Ecoregion Map Research Articles

Pushing the Frontiers of Biodiversity Research: Unveiling the Global Diversity, Distribution, and Conservation of Fungi

Fungi comprise approximately 20% of all eukaryotic species and are connected to virtually all life forms on Earth. Yet, their diversity remains contentious, their distribution elusive, and their conservation neglected. We aim to flip this situation by synthesizing current knowledge. We present a revised estimate of 2–3 million fungal species with a “best estimate” at 2.5 million. To name the unknown >90% of these by the end of this century, we propose recognition of species known only from DNA data and call for large-scale sampling campaigns. We present an updated global map of fungal richness, highlighting tropical and temperate ecoregions of high diversity. We call for further Red List assessments and enhanced management guidelines to aid fungal conservation. Given that fungi play an inseparable role in our lives and in all ecosystems, and considering the fascinating questions remaining to be answered, we argue that fungi constitute the next frontier of biodiversity research.

Early Crop Mapping Using Dynamic Ecoregion Clustering: A USA-Wide Study

Mapping target crops earlier than the harvest period is an essential task for improving agricultural productivity and decision-making. This paper presents a new method for early crop mapping for the entire conterminous USA (CONUS) land area using the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) data with a dynamic ecoregion clustering approach. Ecoregions, geographically distinct areas with unique ecological patterns and processes, provide a valuable framework for large-scale crop mapping. We conducted our dynamic ecoregion clustering by analyzing soil, climate, elevation, and slope data. This analysis facilitated the division of the cropland area within the CONUS into distinct ecoregions. Unlike static ecoregion clustering, which generates a single ecoregion map that remains unchanged over time, our dynamic ecoregion approach produces a unique ecoregion map for each year. This dynamic approach enables us to consider the year-to-year climate variations that significantly impact crop growth, enhancing the accuracy of our crop mapping process. Subsequently, a Random Forest classifier was employed to train individual models for each ecoregion. These models were trained using the time-series MODIS (Moderate Resolution Imaging Spectroradiometer) 250-m NDVI and EVI data retrieved from Google Earth Engine, covering the crop growth periods spanning from 2013 to 2017, and evaluated from 2018 to 2022. Ground truth data were sourced from the US Department of Agriculture’s (USDA) Cropland Data Layer (CDL) products. The evaluation results showed that the dynamic clustering method achieved higher accuracy than the static clustering method in early crop mapping in the entire CONUS. This study’s findings can be helpful for improving crop management and decision-making for agricultural activities by providing early and accurate crop mapping.

Forest Landscape Model Initialization with Remotely Sensed-Based Open-Source Databases in the Absence of Inventory Data

Forecasts of the forest ecosystem dynamics are important for environmental protection and forest resource management. Such forecasts can support decisions about where and how to restore damaged forests and plan felling, and in forest conservation. Forest landscape models (FLM) are used to predict changes in forests at the landscape level. FLM initialization usually requires detailed tree species and age data; so, in the absence of forest inventory data, it is extremely difficult to collect initial data for FLM. In our study, we propose a method for combining data from open sources, including remote sensing data, to solve the problem of the lack of initial data and describe initializing the LANDIS-II model. We collected land cover classification and above-ground biomass products, climate, soil, and elevation data to create initial vegetation and ecoregion maps. Our method is based on some simplifications of the study object—some tree species are replaced by groups of species; the forest stand is considered homogeneous. After initialization, the natural dynamics without harvesting and disturbances were simulated by the Biomass Succession extension for 200 years. The study presents a detailed methodology that can be used to initialize other study areas and other FLMs with a lack of field data.

Omernik's Ecoregion Framework: a Legacy for Understanding Regional Patterns in Attainable Resource Quality.

An initial and comprehensive map of ecological regions across the conterminous United States was provided by Omernik in 1987. Because that paper was the most-cited published by the Annals of the American Association of Geographers, we sought to assess and quantify its contribution to science. To do so, we conducted a scientometric analysis to address the following main questions: 1) What are the temporal and spatial citation trends? We expected that Omernik's paper would still be employed 36 years after its publication, and mostly in the United States of America. 2) For what types of environments and organisms has it been applied? Based on its generality, we expected that it had been applied to both terrestrial and aquatic ecosystems. 3) What are the main applications of Omernik's article? We predicted that it would mostly be used for describing and delineating study sites and management areas, as well as for selecting regional reference sites. The number of citations presented a positive temporal increase, indicating its continued applicability. Most papers dealt with aquatic environments, mainly in streams carried out predominantly in the United States of America, as was one of its earliest applications. The usefulness of ecoregions for assessing and managing biotic and abiotic patterns and distributions were the main topics addressed by scientists. Ecoregions have offered a general framework for developing regional expectations and rational regional management policies across large areas, as was their original intent. In addition, ecoregion maps were used for communicating patterns-or the lack of them-to interested scientists, citizens, and decision-makers. That comprehensiveness of Omernik's ecoregion approach has led to its widespread applicability and continued usefulness to a diverse set of scientific and management disciplines.

