The 30,000 acres of wetlands within the Don Edwards San Francisco Bay National Wildlife Refuge (Refuge) provide critical habitat for over one million waterbirds annually (Page et al. 1999, Warnock et al. 2002). These wetlands consist largely of tidal marshes and open water ponds. Salt evaporator ponds have been in this landscape for over 150 years (Ver Planck 1958) and are heavily used by shorebirds, waterfowl and other wildlife species (Anderson 1970, Accurso 1992, Takekawa et al. 2001, Warnock et al. 2002). Salt ponds, and former salt ponds now managed as wildlife habitat, provide the majority of the roosting and (for some species) foraging habitat for waterbirds in the San Francisco Bay. The South Bay Salt Pond Restoration Project (Restoration Project), of which the Refuge and California Department of Fish and Wildlife's (CDFW, also CDFG) Eden Landing Ecological Reserve are a part, is implementing a large-scale plan to convert 15,100 acres of former salt ponds into tidal and managed wetland habitats (SBSPRP 2007).While the restoration of former salt ponds to tidal marsh will increase habitat for species that depend on tidal marshes, it also will reduce the overall pond habitats available for waterbirds. However, through adaptive management, the Restoration Project is committed to maintaining "baseline" levels of waterbirds in this site of international importance along the Pacific Flyway (Ramsar Convention on Wetlands, 2013). The Restoration Project has committed to retaining between 10-50% of the 15,100 total Project acres as ponds that are managed largely for waterbirds, but information is needed to ensure that the habitat requirements of large numbers of waterbirds can be met with reduced pond acreage. Monthly ground-based surveys, conducted in former and currently active salt ponds by the U.S. Geological Survey San Francisco Bay Estuary Field Station (USGS) and San Francisco Bay Bird Observatory (SFBBO) have been ongoing since 2002 and 2005, respectively, however, these surveys began after the Restoration Project started. Thus, baseline (i.e., historical) numbers remain largely unknown for many waterbird species prior to the initiation of the Restoration Project. However, in the 1980's, state and federal biologists conducted monthly aerial surveys of waterbirds on all of the salt ponds in the South Bay. These data were recently rediscovered and scanned through a cooperative effort with USGS. In 2009, the USGS scanned these datasheets, and a Refuge intern began the process of entering data into a modified version of SFBBO's current waterbird survey database. In 2010, SFBBO and the Refuge received support from the USFWS Inventory & Monitoring Program, with the goal of completing entry of historical data and analyzing these data to compare historical and current waterbird numbers in Eden Landing Ecological Reserve and the Newark, Alviso, Mowry and Ravenswood salt pond complexes. A metadata report describing the datasets, collection methods, and potential caveats, was submitted previously by SFBBO (Demers & Tokatlian 2012).In this report, we describe the methods we used to compare the current and baseline (historical) datasets and present our findings on the current and historical patterns of abundance and distribution for nine guilds and several individual species of interest to the Refuge, CDFW and Restoration Project. We also compare changes in community structure from the historical to the current data, focusing on changes in patterns of species richness and abundance. We also describe work conducted by researchers at the University of California, Davis, to develop a "conversion factor" that enabled current (ground-based) survey data to be compared with historical (aerial-based) survey data.

1. Hotspot analysis is a commonly used method in ecology and conservation to identify areas of high biodiversity or conservation concern. However, delineating and mapping hotspots is subjective and various approaches can lead to different conclusions with regard to the classification of particular areas as hotspots, complicating long-term conservation planning. 2. We present a comparative analysis of recent approaches for identifying waterbird hotspots, with the goal of developing insights about the appropriate use of these methods. We selected four commonly used measures to identify persistent areas of high use: kernel density estimation, Getis-Ord Gi*, hotspot persistence, and hotspots conditional on presence, which represent the range of quantitative hotspot estimation approaches used in waterbird analyses. We applied each of the methods to aerial survey waterbird count data collected in the Great Lakes from 2012-2014. For each approach, we identified areas of high use for seven species/species groups and then compared the results across all methods and with mean effort-corrected counts. 3. Our results indicate that formal hotspot analysis frameworks do not always lead to the same conclusions. The kernel density and Getis-Ord Gi* methods yielded the most similar results across all species analyzed and were generally correlated with mean effort-corrected count data. We found that these two models can differ substantially from the hotspot persistence and hotspots conditional on presence estimation approaches, which were not consistently similar to one another. The hotspot persistence approach differed most significantly from the other methods but is the only method to explicitly account for temporal variation. 4. We recommend considering the ecological question and scale of conservation or management activities prior to designing survey methodologies. Deciding the appropriate definition and scale for analysis is critical for interpretation of hotspot analysis results as is inclusion of important covariates. Combining hotspot analysis methods using an integrative approach, either within a single analysis or post-hoc, could lead to greater consistency in the identification of waterbird hotspots.

