual Meeting, Boston, April 2017 (on predictive proxy indicators in the forestry sector). 60 people at symposium on "Critically examining 'success': Developing inter-disciplinary approaches to measuring conservation outcomes" at the 2017 International Congress for Conservation Biology (ICCB 2017) in Cartagena, Colombia (on predictive proxy indicators) 4 people at the U.S. Forest Service in Shawnee National Forest and Chicago office and 5 people in Indian Forest Service (August 2017). Social media posts related to the research and dissemination via article publication will have also reached broader audiences. Changes/Problems:
Nothing Reported
What opportunities for training and professional development has the project provided?The project has supported post-graduate and graduate students to work closely with the project lead and other experts (e.g. the forestry Extension specialist at Dixon Springs for the University of Illinois) to advance their training and knowledge in several areas, notably in developing a framework and innovative analytical approach to identifying predictive proxy indicators for the long-term impacts of forest conservation and management interventions. The project has also supported professional development primarily in the form of participation in conferences/professional meetings. This includes participation by the PI and a post-doc in key relevant meetings. How have the results been disseminated to communities of interest?Results have been communicated through onepeer-reviewed journal article, twomeetings with U.S. forest service and Indian Forest Service staff, and twointernational conferences, as well as through twitter and associated social media. What do you plan to do during the next reporting period to accomplish the goals?
Nothing Reported
Impacts
What was accomplished under these goals?
This is the first reporting period for this work covering less than a year so there are no major impacts to report yet. We are expecting major impacts primarily through publications in the next reporting period when we plan to have published the first full-length conceptual paper on the predictive proxy indicators (PPI) concept as well as a paper outlining our innovative methods for testing PPIs empirically. During this period, we published the first short description of the idea of PPIs in the peer-reviewed literature. Through consultation and feedback (see audiences reached section of this report), we increasingly see how important PPIs (for example, if a forest landowner has a forest management plan and, after some time, has actually implemented some key activities within it) can be as a tool for decision-makers in the forestry sector who must justify use of funds to various stakeholders. The reason the tool is useful is that it can provide credible near-term information about the likely benefits of a give intervention even though the benefits may not fully accrue until a longer-time has passed. Funding under this project will be central to developing and validating this tool. A near-term impact of this project is support for onePost-doc and two graduate students (oneMS and one PhD). Accomplishments - Objective 1: To develop an analytical approach for assessing the long-term social-ecological impacts of forest conservation and management and empirically validating PPIs. 1) Major activities completed: 1) publishing of first peer-reviewed description of PPIs and situtating the approach among others as a potential solution to the dilemma of how to track and assess long term impacts in the forestry sector; 2) draft conceptual paper on PPIs for submission to a journal in early 2018; 3) analytical approach using synthetic control matching and machine learning to empirically validate PPIs has been developed and a paper describing it with an illustration from the Indian Himalaya context has been drafted. Publication expected in 2018. 2) Data collected: Given personal connections and long in-situ research experience of the post-doc working on this project, Dr. Pushpendra Rana, who has held senior positions in the Indian Forest service, we have collected a wealth of geo-spatial data on variables that may be PPIs or affect how PPIs operate in context. We have compiled a dataset on biophysical features, demographic, social, economic, and political variables for 202 forest management units in a large area of northern India. These data are being used to perform the first empirical test of select PPIs including security of property rights, participation by communities affected, and sustainable financing. We have also begun to collect data on similar variables for forest landowners in Southern Indiana and Southern Illinois. The next phase of the project will look at PPIs in those contexts using the approach tested in northern India. 3) Summary statistics and discussion of results: Results from this research remain largely preliminary given that it's still an early stage. However, for the Activity 1 above we found that very little attention has been paid to assessing longer-term impacts in the literature on forest policy/impact assessment. This finding further supports the need for research under the current project. 4) Key outcomes or other accomplishments realized: We have raised awareness of this work among academic audiences and produced one peer-reviewed journal article as well as helping to support the graduate education of two students and the research of one post-doc. Accomplishments - Objective 2: To use the approach in specific geographic and programmatic contexts in the United States and abroad to empirically validate a set of PPIs. 1) Major activities completed: 1) we collected data from the northern India context as described above and have begun to collect data from southern Illinois and southern Indiana; 2) draft of first empirical test of the PPI valdation approach has been completed and we expect this to be published in 2018. 2) Data collected: Same as described under Objective 1. 3) Summary statistics and discussion of results: Preliminary results are emerging that the method we developed is effective in testing PPIs and we've identified participation in decision making relating to reforestation efforts as likely a key predictive indicator. However, this remains to be confirmed as we move forward with this work in the next year. 4) Key outcomes or other accomplishments realized: As for Objective 1, we have raised awareness of this work among academic audiences helped to support the graduate education of two students and the research of one post-doc.
Publications
- Type:
Journal Articles
Status:
Published
Year Published:
2017
Citation:
Miller, D.C., C.B. Wahl�n and P. Rana. 2017. A Crystal Ball for Forests? Analyzing the Social-Ecological Impacts of Forest Conservation and Management over the Long Term. Environment and Society: Advances in Research. 8: 40-62.
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