Pathways framework identifies wildfire impacts on agriculture.

Wildfires are a growing concern to society and the environment in many parts of the world. Within the United States, the land area burned by wildfires has steadily increased over the past 40 years. Agricultural land management is widely understood as a force that alters fire regimes, but less is known about how wildfires, in turn, impact the agriculture sector. Based on an extensive literature review, we identify three pathways of impact-direct, downwind and downstream-through which wildfires influence agricultural resources (soil, water, air and photosynthetically active radiation), labour (agricultural workers) and products (crops and livestock). Through our pathways framework, we highlight the complexity of wildfire-agriculture interactions and the need for collaborative, systems-oriented research to better quantify the magnitude of wildfire impacts and inform the adaptation of agricultural systems to an increasingly fire-prone future.

Biases and limitations of Global Forest Change and author-generated land cover maps in detecting deforestation in the Amazon.

Studying land use change in protected areas (PAs) located in tropical forests is a major conservation priority due to high conservation value (e.g., species richness and carbon storage) here, coupled with generally high deforestation rates. Land use change researchers use a variety of land cover products to track deforestation trends, including maps they produce themselves and readily available products, such as the Global Forest Change (GFC) dataset. However, all land cover maps should be critically assessed for limitations and biases to accurately communicate and interpret results. In this study, we assess deforestation in PA complexes located in agricultural frontiers in the Amazon Basin. We studied three specific sites: Amboró and Carrasco National Parks in Bolivia, Jamanxim National Forest in Brazil, and Tambopata National Reserve and Bahuaja-Sonene National Park in Peru. Within and in 20km buffer areas around each complex, we generated land cover maps using composites of Landsat imagery and supervised classification, and compared deforestation trends to data from the GFC dataset. We then performed a dissimilarity analysis to explore the discrepancies between the two remote sensing products. Both the GFC and our supervised classification showed that deforestation rates were higher in the 20km buffer than inside the PAs and that Jamanxim National Forest had the highest deforestation rate of the PAs we studied. However, GFC maps showed consistently higher rates of deforestation than our maps. Through a dissimilarity analysis, we found that many of the inconsistencies between these datasets arise from different treatment of mixed pixels or different parameters in map creation (for example, GFC does not detect reforestation after 2012). We found that our maps underestimated deforestation while GFC overestimated deforestation, and that true deforestation rates likely fall between our two estimates. We encourage users to consider limitations and biases when using or interpreting our maps, which we make publicly available, and GFC's maps.

Integration of qualitative and quantitative methods for land-use-change modeling in a deforestation frontier.

Development and implementation of effective protected area management to reduce deforestation depend in part on identifying factors contributing to forest loss and areas at risk of conversion, but standard land-use-change modeling may not fully capture contextual factors that are not easily quantified. To better understand deforestation and agricultural expansion in Amazonian protected areas, we combined quantitative land-use-change modeling with qualitative discourse analysis in a case study of Brazil's Jamanxim National Forest. We modeled land-use change from 2008 to 2018 and projected deforestation through 2028. We used variables identified in a review of studies that modeled land-use change in the Amazon (e.g., variables related to agricultural suitability and economic accessibility) and from a critical discourse analysis that examined documents produced by different actors (e.g., government agencies and conservation nonprofit organizations) at various spatial scales. As measured by analysis of variance, McFadden's adjusted pseudo R2 , and quantity and allocation disagreement, we found that including variables in the model identified as important to deforestation dynamics through the qualitative discourse analysis (e.g., the proportion of unallocated public land, distance to proposed infrastructure developments, and density of recent fires) alongside more traditional variables (e.g., elevation, distance to roads, and protection status) improved the predictive ability of these models. Models that included discourse analysis variables and traditional variables explained up to 19.3% more of the observed variation in deforestation probability than a model that included only traditional variables and 4.1% more variation than a model with only discourse analysis variables. Our approach of integrating qualitative and quantitative methods in land-use-change modeling provides a framework for future interdisciplinary work in land-use change.

El desarrollo y la implementación de la gestión efectiva de las áreas protegidas para reducir la deforestación dependen parcialmente de la identificación de los factores que contribuyen a la pérdida del bosque y de las áreas en riesgo de ser convertidas, pero el modelado estándar del cambio de uso de suelo puede no capturar completamente los factores contextuales que no se cuantifican fácilmente. Combinamos el modelado cuantitativo del cambio de uso de suelo con el análisis cualitativo del discurso en un estudio de caso del Bosque Nacional Jamanxim de Brasil para entender de mejor manera la deforestación y la expansión agrícola en las áreas protegidas del Amazonas. Modelamos el cambio de uso de suelo entre 2008 y 2018 y lo proyectamos hasta 2028. Usamos las variables identificadas en una revisión de estudios que modelaron el cambio de uso de suelo en el Amazonas (p. ej.: variables relacionadas con la idoneidad agrícola y la accesibilidad económica) y en el análisis crítico del discurso que examinó documentos producidos por diferentes actores (p. ej.: agencias gubernamentales y organizaciones sin fines de lucro para la conservación) a varias escalas espaciales. Conforme a las medidas del análisis de varianza, la pseudo-R2 ajustada de McFadden y el desacuerdo en la cantidad y la asignación, descubrimos que la inclusión dentro del modelo de las variables identificadas como importantes para las dinámicas de deforestación mediante el análisis cualitativo del discurso (p. ej.: la proporción de terrenos públicos sin asignar, la distancia hacia los desarrollos propuestos de infraestructura y la densidad de incendios recientes) junto con variables más tradicionales (p. ej.: elevación, distancia a las carreteras y estado de protección) mejoró la habilidad predictiva de dichos modelos. Los modelos que incluyeron la mezcla de variables explicaron hasta 19.3% más de la variación observada en la probabilidad de deforestación que un modelo que solamente incluyó las variables tradicionales y 4.1% más variación que un modelo con las variables del análisis del discurso. Nuestra estrategia de integrar los métodos cualitativos y cuantitativos dentro del modelado del cambio de uso de suelo proporciona un marco para futuros trabajos interdisciplinarios sobre el cambio de uso de suelo.