Putting fire on the map of Brazilian savanna ecoregions

The Brazilian savanna (Cerrado) is considered the most floristically diverse savanna in the world, home to more than seven thousand species. The region is a mosaic of savannas, grasslands and forests whose unique biophysical and landscape attributes are on the basis of a recent ecoregional map, paving the way to improved region-based strategies for land management actions. However, as a fire-prone ecosystem, Cerrado owes much of its distribution and ecological properties to the fire regime and contributes to an important parcel of South America burned area. Accordingly, any attempt to use ecoregion geography as a guide for management strategies should take fire into account, as an essential variable. The main aim of this study is to complement the ecoregional map of the Cerrado with information related to the fire component. Using remotely sensed information, we identify patterns and trends of fire frequency, intensity, seasonality, extent and scar size, and combine this information for each ecoregion, relying on a simple classification that summarizes the main fire characteristics over the last two decades. Results show a marked north-south fire activity gradient, with increased contributions from MATOPIBA, the latest agricultural frontier. Five ecoregions alone account for two thirds of yearly burned area. More intense fires are found in the Arc of Deforestation and eastern ecoregions, while ecoregions in MATOPIBA display decreasing fire intensity. An innovative analysis of fire scars stratified by size class shows that infrequent large fires are responsible for the majority of burned area. These large fires display positive trends over many ecoregions, whereas smaller fires, albeit more frequent, have been decreasing in number. The final fire classification scheme shows well defined spatially-aggregated groups, where trends are found to be the key factor to evaluate fire within their regional contexts. Results presented here provide new insights to improve fire management strategies under a changing climate.

Mapping the terrestrial ecoregions of the Purus-Madeira interfluve in the Amazon Forest using machine learning techniques

An ecoregion is a region with similar environmental conditions. However, many ecoregions represent regional habitat heterogeneity, and areas with little fieldwork information can benefit from ecoregion mapping by providing information about their biodiversity distribution. This work presents the procedure adopted to map the terrestrial ecoregions of the Purus-Madeira interfluve, in the Brazilian Amazon using Machine Learning techniques. A methodological approach with Self-Organizing Map and K-means algorithms is proposed for the ecoregion mapping and the resulting model is discussed. The final ecoregion map was built up from a set of variables including altitude, slope, drainage density, percentage of tree cover and a vegetation map. Discriminant analysis identified the extent to which the variables are similar or different between the ecoregions, with a Kappa index of 0.86. This indicates that the methodological approach is reliable and thus can reproduce valid results over different areas. We produced a map with 14 ecoregions to account for the environmental diversity in the Purus-Madeira interfluve. This map can be used for the planning of biodiversity conservation.

To Achieve Big Wins for Terrestrial Conservation, Prioritize Protection of Ecoregions Closest to Meeting Targets

Most of the terrestrial world is experiencing high rates of land conversion despite growth of the global protected area (PA) network. There is a need to assess whether the current global protection targets are achievable across all major ecosystem types and to identify those that need urgent protection. Using recent rates of habitat conversion and protection and the latest terrestrial ecoregion map, we show that if the same approach to PA establishment that has been undertaken over the past three decades continues, 558 of 748 ecoregions (ca. 75%) will not meet an aspirational 30% area protection target by 2030. A simple yet strategic acquisition plan that considers realistic futures around habitat loss and PA expansion could more than double the number of ecoregions adequately protected by 2030 given current funding constraints. These results highlight the importance of including explicit ecoregional representation targets within any new post-2020 global PA target.