As part of the Tropical Rivers Inventory and Assessment Project (TRIAP), a database of 94,148 waterbird records was assembled, comprising 82,596 records from the TRIAP area and 11,552 records from a surrounding 10 km buffer. These records were sourced from databases for Atlas1 and Atlas2 provided by Birds Australia, 99.1% of which are from the Historical Atlas (pre-1977), the first Field Atlas (1977-1981) or the second Field Atlas (1997-2002). Waterbirds were defined to include species of …Show full description As part of the Tropical Rivers Inventory and Assessment Project (TRIAP), a database of 94,148 waterbird records was assembled, comprising 82,596 records from the TRIAP area and 11,552 records from a surrounding 10 km buffer. These records were sourced from databases for Atlas1 and Atlas2 provided by Birds Australia, 99.1% of which are from the Historical Atlas (pre-1977), the first Field Atlas (1977-1981) or the second Field Atlas (1997-2002). Waterbirds were defined to include species of freshwater and coastal wetlands including in-shore but not off-shore marine species. The TRIAP waterbird fauna comprises 145 species from twenty families, of which 112 species are represented in the database by more than ten records. One TRIAP waterbird species – the Australian Painted Snipe – is listed as threatened under the Environment Protection and Biodiversity Conservation Act 1999 (EPBCA). Eighty-seven species are listed as "migratory" under the EPBCA, 44 species are listed under the Japan-Australia Migratory Bird Agreement and 53 species under the China-Australia Migratory Bird Agreement. The geographical characteristics of all listed species are summarised for the TRIAP area. In the TRIAP area, the Australian Painted Snipe is an infrequent visitor or perhaps rare resident found more frequently in the more arid south. Its preferred habitat of ephemeral wetlands with a mix of mud-flats and dense low vegetation does not closely match habitats recorded for the species in the TRIAP area, which may reflect the marginal nature of its occurrence in this area. Breeding records in the TRIAP area have been in flooded grasslands. A foraging guild classification based on a classification of foraging substrate, foraging methods and food types is presented in this dataset. Twelve foraging guilds are recognised as occurring in the TRIAP area. No waterbirds are endemic to the TRIAP area. However, the TRIAP area represents a major proportion of the range of the Chestnut Rail, and a major proportion of the Australian range of the Great-billed Heron. A biogeographic classification of TRIAP waterbirds is developed based on breeding distributions. Four classes are recognised: a. species for whom TRIAP is a core breeding area; b. Australasian species for whom TRIAP is marginal to their main distribution; c. Palaearctic / Nearctic migrants – these do not breed in Australia; and d. Non-migratory species with a distribution centre in Asia, or Malaysia including New Guinea. Few species other than vagrants have restricted ranges within the TRIAP area, but there is a weak declining gradient in species richness from east to west. The distribution of waterbird families, foraging guilds and threatened species were compared qualitatively with a 1:250 000 classification of waterbodies into seven units. Although the results are "noisy", groups associated with deep water and saline habitats were clearly identifiable. A geomorphic classification of rivers provides only linear data and poor spatial correspondence with waterbird records. Neither classification provides a direct measure of the wetland features most relevant to most species, and whilst quantitative analysis could be pursued, it appears unlikely to identify many definitive habitat relationships. See Table 6, section 3.3 of (Franklin 2008) for an explanation of foraging guilds. Note that "herbivore" includes the possibility of also being extensively insectivorous, whereas "insectivore" implies that herbivory is not a major component of the diet. See lineage for more details or refer to: Franklin DC. 2008. Report 9: The waterbirds of Australian tropical rivers and wetlands. In A Compendium of Ecological Information on Australia’s Northern Tropical Rivers. Sub-project 1 of Australia’s Tropical Rivers – an integrated data assessment and analysis (DET18). A report to Land & Water Australia, ed. GP Lukacs, CM Finlayson. National Centre for Tropical Wetland Research: Townsville. Note: Metadata not published in Australian Spatial Data Directory (ASDD) as of October 2009- No ANZLIC Unique Identifier assigned.

Summary of published calibration equations and associated statistics relating δ2Hp to δ2Hf for waterfowl, waterbirds, and shorebirds.

Fecal pollution in coastal areas is of a high concern since it affects bathing and shellfish harvesting activities. Wild waterbirds are non-negligible in the overall signal of the detectable pollution. Yet, studies on wild waterbirds’ gut microbiota focus on migratory trajectories and feeding impact on their shape, rare studies address their comparison to other sources and develop quantitative PCR (qPCR)-based Microbial Source Tracking (MST) markers to detect such pollution. Thus, by using 16S rRNA amplicon high-throughput sequencing, the aims of this study were (i) to explore and compare fecal bacterial communities from wild waterbirds (i.e., six families and 15 species, n = 275 samples) to that of poultry, cattle, pigs, and influent/effluent of wastewater treatment plants (n = 150 samples) and (ii) to develop new MST markers for waterbirds. Significant differences were observed between wild waterbirds and the four other groups. We identified 7,349 Amplicon Sequence Variants (ASVs) from the hypervariable V3–V4 region. Firmicutes and Proteobacteria and, in a lesser extent, Actinobacteria and Bacteroidetes were ubiquitous while Fusobacteria and Epsilonbacteraeota were mainly present in wild waterbirds. The clustering of samples in non-metric multidimensional scaling (NMDS) ordination indicated a by-group clustering shape, with a high diversity within wild waterbirds. In addition, the structure of the bacterial communities was distinct according to bird and/or animal species and families (Adonis R2 = 0.13, p = 10–4, Adonis R2 = 0.11, p = 10–4, respectively). The Analysis of Composition of Microbiomes (ANCOM) showed that the wild waterbird group differed from the others by the significant presence of sequences from Fusobacteriaceae (W = 566) and Enterococcaceae (W = 565) families, corresponding to the Cetobacterium (W = 1427) and Catellicoccus (W = 1427) genera, respectively. Altogether, our results suggest that some waterbird members present distinct fecal microbiomes allowing the design of qPCR MST markers. For instance, a swan- and an oystercatcher-associated markers (named Swan_2 and Oyscab, respectively) have been developed. Moreover, bacterial genera harboring potential human pathogens associated to bird droppings were detected in our dataset, including enteric pathogens, i.e., Arcobacter, Clostridium, Helicobacter, and Campylobacter, and environmental pathogens, i.e., Burkholderia and Pseudomonas. Future studies involving other wildlife hosts may improve gut microbiome studies and MST marker development, helping mitigation of yet unknown fecal pollution sources.

