Statistical matching for conservation science

The awareness of the need for robust impact evaluations in conservation is growing and statistical matching techniques are increasingly being used to assess the impacts of conservation interventions. Used appropriately matching approaches are powerful tools, but they also pose potential pitfalls. We outlined important considerations and best practice when using matching in conservation science. We identified 3 steps in a matching analysis. First, develop a clear theory of change to inform selection of treatment and controls and that accounts for real‐world complexities and potential spillover effects. Second, select the appropriate covariates and matching approach. Third, assess the quality of the matching by carrying out a series of checks. The second and third steps can be repeated and should be finalized before outcomes are explored. Future conservation impact evaluations could be improved by increased planning of evaluations alongside the intervention, better integration of qualitative methods, considering spillover effects at larger spatial scales, and more publication of preanalysis plans. Implementing these improvements will require more serious engagement of conservation scientists, practitioners, and funders to mainstream robust impact evaluations into conservation. We hope this article will improve the quality of evaluations and help direct future research to continue to improve the approaches on offer.Peer reviewe

Quantifying uncertainty about how interventions are assigned would improve impact evaluation in conservation: reply to Rasolofoson 2022

Non peer reviewe

A global analysis of the social and environmental outcomes of community forests

Community forest management (CFM) has been promoted for decades as a way to merge environmental conservation with economic development and natural resource rights agendas. Yet many of these initiatives have also led to substantial socioeconomic and environmental trade-offs. We present a comprehensive global analysis of environmental, income and natural resource rights outcomes of CFM, using data from 643 cases in 51 countries. We find that while the majority of cases reported positive environmental and income-related outcomes, forest access and resource rights were often negatively affected by policies to formalize CFM, countering one of CFM&rsquo;s principal goals. Positive outcomes across all three dimensions were rare. We show that biophysical conditions, de facto tenure rights, national context, user-group characteristics and intervention types are key predictors of joint positive outcomes. These findings highlight key conducive conditions for CFM interventions, which can inform CFM design to ensure positive outcomes across multiple sustainability dimensions. </section

Contextual Factors Shaping Forest-Poverty Dynamics

This report, titled “Forests, Trees and the Eradication of Poverty: Potential and Limitations”, presents the results of the seventh global scientific assessment undertaken so far within the framework of GFEP. All assessment reports are prepared by internationally recognised scientists from a variety of biophysical and social science disciplines. The publications are presented to stakeholders across relevant international policy fora. In this way, GFEP supports a more coherent policy dialogue about the role of forests in addressing the broader environmental, social and economic challenges reflected in the United Nations Sustainable Development Goals (SDGs). Poverty is one of the greatest challenges facing humanity. Globally, one out of every 10 people lives in extreme poverty. Poverty eradication has therefore found a place at the top of the United Nations 2030 Agenda for Sustainable Development. “End poverty in all its forms everywhere” is the first Goal of this Agenda, which is supported by all 193 UN member states. The international community is now stepping up efforts to achieve this goal, especially in response to the severe setback caused by the Covid-19 pandemic. The zoonotic nature of the Covid-19 virus has also illustrated the urgency to reduce human pressure on nature

Assessing multidimensional sustainability : lessons from Brazil’s social protection programs

Examining linkages among multiple sustainable development outcomes is key for understanding sustainability transitions. Yet rigorous evidence on social and environmental outcomes of sustainable development policies remains scarce. We conduct a national-level analysis of Brazil’s flagship social protection program, Zero Hunger (ZH), which aims to reduce food insecurity and poverty. Using data from rural municipalities across Brazil and quasi-experimental causal inference techniques, we assess relationships between social protection investment and outcomes related to sustainable development goals (SDGs): "no poverty" (SDG 1), "zero hunger" (SDG 2), and "health and well being" (SDG 3). We also assess potential perverse outcomes arising from agricultural development impacting "climate action" (SDG 13) and "life on land" (SDG 15) via clearance of natural vegetation. Despite increasing daily per capita protein and kilocalorie production, summed ZH investment did not alleviate child malnutrition or infant mortality and negligibly influenced multidimensional poverty. Higher investment increased natural vegetation cover in some biomes but increased losses in the Cerrado and especially the Pampa. Effects varied substantially across subprograms. Conditional cash transfer (Bolsa Familia [BF]) was mainly associated with nonbeneficial impacts but increased protein production and improved educational participation in some states. The National Program to Strengthen Family Farming (PRONAF) was typically associated with increased food production (protein and calories), multidimensional poverty alleviation, and changes in natural vegetation. Our results inform policy development by highlighting successful elements of Brazil’s ZH program, variable outcomes across divergent food security dimensions, and synergies and trade-offs between sustainable development goals, including environmental protection

Forest-linked livelihoods in a globalized world.

