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Conservation Challenges

Conservation Challenges maps are accessible on desktop and tablet.

Conservation challenges are human activities or environmental changes that can have positive or negative impacts on wildlife and people. As birds migrate across the hemisphere they encounter myriad challenges.These maps are presented to bring awareness to the extent of human activities and environmental changes across the hemisphere, through the lens of migratory birds. The Conservation Challenge Maps show the footprint of human activities and environmental changes across the hemisphere. The Species Conservation Challenge Maps show where birds are exposed to the footprint of human activities and environmental changes throughout their annual migratory journey. By visualizing where, when, and how extensively human activities co-occur with migratory birds, we can better understand the challenges birds face and explore creative solutions that will maximize benefits for birds and people.

Interpreting the Conservation Challenge Maps

Visualizing the extent of overlap between migratory birds and conservation challenges illustrates how critical it is that we consider birds in management activities across the hemisphere. The Conservation Challenge Maps do not distinguish between areas that are positive or negative for birds, and in some areas where birds are exposed to challenges, those challenges are already being addressed. Poorly sited wind turbines may cause mortality through bird collisions, yet properly sited turbines offset the use of oil and gas, which mitigates one of the greatest challenges of all for birds and people—climate change. Similarly, in many places where birds co-occur with forest management, foresters are already incorporating the needs of birds into how they manage the forest. Conservation actions must be designed in the context of local conditions, and the solutions to these challenges will vary from one place to another.

The Bird Migration Explorer does not quantify the severity of challenges or the associated impacts on bird populations. The maps show the proportion of birds that may encounter a human activity or environmental change, based on the co-occurrence of the challenge and the species at a 3-km resolution, summarized in 50-km and 150-km hexagons. While 3-km cells are fine-scale at a hemispheric extent, they are coarse at a local extent. These maps are most appropriately interpreted as an index of exposure. Because of these limitations, understanding the severity and impact of a conservation challenge at a site requires additional local knowledge about the area and particular species.

Data in these maps are a combination of eBird Status abundance models and a variety of conservation challenge layers. The eBird Status models occasionally have spatial and temporal gaps in areas or weeks when observation data are too scarce to generate accurate predictions. The extent of the prediction area varies by week, and data gaps tend to affect areas that are most sparsely populated (e.g., the Canadian far north, the upper Amazon basin). See the eBird Status maps and methods for more details.

Mapping Methods

Identifying and Mapping the Footprint of Conservation Challenges

We began by using a standard framework of threats (also used by the International Union for the Conservation of Nature (IUCN), BirdLife International, and the Conservation Measures Partnership) to generate a list of 85 threats to migratory birds and score the relevance of each threat to each species of migratory bird. In cases where a threat was scored as relevant for one species, but there was no information for a similar species, we extrapolated relevance to the similar species that lacked information. We then lumped these 85 threats into a smaller number of categories that represented larger groups of human activities (e.g., forest management or surface water management). Because many of the human activities that present threats to birds also present a component of the solution, we adopted the term “conservation challenge” to convey both the risk and opportunity associated with each of these activities. We then searched for hemispheric spatial layers that could be used to represent a threat or groups of threats.

The Bird Migration Explorer does not include all the major issues birds face. We identified hemispheric spatial layers for 19 conservation challenges.

Urban Areas
Surburban Areas
Coastal Modification
Agriculture
Livestock Management
Oil and Gas Production
Wind Turbines
Roads
Power Lines
Communication Towers
Forest Management
Coastal Disturbance
Groundwater Depletion
Surface Water Management
Light Pollution
Water Quality
Sea Level Rise
Increasingly Severe Flooding
Drought

For each of these conservation challenges, we identified spatial layers that met the following criteria: hemispheric coverage, recent source data (preferably within the last 10 years), suitable spatial resolution (preferably 1-km cells or finer), and accuracy. We aggregated up to 3-km cells and then thresholded each layer into a binary presence/absence surface to represent the footprint of the conservation challenge (Table 1). The conservation challenge layers were gathered from various sources and, accordingly, were developed by various methods (Table 1). The datasets may be subject to gaps or inaccuracies, and thus should be used to examine broad spatial patterns, but should not be over-interpreted or used as a stand-alone decision-support tool.

Table 1. Map layer processing steps to delineate the footprint for each conservation challenge.