Plant dispersal syndromes are allocated based on diaspore morphology and used to predict mechanisms of dispersal. Many authors assume that only angiosperms with endozoochory, epizoochory or anemochory syndromes have a long-distance dispersal (LDD) mechanism. Too much faith is often placed in classical syndromes to explain historical dispersal events and to predict future ones. The “endozoochory syndrome” is actually a “frugivory syndrome” and has often diverted attention from endozoochory by non-frugivores (e.g. waterbirds and large herbivores) that disperse a broad range of angiosperms, for which they likely provide the maximum dispersal distances. Neither the endozoochory nor the epizoochory syndromes provide helpful predictions of which plants non-frugivores disperse, or by which mechanism. We combined data from Albert et al. (2015a), Soons et al. (2016) and Julve (1998) to show that only 4% of European plant species dispersed by ungulate endozoochory belong to the corresponding syndrome, compared to 36% for ungulate epizoochory and 8% for endozoochory by migratory ducks. In contrast, the proportions of these species that are assigned to an “unassisted syndrome” are 37%, 31% and 28%, respectively. Since allocated syndromes do not adequately account for zoochory, empirical studies often fail to find the expected relationship between syndromes and LDD events such as those underlying the colonization of islands or latitudinal migration. We need full incorporation of existing zoochory data into dispersal databases, and more empirical research into the relationship between plant traits and the frequency and effectiveness of different dispersal mechanisms (paying attention to unexpected vectors). Acknowledging the broad role of non-frugivores in facilitating LDD is crucial to improve predictions of the consequences of global change, such as how plant distributions respond to climate change, and how alien plants spread. Networks of dispersal interactions between these vertebrates and plants are a vital but understudied part of the Web of Life. The datasets we present here illustrate these limitations of syndromes, and include data from Brochet et al. (2010) regarding the syndromes of plants dispersed by Eurasian Teal via epizoochory or endozoochory.

Methods This dataset is a compilation of previously published and freely available datasets on seed dispersal and plant traits from the following sources:

Albert, A. et al. 2015. Seed dispersal by ungulates as an ecological filter: a trait-based meta-analysis. - Oikos 124: 1109-1120.

Julve, P. 1998. Baseflor. Index botanique, écologique et chorologique de la flore de France. - accession date 2020/07/01 (http://perso.wanadoo.fr/philippe.julve/catminat.htm).

Soons, M. B. et al. 2016. Seed dispersal by dabbling ducks: an overlooked dispersal pathway for a broad spectrum of plant species. - Journal of Ecology 104: 443-455.

Brochet, A.-L. et al. 2010. Plant dispersal by teal (Anas crecca) in the Camargue: duck guts are more important than their feet. - Freshwater Biology 55: 1262-1273.

This report summarizes the Waterfowl Breeding Population and Habitat Survey for Yukon Delta, Alaska during 1990. The study area, methods, a comparison of the methods, and a table of waterfowl counts are provided.