Forests have re-taken centre stage in global conversations about sustainability, climate and biodiversity. Here, we use a horizon scanning approach to identify five large-scale trends that are likely to have substantial medium- and long-term effects on forests and forest livelihoods: forest megadisturbances; changing rural demographics; the rise of the middle-class in low- and middle-income countries; increased availability, access and use of digital technologies; and large-scale infrastructure development. These trends represent human and environmental processes that are exceptionally large in geographical extent and magnitude, and difficult to reverse. They are creating new agricultural and urban frontiers, changing existing rural landscapes and practices, opening spaces for novel conservation priorities and facilitating an unprecedented development of monitoring and evaluation platforms that can be used by local communities, civil society organizations, governments and international donors. Understanding these larger-scale dynamics is key to support not only the critical role of forests in meeting livelihood aspirations locally, but also a range of other sustainability challenges more globally. We argue that a better understanding of these trends and the identification of levers for change requires that the research community not only continue to build on case studies that have dominated research efforts so far, but place a greater emphasis on causality and causal mechanisms, and generate a deeper understanding of how local, national and international geographical scales interact.This work was funded by the UK’s Department for International Development (grant number 203516-102) and governed by the University of Michigan’s Institutional Review Board (HUM00092191). JAO acknowledges the 520 support of a European Union FP7 Marie Curie international outgoing fellowship (FORCONEPAL). LVR was funded by the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme (Grant agreement No. 853222 FORESTDIET). AJB acknowledges the support of an Australian Research Council Australia Laureate Fellowship (grant number 525 FL160100072). LBF acknowledges support from the European Union Marie Curie global fellowship (CONRICONF). PM was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (Grant agreement No 677140 MIDLAND)

BIOFRAG: A new database for analysing BIOdiversity responses to forest FRAGmentation

Habitat fragmentation studies are producing inconsistent and complex results across which it is nearly impossible to synthesise. Consistent analytical techniques can be applied to primary datasets, if stored in a flexible database that allows simple data retrieval for subsequent analyses. Method: We developed a relational database linking data collected in the field to taxonomic nomenclature, spatial and temporal plot attributes and further environmental variables (e.g. information on biogeographic region. Typical field assessments include measures of biological variables (e.g. presence, abundance, ground cover) of one species or a set of species linked to a set of plots in fragments of a forested landscape. Conclusion: The database currently holds records of 5792 unique species sampled in 52 landscapes in six of eight biogeographic regions: mammals 173, birds 1101, herpetofauna 284, insects 2317, other arthropods: 48, plants 1804, snails 65. Most species are found in one or two landscapes, but some are found in four. Using the huge amount of primary data on biodiversity response to fragmentation becomes increasingly important as anthropogenic pressures from high population growth and land demands are increasing. This database can be queried to extract data for subsequent analyses of the biological response to forest fragmentation with new metrics that can integrate across the components of fragmented landscapes. Meta-analyses of findings based on consistent methods and metrics will be able to generalise over studies allowing inter-comparisons for unified answers. The database can thus help researchers in providing findings for analyses of trade-offs between land use benefits and impacts on biodiversity and to track performance of management for biodiversity conservation in human-modified landscapes.Fil: Pfeifer, Marion. Imperial College London; Reino UnidoFil: Lefebvre, Veronique. Imperial College London; Reino UnidoFil: Gardner, Toby A.. Stockholm Environment Institute; SueciaFil: Arroyo Rodríguez, Víctor. Universidad Nacional Autónoma de México; MéxicoFil: Baeten, Lander. University of Ghent; BélgicaFil: Banks Leite, Cristina. Imperial College London; Reino UnidoFil: Barlow, Jos. Lancaster University; Reino UnidoFil: Betts, Matthew G.. State University of Oregon; Estados UnidosFil: Brunet, Joerg. Swedish University of Agricultural Sciences; SueciaFil: Cerezo Blandón, Alexis Mauricio. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Métodos Cuantitativos y Sistemas de Información; ArgentinaFil: Cisneros, Laura M.. University of Connecticut; Estados UnidosFil: Collard, Stuart. Nature Conservation Society of South Australia; AustraliaFil: D´Cruze, Neil. The World Society for the Protection of Animals; Reino UnidoFil: Da Silva Motta, Catarina. Ministério da Ciência, Tecnologia, Inovações. Instituto Nacional de Pesquisas da Amazônia; BrasilFil: Duguay, Stephanie. Carleton University; CanadáFil: Eggermont, Hilde. University of Ghent; BélgicaFil: Eigenbrod, Félix. University of Southampton; Reino UnidoFil: Hadley, Adam S.. State University of Oregon; Estados UnidosFil: Hanson, Thor R.. No especifíca;Fil: Hawes, Joseph E.. University of East Anglia; Reino UnidoFil: Heartsill Scalley, Tamara. United State Department of Agriculture. Forestry Service; Puerto RicoFil: Klingbeil, Brian T.. University of Connecticut; Estados UnidosFil: Kolb, Annette. Universitat Bremen; AlemaniaFil: Kormann, Urs. Universität Göttingen; AlemaniaFil: Kumar, Sunil. State University of Colorado - Fort Collins; Estados UnidosFil: Lachat, Thibault. Swiss Federal Institute for Forest; SuizaFil: Lakeman Fraser, Poppy. Imperial College London; Reino UnidoFil: Lantschner, María Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Patagonia Norte. Estación Experimental Agropecuaria San Carlos de Bariloche; ArgentinaFil: Laurance, William F.. James Cook University; AustraliaFil: Leal, Inara R.. Universidade Federal de Pernambuco; BrasilFil: Lens, Luc. University of Ghent; BélgicaFil: Marsh, Charles J.. University of Leeds; Reino UnidoFil: Medina Rangel, Guido F.. Universidad Nacional de Colombia; ColombiaFil: Melles, Stephanie. University of Toronto; CanadáFil: Mezger, Dirk. Field Museum of Natural History; Estados UnidosFil: Oldekop, Johan A.. University of Sheffield; Reino UnidoFil: Overal , Williams L.. Museu Paraense Emílio Goeldi. Departamento de Entomologia; BrasilFil: Owen, Charlotte. Imperial College London; Reino UnidoFil: Peres, Carlos A.. University of East Anglia; Reino UnidoFil: Phalan, Ben. University of Southampton; Reino UnidoFil: Pidgeon, Anna Michle. University of Wisconsin; Estados UnidosFil: Pilia, Oriana. Imperial College London; Reino UnidoFil: Possingham, Hugh P.. Imperial College London; Reino Unido. The University Of Queensland; AustraliaFil: Possingham, Max L.. No especifíca;Fil: Raheem, Dinarzarde C.. Royal Belgian Institute of Natural Sciences; Bélgica. Natural History Museum; Reino UnidoFil: Ribeiro, Danilo B.. Universidade Federal do Mato Grosso do Sul; BrasilFil: Ribeiro Neto, Jose D.. Universidade Federal de Pernambuco; BrasilFil: Robinson, Douglas W.. State University of Oregon; Estados UnidosFil: Robinson, Richard. Manjimup Research Centre; AustraliaFil: Rytwinski, Trina. Carleton University; CanadáFil: Scherber, Christoph. Universität Göttingen; AlemaniaFil: Slade, Eleanor M.. University of Oxford; Reino UnidoFil: Somarriba, Eduardo. Centro Agronómico Tropical de Investigación y Enseñanza; Costa RicaFil: Stouffer, Philip C.. State University of Louisiana; Estados UnidosFil: Struebig, Matthew J.. University of Kent; Reino UnidoFil: Tylianakis, Jason M.. University College London; Estados Unidos. Imperial College London; Reino UnidoFil: Teja, Tscharntke. Universität Göttingen; AlemaniaFil: Tyre, Andrew J.. Universidad de Nebraska - Lincoln; Estados UnidosFil: Urbina Cardona, Jose N.. Pontificia Universidad Javeriana; ColombiaFil: Vasconcelos, Heraldo L.. Universidade Federal de Uberlandia; BrasilFil: Wearn, Oliver. Imperial College London; Reino Unido. The Zoological Society of London; Reino UnidoFil: Wells, Konstans. University of Adelaide; AustraliaFil: Willig, Michael R.. University of Connecticut; Estados UnidosFil: Wood, Eric. University of Wisconsin; Estados UnidosFil: Young, Richard P.. Durrell Wildlife Conservation Trust; Reino UnidoFil: Bradley, Andrew V.. Imperial College London; Reino UnidoFil: Ewers, Robert M.. Imperial College London; Reino Unid