Projected losses of ecosystem services in the US disproportionately affect non-white and lower-income populations.

Addressing how ecosystem services (ES) are distributed among groups of people is critical for making conservation and environmental policy-making more equitable. Here, we evaluate the distribution and equity of changes in ES benefits across demographic and socioeconomic groups in the United States (US) between 2020 and 2100. Specifically, we use land cover and population projections to model potential shifts in the supply, demand, and benefits of the following ES: provision of clean air, protection against a vector-borne disease (West Nile virus), and crop pollination. Across the US, changes in ES benefits are unevenly distributed among socioeconomic and demographic groups and among rural and urban communities, but are relatively uniform across geographic regions. In general, non-white, lower-income, and urban populations disproportionately bear the burden of declines in ES benefits. This is largely driven by the conversion of forests and wetlands to cropland and urban land cover in counties where these populations are expected to grow. In these locations, targeted land use policy interventions are required to avoid exacerbating inequalities already present in the US.

Approaches to interdisciplinary mixed methods research in land-change science and environmental management.

Combining qualitative and quantitative methods and data is crucial to understanding the complex dynamics and often interdisciplinary nature of conservation. Many conservation scientists use mixed methods, but there are a variety of mixed methods approaches, a lack of shared vocabulary, and few methodological frameworks. We reviewed articles from 2 conservation-related fields that often incorporate qualitative and quantitative methods: land-change science (n = 16) and environmental management (n = 16). We examined how authors of these studies approached mixed methods research by coding key methodological characteristics, including relationships between method objectives, extent of integration, iterative interactions between methods, and justification for use of mixed methods. Using these characteristics, we created a typology with the goal of improving understanding of how researchers studying land-change science and environmental management approach interdisciplinary mixed methods research. We identified 5 types of mixed methods approaches, which we termed simple nested, informed nested, simple parallel, unidirectional synthesis, and bidirectional synthesis. Methods and data sources were often used to address different research questions within a project, and only around half of the reviewed papers methodologically integrated different forms of data. Most authors used one method to inform the other, rather than both informing one another. Very few articles used methodological iteration. Each methodological type has certain epistemological implications, such as the disciplinary reach of the research and the capacity for knowledge creation through the exchange of information between distinct methodologies. To exemplify a research design that can lead to multidimensional knowledge production, we provide a methodological framework that bidirectionally integrates and iterates qualitative and quantitative methods.

Estrategias para la Investigación Interdisciplinaria con Métodos Mixtos en las Ciencias del Cambio de Suelo y el Manejo Ambiental Resumen La combinación entre los métodos cualitativos y cuantitativos y los datos es crucial para el entendimiento de las dinámicas complejas y con frecuencia, de la naturaleza interdisciplinaria de la conservación. Muchos científicos de la conservación usan métodos mixtos, aunque existe una variedad de estrategias de métodos mixtos, una falta de vocabulario común y pocos marcos de trabajo metodológicos. Revisamos los artículos publicados en dos campos relacionados con la conservación, los cuales con frecuencia incorporan métodos cualitativos y cuantitativos: las ciencias del cambio de suelo (n = 16) y el manejo ambiental (n = 16). Examinamos cómo los autores de estos estudios abordaron la investigación de métodos mixtos al codificar las características metodológicas importantes, incluyendo las relaciones entre los objetivos de los métodos, la extensión de la integración, las interacciones iterativas entre los métodos y la justificación para el uso de los métodos mixtos. Con estas características creamos una tipología con el objetivo de mejorar el entendimiento de cómo los investigadores que estudian las ciencias del cambio de suelo y el manejo ambiental abordan la investigación interdisciplinaria de métodos mixtos. Identificamos cinco tipos de estrategias de métodos mixtos, que denominamos anidadas, anidadas informadas, paralelas simples, de síntesis unidireccional y de síntesis bidireccional. Con frecuencia se utilizaron métodos y fuentes de datos para responder a diferentes preguntas de investigación dentro de un proyecto y sólo alrededor de la mitad de los artículos revisados integraron de manera metodológica diferentes presentaciones de los datos. La mayoría de los autores usaron un método para orientar al otro método, en lugar de que ambos métodos se orientaran mutuamente. Fueron muy pocos los artículos que usaron la iteración metodológica. Cada estilo metodológico tiene ciertas implicaciones epistemológicas, como el alcance disciplinario de la investigación y la capacidad de creación de conocimiento por medio del intercambio de información entre las distintas metodologías. Proporcionamos un marco de trabajo metodológico que integre de manera bidireccional y reitere los métodos cualitativos y cuantitativos para ejemplificar un diseño de investigación que pueda derivar en la producción multidimensional del conocimiento.