Data Sources: Banque informatisée des oiseaux de mer au Québec (BIOMQ: ECCC-CWS Quebec Region) Atlantic Colonial Waterbird Database (ACWD: ECCC-CWS Atlantic Region).. Both the BIOMQ and ACWD contain records of individual colony counts, by species, for known colonies located in Eastern Canada. Although some colonies are censused annually, most are visited much less frequently. Methods used to derive colony population estimates vary markedly among colonies and among species. For example, census methods devised for burrow-nesting alcids typically rely on ground survey techniques. As such, they tend to be restricted to relatively few colonies. In contrast, censuses of large gull or tern colonies, which are geographically widespread, more appropriately rely on a combination of broad-scale aerial surveys, and ground surveys at a subset of these colonies. In some instances, ground surveys of certain species are not available throughout the study area. In such cases, consideration of other sources, including aerial surveys, may be appropriate. For example,data stemming from a 2006 aerial survey of Common Eiders during nesting, conducted by ECCC-CWS in Labrador, though not yet incorporated in the ACWD, were used in this report. It is important to note that colony data for some species, such as herons, are not well represented in these ECCC-CWS databases at present. Analysis of ACWD and BIOMQ data (ECCC-CWS Quebec and Atlantic Regions): Data were merged as temporal coverage, survey methods and geospatial information were comparable. Only in cases where total counts of individuals were not explicitly presented was it necessary to calculate proxies of total counts of breeding individuals (e.g., by doubling numbers of breeding pairs or of active nests). Though these approaches may underestimate the true number of total individuals associated with a given site by failing to include some proportion of the non-breeding population (i.e., visiting adult non-breeders, sub-adults and failed breeders), tracking numbers of breeding individuals (or pairs) is considered to be the primary focus of these colony monitoring programs.In order to represent the potential number of individuals of a given species that realistically could be and may historically have been present at a given colony location (see section 1.1), the maximum total count obtained per species per site since 1960 was used in the analyses. In the case of certain species,especially coastal piscivores (Wires et al. 2001; Cotter et al. 2012), maxima reached in the 1970s or 1980s likely resulted from considerable anthropogenic sources of food, and these levels may never be seen again. The effect may have been more pronounced in certain geographic areas. Certain sites once used as colonies may no longer be suitable for breeding due to natural and/or human causes, but others similarly may become suitable and thus merit consideration in long-term habitat conservation planning. A colony importance index (CII) was derived by dividing the latter maximum total count by the potential total Eastern Canadian breeding population of that species (the sum of maximum total counts within a species, across all known colony sites in Eastern Canada). The CII approximates the proportion of the total potential Eastern Canadian breeding population (sum of maxima) reached at each colony location and allowed for an objective comparison among colonies both within and across species. In some less-frequently visited colonies, birds (cormorants, gulls, murres and terns, in particular) were not identified to species. Due to potential biases and issues pertaining to inclusion of these data, they were not considered when calculating species’ maximum counts by colony for the CII. The IBA approach whereby maximum colony counts are divided by the size of the corresponding actual estimated population for each species (see Table 3.1.2; approximate 1% continental threshold presented) was not used because in some instances individuals were not identified to species at some sites, or population estimates were unavailable.Use of both maxima and proportions of populations (or an index thereof) presents contrasting, but complementary, approaches to identifying important colonial congregations. By examining results derived from both approaches, attention can be directed at areas that not only host large numbers of individuals, but also important proportions of populations. This dual approach avoids attributing disproportionate attention to species that by their very nature occur in very large colonies (e.g., Leach’s Storm Petrel) or conversely to colonies that host important large proportions of less-abundant species (Roseate Tern, Caspian Tern, Black-Headed Gull, etc.), but in smaller overall numbers. Point Density Analysis (ArcGIS Spatial Analyst) with kernel estimation, and a 10-km search radius,was used to generate maps illustrating the density of colony measures (i.e., maximum count by species,CII by species), modelled as a continuous field (Gatrell et al. 1996). Actual colony locations were subsequently overlaid on the resulting cluster map. Sites not identified as important should not be assumed to be unimportant.