Map Layer	Thresholding Criteria
Urban Areas	We mapped urban areas as a binary surface by identifying all 3-km cells where the human population density exceeded 1,000 people per square mile (386 people per square kilometer) in 2010 (Gao 2017, Gao 2020).
Suburban Areas	We mapped suburban areas as a binary surface by identifying all 3-km cells where the human population density was between 100 and 1,000 people per square mile (38 to 386 per square kilometer) in 2010 (Gao 2017, Gao 2020).
Coastal Modification	We mapped the current footprint of coastal modification as a binary surface by identifying 3-km cells where there were ports (Maritime Safety Office 2019) or a high human footprint (values 25–50 on a scale from 0–50; Venter et al. 2016, Venter et al. 2018) within 6-km of the coast, including the Great Lakes (Wessel and Smith 2017).
Agriculture	We mapped the current extent of agriculture by identifying all 3-km cells containing cropland in 2022 (Karra et al. 2021), including both irrigated and rainfed fields (but excluding flooded crops and minor fragments). Urban areas and areas north of the Arctic Circle (66.6 N) were removed.
Livestock Management	We mapped the current extent of livestock management by identifying all 3-km cells containing rangeland or cropland in 2022 (Karra et al. 2021) where at least 10% of the land area was used as pasture in the year 2000. Pasture was identified based on satellite data combined with agricultural inventory data (see Ramankutty et al. 2008, Ramankutty et al. 2010 for details). Urban areas were removed.
Oil and Gas Production	We mapped existing oil and gas infrastructure as a binary surface by identifying all 3-km cells that contained oil wells, pipelines, production stations, refineries, processing plants, or liquefied natural gas locations (Homeland Infrastructure Foundation-Level Database 2019, Sabbatino et al. 2017).
Wind Turbines	We mapped the current onshore wind energy footprint as a binary surface by identifying all 3-km cells where wind turbine installations are located based on both global (Dunnet et al. 2020) and U.S. (Hoen et al. 2018) datasets.
Roads	We mapped the current footprint of roads as a binary surface by identifying all 3-km cells that included roads as mapped in the 2018 Global Roadways Inventory Project (Meijer et al. 2018).
Power Lines	We mapped the current footprint of power lines as a binary surface by identifying all 3-km cells where high voltage (>70 kV) and medium voltage (10–70 kV) power lines were predicted to occur in 2020 (Arderne et al. 2020).
Communication Towers	We mapped the current footprint of communication towers as a binary surface by identifying all 3-km cells where cell towers were present in 2023 (Unwired Labs 2023).
Forest Management	We mapped the current footprint of forest management as a binary surface by identifying 3-km cells where forestry and logging activities occur based on a dataset that classified drivers of global forest loss and regrowth (Curtis et al. 2018). This analysis defined forestry as “large-scale forestry operations occurring within managed forests and tree plantations with evidence of forest regrowth in subsequent years.” Urban and suburban areas were removed.
Coastal Disturbance	We mapped the current footprint of coastal disturbance as a binary surface by identifying 3-km cells that were within half an hour of towns of 5,000 people or more or ports of any size (Nelson et al. 2019), and within 6-km of the coast, including the Great Lakes (Wessel and Smith 2017).
Groundwater Depletion	We mapped the current footprint of groundwater depletion as a binary surface by identifying 3-km cells where the maximum anthropogenic groundwater pumping between 2000 and 2010 exceeded 0.25 millimeters per year (Herbert 2019).
Surface Water Management	We mapped the current footprint of surface water management as a binary surface by identifying 3-km cells with high levels of river fragmentation, flow disruption, and/or dam density (combined average of 0.65 or greater on a scale of 0-1; Vorosmarty et al. 2010, Conservation Biology Institute 2010), or where highly regulated rivers are located. Highly regulated rivers are defined here as those which have a degree of water flow regulation >10 on a scale from 0 to 100 (Grill et al. 2019).
Light Pollution	We mapped the current footprint of light pollution as a binary surface by identifying 3-km cells with any nighttime lights (i.e., values >0) per the 2021 annual VIIRS nighttime lights dataset produced by the Earth Observation Group at Colorado School of Mines. (Earth Observation Group, Payne Institute for Public Policy 2023, Elvidge et al. 2013, Elvidge et al. 2021).
Water Quality	We mapped the current footprint of nitrogen and phosphorous loading by identifying 3-km cells with high levels of these nutrients (0.8 or greater on a scale of 0–1; Vorosmarty et al. 2010, Conservation Biology Institute 2010).
Sea Level Rise	We mapped the future footprint of sea level rise by identifying 3-km cells projected to experience inundation under a 1-meter sea level rise scenario based on both global (Braaten et al.) and U.S. (NOAA Office for Coastal Management 2019) datasets. Global projections were developed based on elevation and proximity to the coastline. Sea level rise in the contiguous U.S. was modeled under a bathtub approach that incorporated local elevation, tides, and topography. Global scenarios were matched to local sea level rise in each state through downscaled estimates (Sweet et al. 2017).
Increasingly Severe Flooding	We mapped future flood exposure as a binary surface by identifying all 3-km cells where the level of flooding expected from a 100-year flood is expected to happen as often as every 25 years (i.e., 4x as frequent; Hirabayashi 2021).
Drought	We mapped the current footprint of drought as a binary surface by identifying 3-km cells that had a drought hazard score of 0.55 or greater on a scale of 0–1 (Carrão 2016).

These 19 conservation challenges do not represent all the major issues birds face. Partners in Flight, BirdLife International, the US Fish and Wildlife Service, the Committee on the Status of Endangered Wildlife in Canada, and the IUCN are sources of additional information on threats, impacts, and conservation status for migratory birds.