Spatial heterogeneity of climate variation and vegetation response for Arctic and high-elevation regions from 2001–2018

In recent decades, an amplification of warming in Arctic and high-elevation regions has been widely observed, along with a general enhancement of vegetation growth. However, driven by variability in controlling factors and complex mechanisms, climate and vegetation changes can be highly heterogeneous in space and time. In this study, an analysis is performed separating Arctic and Tibetan Plateau (TP) vegetated areas into various units according to a map of terrestrial ecoregions. The most recent variations of heat, moisture, and vegetation growth (MODIS Normalized Difference Vegetation Index) are evaluated over 2001–2018. Relationships among the climate and vegetation variables are assessed. Six distinct change patterns are identified: (1) synchronized increase of day and night temperature and precipitation during April to October coinciding with strong vegetation greening, (2) profound warming with no change in precipitation and vegetation, (3) an increase of summer temperature and vegetation with a negative latitudinal gradient, (4) greening under increased precipitation without warming, (5) browning not likely being driven by climate, (6) warming only during the nighttime and moderately enhanced vegetation growth. It is demonstrated that vegetation growth in the Arctic and TP is largely controlled by nighttime temperature and precipitation, as opposed to daytime temperature. The exception is the Canadian Arctic, where greening is directly related to summer daytime warming, and a contrasting relationship is observed on the TP. The underlying causes of these patterns are discussed, relating them to multiple mechanisms reported in the literature. These findings may help to further understand the changing Arctic and high-elevation climate and its effects on vegetation growth.

Mapping fire regime ecoregions in California

The fire regime is a central framing concept in wildfire science and ecology and describes how a range of wildfire characteristics vary geographically over time. Understanding and mapping fire regimes is important for guiding appropriate management and risk reduction strategies and for informing research on drivers of global change and altered fire patterns. Most efforts to spatially delineate fire regimes have been conducted by identifying natural groupings of fire parameters based on available historical fire data. This can result in classes with similar fire characteristics but wide differences in ecosystem types. We took a different approach and defined fire regime ecoregions for California to better align with ecosystem types, without using fire as part of the definition. We used an unsupervised classification algorithm to segregate the state into spatial clusters based on distinctive biophysical and anthropogenic attributes that drive fire regimes – and then used historical fire data to evaluate the ecoregions. The fire regime ecoregion map corresponded well with the major land cover types of the state and provided clear separation of historical patterns in fire frequency and size, with lower variability in fire severity. This methodology could be used for mapping fire regimes in other regions with limited historical fire data or forecasting future fire regimes based on expected changes in biophysical characteristics.

Religion and Child Health in West and Central Africa

Table A1. Surveys, response rates, populations and samples Table A2. Sample deduction Table A3. Testing data quality by religion and household wealth Table A4. Number of observations for each country by community level religious composition Table A5. Full regression outputs for Figures 2 and 3 and Table 2 Figure A1. Predicted outcomes by community level religious composition for Protestants, Catholics, and Muslims Figure A2. Differences in under-five mortality by religion and community level religious composition. Hazard ratios from Cox proportional-hazard models Figure A3. Differences in height-for-age z-score by religion and community level religious composition. Missing outcome and covariates imputed Figure A4. Differences in under-five mortality by religion and community level religious composition. Missing covariates imputed Figure A5. Map of study area, communities, and ecoregions Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Cerrado ecoregions: A spatial framework to assess and prioritize Brazilian savanna environmental diversity for conservation

The Brazilian Cerrado is the second largest biome in Latin America, extending over more than 200 million ha and hosts some of the most intensive agricultural activities for grain and beef production in the world. Because of the biodiversity richness and high levels of endemism, Cerrado is considered one of world's hotspot for biodiversity conservation. The objectives of this study are three-fold: to present a comprehensive division of Cerrado into different ecoregions that reflect the environmental heterogeneity within the biome; to analyze the ecoregions in terms of biophysical characteristics, protected areas, environmental liability in riparian permanent protection areas along watercourses, and priorities for biodiversity conservation; and to rank the ecoregions in terms of endangerment for biodiversity conservation and restoration. A previous study that delineated 22 ecoregions using geomorphology, vegetation, soil, geology, and plant diversity maps was revised using topography, vegetation, precipitation, and soil maps. Our new ecoregion map consists of 19 units that are unique in terms of landscape characteristics and has been adjusted to the current official boundary map of Cerrado. Some of the ecoregions consist of only one geomorphological compartment, whereas others are heterogeneous, consisting of up to eight compartments. Ferralsols comprise the dominant soil type in 14 of the ecoregions. The percentage of protected areas within ecoregions ranges from 1.7% to 51.5%. The most endangered ecoregion, where land use change critically threatens habitat integrity, is the Depressão Cárstica do São Francisco (states of Bahia, Minas Gerais, and Piauí), where environmental liability along riparian permanent protection areas amounts to 85.6% of the total area. Our proposed ecoregion map provides a spatial framework for regional and local assessments to improve decision-making processes to reconcile conservation and restoration planning, sustainable agriculture, and provision of ecosystem services. Besides de adjustment of the previous Cerrado's ecoregion map to the official biome boundary (relevant for the implementation of public policies of conservation as those regulated by the Brazilian Forest Code), the new analyses of the ecoregion map represent a substantial improvement in comparison to the ones conducted by the previous study in 2003. In addition, current web resources allow us to make all the information used or derived from this study available to other users. This opens the possibility of additional improvements of our findings by the scientific community or to be used effectively by decision makers.