Where stable source populations of at-risk species exist, translocation may be a reasonable strategy for re-establishing extirpated populations. However, the success rates of such efforts are mixed, necessitating thorough preliminary investigation. Stochastic population modeling can be a useful method of assessing the potential success of translocations. Here, we report on the results of modeling translocation success for the Hawaiian Common Gallinule (‘alae ‘ula; Gallinula galeata sandvicensis), an endangered waterbird endemic to the Hawaiian Islands. Using updated vital rates, we constructed a model simulating three existing extant (wild) source populations and a hypothetical recipient site on another island. We then projected the effects of six different translocation scenarios and sensitivity of the results to variation of three important demographic parameters on the probability of extinction (PE) of the reintroduced and donor populations. Larger translocations, of at least 30 birds, had low probability of extinction in the reintroduced population, but raised extinction risk of the smallest source population. Spacing out translocations in time (e.g., 10 birds translocated in total in three installments over nine years), led to lower PE than translocating all individuals at once (i.e., bulk translocations) for both the source and reintroduced populations. Brood size and hatch-year juvenile survival had a disproportionate impact on reintroduced population viability. Importantly, the reported juvenile survival rate is very near the threshold for population failure. This suggests that post-introduction and subsequent management of wetlands, particularly predator control, could be critical to reintroduction success. We recommend that individuals should be translocated from multiple, genetically distinct subpopulations to reduce the possibility of inbreeding depression. Based on this analysis, the recipient wetland should be sufficiently large that it can support at least 25 pairs of gallinules. Based on recent estimates of population densities on O‘ahu, such a wetland would need to be between 3.75-74.6 ha. Where stable source populations of at-risk species exist, translocation may be a reasonable strategy for re-establishing extirpated populations. However, the success rates of such efforts are mixed, necessitating thorough preliminary investigation. Stochastic population modeling can be a useful method of assessing the potential success of translocations. Here, we report on the results of modeling translocation success for the Hawaiian Common Gallinule (‘alae ‘ula; Gallinula galeata sandvicensis), an endangered waterbird endemic to the Hawaiian Islands. Using updated vital rates, we constructed a model simulating three existing extant (wild) source populations and a hypothetical recipient site on another island. We then projected the effects of six different translocation scenarios and sensitivity of the results to variation of three important demographic parameters on the probability of extinction (PE) of the reintroduced and donor populations. Larger translocations, of at least 30 birds, had low probability of extinction in the reintroduced population, but raised extinction risk of the smallest source population. Spacing out translocations in time (e.g., 10 birds translocated in total in three installments over nine years), led to lower PE than translocating all individuals at once (i.e., bulk translocations) for both the source and reintroduced populations. Brood size and hatch-year juvenile survival had a disproportionate impact on reintroduced population viability. Importantly, the reported juvenile survival rate is very near the threshold for population failure. This suggests that post-introduction and subsequent management of wetlands, particularly predator control, could be critical to reintroduction success. We recommend that individuals should be translocated from multiple, genetically distinct subpopulations to reduce the possibility of inbreeding depression. Based on this analysis, the recipient wetland should be sufficiently large that it can support at least 25 pairs of gallinules. Based on recent estimates of population densities on O‘ahu, such a wetland would need to be between 3.75-74.6 ha. Methods Reproductive rate data (HAGAVitalRates_9-10-23_Export) We acquired nest data from recent monitoring projects run through the state of Hawaii Department of Land and Natural Resources, Division of Forestry and Wildlife (DOFAW) on O‘ahu, and graduate dissertation work conducted at Hanalei National Wildlife Refuge on Kaua‘i (by BW). Nests on O‘ahu were located during routine weekly or biweekly surveys using an area-search survey. A team of 3–7 observers walked meandering transects with the goal of locating all nests in a given area. All nests were visually checked 2 times per week until hatching or failure. DOFAW nest monitoring continued throughout the annual cycle. A subset of Hawaiian Gallinule nests on O‘ahu was monitored from January through December 2020–2023. All nests were visually checked at least twice weekly, and a subset was monitored from January through December 2020–2023 using SPYPOINT Solar Dark (GG Telecom, Quebec, Canada) passive infrared cameras (trigger speed: 0.07 s) placed about 1 m from the nest, mounted on a 7.6 cm wide metal post 1.8 m long, fixed with a fully adjustable camera mount that allows a camera angle of 0–90. Cameras were programmed to take 2 images back-to-back immediately upon infrared motion activation. Cameras were programmed to take photos instantly for each activation (Instant setting recovery speed: 0.3 s). Cameras were checked weekly for battery life and SD card data retrieval and were removed either immediately after a nest wasconfirmed failed or after a nest was confirmed successful. A nest was considered successful if at least 1 egg hatched and was considered failed if the eggs all disappeared before the expected hatch date or if signs of predation (e.g., predator scat/tracks in the nest or destroyed eggs adjacent to the nest), flooding (e.g., intact eggs outside nest following an increase in water level or nest submerged under water), or abandonment (e.g., eggs cold to the touch in the morning, hot to the touch in the afternoon) were apparent. On Kaua‘i, nests were found by conducting systematic searches. In wetland units managed strictly for waterbirds, transects spaced 10 m apart were walked, while in taro that was grown on the refuge searches were done by walking the pond perimeter. Although Hawaiian Gallinules can nest year-round (Shallenberger 1977, Byrd and Zeillemaker 1981), searches were concentrated during the main breeding season. Nests also were found incidentally during regular activities by refuge staff and taro farmers. Nests on Kaua‘i were monitored with and without cameras (see Webber 2022 for details of monitoring and assessment of nest fates). All nests were checked every 3–5 d to monitor nest status; if the brood continued to use the nest after hatching and the camera was available, monitoring continued for brood survival data. Brood Survival Data (BroodDatabase_8-24-22) Due to some methodological differences in brood monitoring among datasets compiled in this study, we resampled data to a matching, lowest common temporal resolution. Brood data from Keawawa wetland (O‘ahu) were recorded via multiple daily surveys for the first 60þ d posthatch by a group of trained citizen science volunteers. Brood encounter data on Kaua‘i were collected based on 4 d encounter intervals, recording presence and number of chicks if the brood was detected on any day within the interval. All brood records in our Kaua‘i dataset were collected by BW, and they were monitored by surveying telemetered adults (see Webber 2022 for details). Territories with known nests were monitored starting at what was estimated to be mid-incubation, and visited at least once every 4 d. At James Campbell National Wildlife Refuge (O‘ahu), brood encounters were opportunistic. Except for data from Keawawa, most brood monitoring ended after the first month post-hatch. Based on these data formats, we reduced our combined data to 4 d intervals and the first 30 d post-hatch to avoid estimating parameters with a sparse dataset.