Quantifying and Mapping the Co-occurrence of Conservation Challenges and Migratory Birds

To map exposure, we combined the conservation challenge data with weekly distribution data from [eBird](https://science.ebird.org/en/status-and-trends) Status abundance models developed by the Cornell Lab of Ornithology. We aligned the conservation challenges to match the [eBird](https://science.ebird.org/en/status-and-trends) models (3-km cells in a sinusoidal projection) and then overlaid each challenge with each species’ weekly distribution to quantify co-occurrence, or exposure over the course of the year.

For the Conservation Challenge maps, we summarized the proportion of each hexagon overlapped by the conservation challenge footprint. We used the percent of area to classify results into five categories (Table 2).

Table 2. Categories of occurrence of conservation challenges (categories based on information from the Conservation Coaches Network for quantifying spatial exposure to threats).

Level	Occurence
Very High	Pervasive: 71–100% of area
High	Widespread: 31–70% of area
Medium	Restricted: 11–30% of area
Low	Very narrow: 1–10% of area

For the Species Conservation Challenge maps, we first summarized total abundance of each species within each hexagon, for each week of the year. For each species/week, we grouped hexagons into five ranked distribution classes where hexagons were sorted from highest to lowest abundance, then split into five classes that each sum to 20% of the total abundance. The resulting classes (very high [top 20%], high, moderate, low, very low [bottom 20%]) visualize the contribution of each hexagon to the total population of the species. Next, we calculated the proportion of the population in each hexagon overlapping the conservation challenge footprint in each week, and classified results into one of five potential co-occurrence categories (Table 3).

Table 3. Levels of co-occurrence with conservation challenges for migratory birds (categories based on information from the Conservation Coaches Network for quantifying spatial exposure to threats).

Level	Co-occurence
Very High	Pervasive: 71–100% of population overlaps with conservation challenge footprint
High	Widespread: 31–70% of population overlaps with conservation challenge footprint
Medium	Restricted: 11–30% of population overlaps with conservation challenge footprint
Low	Very narrow: 1–10% of population overlaps with conservation challenge footprint
None	Not present or unknown occurrence: 0% of population overlaps with conservation challenge footprint

Using these two measures, we created a bivariate visualization:

Species abundance (represented by symbol size): this indicates the relative contribution of an area to the total population of a species.
Potential exposure (represented by color): this indicates the proportion of the bird population in an area that overlaps with the conservation challenge.

Because not all species are impacted by all conservation challenges, we filtered Species Conservation Challenge maps to render only relevant combinations. To identify the relevant conservation challenges, we used our initial list of 85 threats. If a threat was scored as having a negative impact on a species, then the associated conservation challenge was flagged for inclusion for the species. Many threats remain poorly documented for some species and will change over time as new information becomes available. Thus, the list of conservation challenges for each species represents our current understanding of the conservation of these migratory birds.

Species Conservation Statistics

Climate Vulnerability

Climate Vulnerability is derived from a published analysis by the National Audubon Society. This analysis compiled more than 140 million observations to develop species distribution models and assess climate change vulnerability for 604 North American bird species at a continental scale in both breeding and non-breeding seasons and under a climate scenario of 3°C warming. Based on projected range loss and potential range gain for each species, climate vulnerability was categorized as neutral, low, moderate, or high. Learn more about climate vulnerability here.

Global Population Estimate

The global population estimate is derived from the Partners in Flight Avian Conservation Assessment Database, managed by Bird Conservancy of the Rockies. This database contains the most current and complete information on the biological vulnerability of North American bird species at various scales, and identifies important species and regions for conservation action. This database was developed with data from dozens of large-scale, long-term bird population surveys as well as input and review from dozens of ornithological experts from ten countries.

The global population size is an estimate of the number of breeding age individuals that occur across the entire range of a species. Learn more about the Avian Conservation Assessment Database here.

Continental Conservation Status

Continental Conservation Status is derived from the Partners in Flight Avian Conservation Assessment Database, managed by Bird Conservancy of the Rockies. This database contains the most current and complete information on the biological vulnerability of North American bird species at various scales, and identifies important species and regions for conservation action. This database was developed with data from dozens of large-scale, long-term bird population surveys as well as input from dozens of ornithological experts from ten countries.

Based on quantitative criteria, the continental (US/Canada) conservation status is assigned to species that are designated as: Highly Vulnerable and in Urgent Need of Special Attention (Red List), Range Restricted and Small Populations in Need of Constant Care (Yellow Watch List R), Steep Declines and Major Threats (Yellow Watch List D), or Common Birds in Steep Decline. Learn more about the Avian Conservation Assessment Database here.

Global IUCN Red List Category

Global IUCN Red List Category is derived from BirdLife International's assessments of extinction risk for the International Union for Conservation of Nature (IUCN) Red List of Threatened Species, which is the world's most comprehensive inventory of the extinction risk of species.

Based on quantitative criteria, the global extinction risk of each species has been assigned to one of the following levels: Critically Endangered, Endangered, Vulnerable, Near Threatened, or Least Concern. Learn more about the IUCN Red List here.

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