A first revision of the Italian Ecoregion map

According to advances in phytogeographic knowledge, a revision of boundaries for the Italian Ecoregions have been made. Main changes relate to the southern and eastern limits between Temperate and Mediterranean Divisions. The revision triggered a comprehensive update of Ecoregions for an improved support to biodiversity and sustainable management initiatives.

Bioclimatic classification of US vegetation along a coast-to-coast macrotransect crossing central United States. I: Mediterranean vegetation

This report presents the first of two parts of a bioclimatic classification of the vegetation of the United States. Using a geographical information system, 987 weather stations were located along a longitudinal macrotransect from the shores of the Atlantic to Pacific on four maps: Map of the Physiographic Divisions of the Conterminous US, US Potential Natural Vegetation Map, US Ecoregion Map, and Terrestrial Ecosystems-Isobioclimates Map of the Conterminous United States. Based on these maps, bibliographic resources and field data, we deduced the potential natural vegetation (PNV) of each weather station; then, we assigned the different PNV types to alliance or association levels using the US National Vegetation Classification (USNVC). In a next step, USNVC groups were related with similar level phytosociological syntaxa described in the study area. The bioclimatic distribution of the USNVC units defined was then interpreted using the bioclimatic classification proposed in successive approximations by S. Rivas-Martínez. The distribution of USNVC alliances was mainly linked to the macrobioclimates (Mediterranean, Temperate, and Tropical) of the longitudinal gradient examined, though some edaphic factors induced the appearance of specialized plant groups. Herein, we present our data for the Mediterranean macrobioclimate, in which 53 alliances and 28 isobioclimates were identified.

Detecting spatial regimes in ecosystems.

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory-based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change.

A stratified random sampling design in space and time for regional to global scale burned area product validation.

The potential research, policy and management applications of global burned area products place a high priority on rigorous, quantitative assessment of their accuracy. Such an assessment can be achieved by implementing validation methods employing design-based inference in which the independent reference data are selected via a probability sampling design. The majority of global burned area validation exercises use Landsat data to derive the independent reference data. This paper presents a three-dimensional sampling grid that allows for probability sampling of Landsat data in both space and time. To sample the globe in the spatial domain with non-overlapping sampling units, the Thiessen Scene Area (TSA) tessellation of the Landsat path/row geometry is used. The TSA grid is combined in time with the 16-day Landsat acquisition calendar to provide three-dimensional elements (voxels).This allows for implementation of stratified random sampling designs, where not only the location but also the time interval of the independent reference data is explicitly drawn by probability sampling. To illustrate this, we use a stratification methodology based on the Olson global ecoregion map and on the MODIS global active fire product. Using the global MODIS burned area product to establish a hypothetical population of reference data, we show that a sampling scheme based on the proposed stratification with equal sample allocation among strata is effective in reducing the standard errors of accuracy and area estimators compared to simple random sampling. Globally, the standard errors were reduced by 63%, 54%, 22% and 53% for overall accuracy, omission error, commission error and total burned area estimates respectively. By incorporating probability sampling in both the spatial and temporal domains, the present study establishes the foundation for rigorous design-based validation of global burned area products and, more generally, of terrestrial thematic products that have high temporal variability.

A GIS-based multivariate clustering for characterization and ecoregion mapping from a viticultural perspective

In wine-growing regions, zoning studies define areas according to their potential to produce specific wines and also identify the key drivers behind their variability and optimize vineyard management for sustainable viticulture. However, delineation of homogeneous zones is difficult because of the complex combination of factors which could affect zone classifications. One possibility to capture potential variability is the use of natural environmental properties as they are related to success in grape growing. With the aim of characterizing the spatial variability of the main vine-related environmental variables and determining different zones, climate and topographical data were obtained for Extremadura (southwestern Spain), an important wine region. Firstly, accurate maps of all climate indices were generated by using regression-kriging as the most suitable algorithm in which exhaustive secondary information on elevation was incorporated, and maps of topography-derived variables were obtained using GIS (Geographical Information System) tools. Secondly, principal component analysis and multivariate geographic classification were used to define homogeneous classes, resulting in three zones. Each zone was further characterized by overlaying the zonation map with a geology map and all enviromental layers. It was obtained that although a wide part of the Extremaduran territory has warm climate characteristics, the zones have different viticultural potential and a high proportion of the region lays on suitable substrate. This zonation in Extremadura is the basis for further zoning studies at more detailed field scale and the modeling of vineyard response to climate change.