Cameron C. 2025. Waterbird species–area relationships at Florida lakes: validating a management threshold using citizen science data. Lake Reserv Manage. XXX–XXX.Surface area and waterbird species richness are highly correlated at lakes around the world. In Florida, this relationship has helped inform establishment of lake regulatory levels. Leveraging professional and citizen science waterbird species richness datasets for 25 Florida lakes, this study demonstrates the ability of eBird citizen science data to detect relative differences in species richness among lakes. Then a statewide species–area evaluation is completed using eBird data for 236 lakes. The results generally support an existing 15% lake area reduction threshold, corresponding to a loss of one waterbird species, used by some Florida lake managers to limit species richness decreases. However, a more conservative 12% threshold may be warranted for lakes with characteristics different from those in previous studies. Methods for the use of eBird data to assess relative species richness differences, account for sampling effort, and establish regulatory thresholds may translate to other regions. While this approach considers one narrow aspect of lake ecology and should only be used as part of a suite of ecologic and hydrologic metrics, it can serve as a practical and critical backstop for lake protection.

In many situations, colonial waterbird colony size is best evaluated from aerial photographs taken during the breeding season. This is typically the case where colonies are not accessible or when it is not feasible to count all birds or nests from ground locations or by boat. This dataset presents high resolution aerial imagery and corresponding nest counts of Caspian terns (Hydroprogne caspia), double-crested cormorants (Nannopterum auritum), Brandt’s cormorants (Urile penicillatus), California gulls (Larus californicus), ring-billed gulls (Larus delawarensis), and American white pelicans (Pelecanus erythrorhynchos) nesting in the Columbia River Basin, during the 2023 breeding season. Photos were taken from a fixed-wing aircraft during peak nesting, and colony size was estimated by digitizing photos and enumerating visible birds using ArcGIS and DotDotGoose. Colony size was reported as the number of birds on colony, and, in the case of terns and cormorants, the number of active breeding pairs. These data are part of a wider project to evaluate the efficacy of management actions to reduce the impacts of predation by piscivorous colonial waterbirds on Endangered Species Act (ESA)- listed juvenile salmonids (smolts; Oncorhynchus spp.) in the Columbia River Basin. Methods Three fixed-winged aerial surveys were conducted in 2023, on the 13th–15th May, 3rd–5th June, and 15th–16th June, to help identify all active nesting colonies of piscivorous waterbirds in the region. To estimate the size of waterbird colonies, aerial photos were taken at oblique angles using a Canon EOS 7D digital SLR camera with one of two image stabilizing lenses, Canon EF 70 - 200mm or Canon EF 100 - 400mm. The lens and camera settings used is included within the image metadata. Photos were taken through the open window of the plane during low altitude flyovers, ~800 – 1,200 feet above the colonies. Aerial images were reviewed and select images were imported to ArcGIS (ESRI 2020. ArcGIS Desktop: Release 10.8.1. Redlands, CA) or DotDotGoose (Ersts, P.J. Version 1.7.0. American Museum of Natural History, Center for Biodiversity and Conservation) to be used for manual colony photo counts. Using ArcGIS, point shape files were created for each image or series of images depending on colony size. In both programs, points were placed manually on either attended nests or individual birds and then summed to give the total. To estimate the number of breeding pairs, direct counts of attended nests were used. However, in some situations it was not possible to count breeding pairs or nests, in these cases the number of individuals was used as a surrogate for breeding colony size. Each photo was counted by at least two counters. To generate an estimate of error, all counters conducted two complete passes of the same photo(s). A pass was defined as examining all areas thoroughly enough that any bird captured in the photo may be counted. To improve the accuracy and consistency of the counts, the total count from each counter was always within 10% of the other. If the count data resulted in differences larger than 10%, counters conducted a third pass or recounted until the average of both counts was within 10%. Once all images were counted, the peak count was determined for each colony and species by comparing total counts from each aerial survey. Each species had a specific counting method. American white pelicans All individual American white pelicans that were visible on or near the breeding site were counted. Birds flying over the colony were not counted. Once chicks were large and mobile, no counts were made and the photo(s) were recorded as “mobile chicks- not counted”. California gulls and Ring-billed gulls All individual gulls that were visible on the colony were counted. Birds flying over the colony were not counted. The two gull species are not consistently distinguishable from aerial photos, therefore, California gulls and ring-billed gulls were grouped and counted together as the total numbers of breeding "gulls" at a colony. If chicks were large and mobile, no counts were made and the photo(s) were recorded as “mobile chicks- not counted”. Caspian terns Caspian terns were counted as either individuals or as attended nests depending on the site. When counting individuals, all Caspian terns visible on the colony were counted. When counting attended nests, all Caspian terns clearly sitting in nest scrapes were counted. If a pair was present at the nest scrape, only one of the birds was counted in an attended nest count. If chicks were large and mobile, no counts were made and the photo(s) were recorded as “mobile chicks- not counted”. Double-crested cormorants and Brandt’s cormorants Early in the breeding season adults were sitting tight on nest structures making nest sites easier to identify, thus attended nests were counted. However, as the breeding season progresses and the number and size of chicks increases, the nest identity can be difficult to determine or be lost. If this was the case, then no counts were made and the photo(s) were recorded as “mobile chicks- not counted”.