BIOFRAG - a new database for analyzing BIOdiversity responses to forest FRAGmentation

Peer reviewe

BIOFRAG – a new database for analyzing BIOdiversity responses to forest FRAGmentation

Habitat fragmentation studies have produced complex results that are challenging to synthesize. Inconsistencies among studies may result from variation in the choice of landscape metrics and response variables, which is often compounded by a lack of key statistical or methodological information. Collating primary datasets on biodiversity responses to fragmentation in a consistent and flexible database permits simple data retrieval for subsequent analyses. We present a relational database that links such field data to taxonomic nomenclature, spatial and temporal plot attributes, and environmental characteristics. Field assessments include measurements of the response(s) (e.g., presence, abundance, ground cover) of one or more species linked to plots in fragments within a partially forested landscape. The database currently holds 9830 unique species recorded in plots of 58 unique landscapes in six of eight realms: mammals 315, birds 1286, herptiles 460, insects 4521, spiders 204, other arthropods 85, gastropods 70, annelids 8, platyhelminthes 4, Onychophora 2, vascular plants 2112, nonvascular plants and lichens 320, and fungi 449. Three landscapes were sampled as long-term time series (>10 years). Seven hundred and eleven species are found in two or more landscapes. Consolidating the substantial amount of primary data available on biodiversity responses to fragmentation in the context of land-use change and natural disturbances is an essential part of understanding the effects of increasing anthropogenic pressures on land. The consistent format of this database facilitates testing of generalizations concerning biologic responses to fragmentation across diverse systems and taxa. It also allows the re-examination of existing datasets with alternative landscape metrics and robust statistical methods, for example, helping to address pseudo-replication problems. The database can thus help researchers in producing broad syntheses of the effects of land use. The database is dynamic and inclusive, and contributions from individual and large-scale data-collection efforts are welcome.Keywords: Species turnover, Data sharing, Database, Global change, Landscape metrics, Edge effects, Forest fragmentation, Matrix contrast, Bioinformatic