북한 산림경관복원 적용을 위한 한반도 생태지역 특성

The objectives of this study are to construct an ecoregion map and to extract ecological factors from each ecoregion to adapt FLR (Forest Landscape Restoration) of North Korea. An ecological map was constructed by PCA(Principal Component Analysis) and MGC(Multivatiate Geographical Clustering). An ANOVA test verified the differences among ecoregions, and post-hoc pair wise comparisons were performed to determine similarities between them. Factor analysis was conducted to extract ecoregional characteristics. Ecoregions were distributed into clusters reflecting differences of south and north and of east and west of their ecological factors. About 12% of land area in North Korea shared similar ecological factors with South Korea, but the remaining 88% was found to be ecologically different. The ANOVA test showed a p-value of 0.000, indicating significant differences between the regions. Post-hoc pair wise comparisons indicated statistically significant similarities in annual mean temperature between ecoregion D and G, precipitation seasonality between ecoregion H and O, and precipitation of the warmest quarter between ecoregion K and O. Because ecoregion A and N showed same in their soil water contents, they were assumed that the dense of forest cover in the Southern ecoregion A is similar to that in the Northern ecoregion N of Korean peninsular. Based on the results of this study, it is necessary to accommodate quantitative and spatial based planning, when South Korea aids forest restoration projects in North Korea. In addition, it is recommended for both South and North Korea to share on Forest Landscape Restoration methodologies with each other.

Assessing Potential Seed Transfer Zones for Five Forb Species from the Great Basin Floristic Region, USA

ABSTRACT: For plant species important in ecological restoration, seed transfer zones have been developed to maximize the probability that sown seed will germinate, establish, persist, and reproduce without negatively impacting the genetic composition of remnant plant populations. However, empirically based seed transfer zones have not been developed for most species. In their absence, maps based on ecological or climatic variables have been suggested as proxies. In the United States, these maps typically include the Environmental Protection Agency's Levels III and IV Ecoregion maps and the US Forest Service's Provisional Seed Zones. Maps of different spatial scales represent a compromise between economic and ecological considerations; those that delineate larger seed transfer zones are less costly to implement but impose more risk of poor adaptation to local conditions. To test the relative suitability of each map in delineating seed transfer zones, we conducted common garden experiments using five forb s...

Representativeness-based sampling network design for the State of Alaska

Resource and logistical constraints limit the frequency and extent of environmental observations, particularly in the Arctic, necessitating the development of a systematic sampling strategy to maximize coverage and objectively represent environmental variability at desired scales. A quantitative methodology for stratifying sampling domains, informing site selection, and determining the representativeness of measurement sites and networks is described here. Multivariate spatiotemporal clustering was applied to down-scaled general circulation model results and data for the State of Alaska at 4 km2 resolution to define multiple sets of ecoregions across two decadal time periods. Maps of ecoregions for the present (2000–2009) and future (2090–2099) were produced, showing how combinations of 37 characteristics are distributed and how they may shift in the future. Representative sampling locations are identified on present and future ecoregion maps. A representativeness metric was developed, and representativeness maps for eight candidate sampling locations were produced. This metric was used to characterize the environmental similarity of each site. This analysis provides model-inspired insights into optimal sampling strategies, offers a framework for up-scaling measurements, and provides a down-scaling approach for integration of models and measurements. These techniques can be applied at different spatial and temporal scales to meet the needs of individual measurement campaigns.

Формулы ареалов лихенизированных грибов семейства Umbilicariaceae из Монголии на основе общемировой карты экорегионов суши

Detailed laconic description of lichens ranges is represented as a formula. The formula is based on the biogeographical subdivision of the world. The formula includes symbols of the biogeographical realms and biomes on the map of the terrestrial ecoregions of the world, where the presence of a species was recorded. The formulas of ranges are given for 34 Umbilicariaceae species recorded in Mongolia.