Hawai‘i’s endangered waterbirds have experienced epizootics caused by ingestion of prey that accumulated a botulinum neurotoxin produced by the anaerobic bacterium Clostridium botulinum (avian botulism; Type C). Waterbird carcasses, necrophagous flies, and their larvae initiate and spread avian botulism, a food-borne paralytic disease lethal to waterbirds. Each new carcass has potential to develop toxin-accumulating necrophagous vectors amplifying outbreaks and killing hundreds of endangered birds. Early carcass removal is an effective mitigation strategy for preventing avian intoxication, toxin concentration in necrophagous and secondary food webs, and reducing the magnitude of epizootics. However, rapid detection of carcasses can be problematic and labor intensive. Therefore, we tested a new method using scent detection canines for avian botulism surveillance on the island of Kaua‘i. During operational surveillance and a randomized double-blind field trial, trained detector canines with experienced field handlers improved carcass detection probability, especially in dense vegetation. Detector canines could be combined with conventional surveillance to optimize search strategies for carcass removal and are a useful tool to reduce risks of the initiation and propagation of avian botulism. This dataset is one of the three datasets that make up this data release. This table contains GPS track data and environmental parameters from the double-blind detection trials that were intended to compare human searches with canine-assisted searches.

Reason for SelectionThe relative use of beach habitat by shorebird species for nesting, foraging, and breeding is an indicator of beach health and quality. Shorebird populations are highly responsive to threats like sea-level rise, changes in freshwater inflow, shoreline alteration and loss, human disturbances, and contaminants. In particular, the American oystercatcher “has been proposed as a ‘sentinel’ bio-indicator of ecosystem integrity because of the depth of life history information available, its specialized dependence on oysters and associated marine invertebrates, and known reproductive responses to a variety of natural and anthropogenic pressures” (Ogden et al. 2014). As a result of these pressures, North American shorebird populations are experiencing “consistent, steep population loss” (Ronenberg et al. 2019). The species included in this index are already monitored by state and Federal agencies and collectively represent a variety of coastal ecosystem features (e.g., nesting habitat availability and quality, fish and marine invertebrate populations).Input DataSouth Atlantic Blueprint 2021 extentBase Blueprint 2022 extentSoutheast Blueprint 2023 extent2019 National Land Cover Database (NLCD): Land cover2023 U.S. Census TIGER/Line state boundaries, accessed 5-15-2023; download the dataThe following beach bird datasets:Wilson’s plover and American oystercatcher Betsy Von Holle (University of Central Florida) led a project that included state waterbird biologists in the South Atlantic: Tim Keyes, Felicia Sanders, Sara Schweitzer, and Janell Brush. They mapped habitat suitability based on nest, or breeding pair, density per beach segment, as was used for Von Holle et al.’s sea turtle research. The approach is documented in Von Holle et al. 2018. The following nesting years were used for the analysis:American oystercatcher: FL (2005-2011), GA (2010-2011), SC (2008), NC (2007)Wilson’s plover: FL (2005-2011), GA (2010-2011), SC (2009-2011), NC (2007)Piping plover and least tern A previous post-doctoral researcher, Bradley Pickens, processed the following datasets by ranking least tern nest abundance and piping plover individuals by quantile (0-6). They were exported as 90 m rasters. Least ternThe point locations and number of least tern nests, or breeding pairs, were provided by waterbird biologists from each state’s natural resource department (Tim Keyes, Felicia Sanders, Sara Schweitzer, and Janell Brush). All least tern locations were buffered by 1 km. Although least tern do not actively forage on the beach itself, the buffer characterizes habitat selected by least tern (i.e., beach width, predator abundance, etc.) and accounts for interannual variability in nesting locations. Among years, data showed least tern often shifted the location of nests in the general vicinity of previous years. Piping plover (winter distribution) The 2011 winter population census of piping plover was provided by the U.S. Geological Survey, as the international census is repeated every five years. Locations were buffered with a 2 km radius. Although home range estimates exist for piping plover (Cohen et al. 2008, Drake et al. 2001), these measures depict primarily linear habitats. We used a 2 km buffer, as this is similar to the mean linear distance of 4.2 km that piping plover moved during winter in Texas (Drake et al. 2001). The resulting buffer was also substantiated by maps in Cohen et al. (2008).Mapping StepsVon Holle et al. used a categorical habitat suitability ranking based on six quantiles of nest density, or breeding pair density, for each species on the Atlantic Coast. Convert to numeric scores by assigning a value of 0 to polygons rated as “none”, a value of 1 to those rated as “low”, a value of 2 to those rated as “moderate”, a value of 3 to those rated as “moderately high”, a value of 4 to those rated as “high”, a value of 5 to those rated as “very high”, and a value of 6 to those rated “extremely high”. Convert the polygons to a separate raster for each species (Wilson’s plover and American oystercatcher), assigning those numeric values.Resample and reproject the least tern and piping plover source data from 90 m pixels to 30 m pixels so it can be used in Zonation in a later step.Create a mask to define the extent of the Zonation run that will be used to create this indicator. Use cell statistics to combine all 4 bird rasters (the two Von Holle rasters created in the previous step, and the 90 m piping plover and least tern rasters) with the output statistic maximum value. Include in the mask all pixels with a value >0 on any of the bird rasters.To create the beach bird index, use the software program Zonation v4 with the core-area algorithm and without the edge removal option (removal rule = 1, edge removal = 0, warp = 1). Input the mask and the rasters for all four species. Zonation produces a continuous ranking of all pixels within the mask based on their importance for the 4 beach-nesting bird species.Reclassify the output Zonation rank raster into 5 classes, seen in the final indicator values below. This layer represents the relative use of habitat for beach nesting birds in the South Atlantic. Generally, areas with higher values in this layer are considered to have greater relative abundance of beach nesting birds than areas with lower values.To create an analysis extent for the indicator, buffer the polygons provided by Von Holle by 25 km. Assign a value of 0 to all pixels within the analysis extent that do not already receive a score elsewhere in the indicator. Zero values are intended to help users better understand the extent of this indicator and make it perform better in online tools.Clip to the South Atlantic Blueprint 2021 extent.Further limit the extent of the zero class by removing pixels from Virginia, because the source data did not cover Virginia. Also, remove deep marine areas that are not covered by a value of 0 or greater in the 2019 NLCD, where this terrestrial indicator does not apply.Clip to the spatial extent of Base Blueprint 2022.As a final step, clip to the spatial extent of Southeast Blueprint 2023.Note: For more details on the mapping steps, code used to create this layer is available in the Southeast Blueprint Data Download under > 6_Code. Final indicator valuesIndicator values are assigned as follows:5 = >80th percentile of importance for bird index species (American oystercatcher, Wilson’s plover,least tern, and piping plover)4 = >60th-80th percentile of importance3 = >40th-60th percentile of importance2 = >20th-40th percentile of importance1 = ≤20th percentile of importance0 = Open water or not identified as a priority for bird index speciesKnown IssuesBeach bird survey data are summarized by beach segment and do not account for variations in density within those segments.Volunteers often collect beach bird data in discrete time frames and survey effort may differ by location. Some areas may not have been surveyed or nests may have been missed. Therefore, this data does not imply absence of species.Red knot is not included due to lack of data.This indicator may underestimate beach bird use of dune areas inland of beach segments because of inconsistencies in the extent of the various bird models.The spatial resolution of the source data for least tern and piping plover has been degraded. While the indicator has a 30 m resolution, it was not created directly from the spatially precise input data for those two birds. Here, we resampled the 90 m resolution data used in the previous version of the indicator back down to 30 m resolution so that we could use it in Zonation.The indicator has an extraneous “tail” of zero values at its southern edge. This is an artifact of how the buffer of zero values was created. Since zero values do not influence Zonation, this does not affect the final Blueprint priorities. It was discovered too late to fix in this update cycle. We hope to make a larger improvement to this indicator in the future to better depict important areas for beach birds across more of the region’s coastline.Disclaimer: Comparing with Older Indicator VersionsThere are numerous problems with using Southeast Blueprint indicators for change analysis. Please consult Blueprint staff if you would like to do this (email hilary_morris@fws.gov).Literature CitedCohen, J.B., Karpanty, S.M., Catlin, D.H., Fraser, J.D., Fischer, R.A., 2008. Winter Ecology of Piping Plovers at Oregon Inlet, North Carolina. Waterbirds 31, 472-479. [https://doi.org/10.1675/1524-4695-31.3.472]. Drake, K.R., Thompson, J.E., Drake, K.L., Zonick, C., 2001. Movements, habitat use, and survival of nonbreeding Piping Plovers. The Condor 103, 259-267. [https://doi.org/10.1093/condor/103.2.259]. Moilanen, A., L. Meller, J. Leppänen, F.M. Pouzols, H. Kujala, A. Arponen. 2014. Zonation Spatial Conservation Planning Framework and Software V4.0, User Manual. [https://github.com/cbig/zonation-core/releases/download/4.0.0/zonation_manual_v4_0.pdf]. Ogden, John C., John D. Baldwin, Oron L. Bass, Joan A. Browder, Mark I. Cook, Peter C. Frederick, Peter E. Frezza, Rafael A. Galvez, Ann B. Hodgson, Kenneth D. Meyer, Lori D. Oberhofer, Ann F. Paul, Pamela J. Fletcher, Steven M. Davis, Jerome J. Lorenz. Waterbirds as indicators of ecosystem health in the coastal marine habitats of southern Florida: 1. Selection and justification for a suite of indicator species, Ecological Indicators, Volume 44, 2014, Pages 148-163, ISSN 1470-160X, [https://doi.org/10.1016/j.ecolind.2014.03.007]. Von Holle, B., Irish, J. L., Spivy, A., Weishampel, J. F., Meylan, A., Godfrey, M. H., Dodd, M., Schweitzer, S.H., Keyes, T., Sanders, F., Chaplin, M. K. 2018. Effects of future sea level rise on coastal habitat. The Journal of Wildlife Management 9999. [https://wildlife.onlinelibrary.wiley.com/doi/epdf/10.1002/jwmg.21633]. Rosenberg, Kenneth & Dokter, Adriaan & Blancher, Peter & Sauer,

Migratory divides separate populations of migratory animals, facilitating the evolution of intraspecific differences in migration strategies. Migration strategies are expected to be different for birds using different flyways and environments, but the knowledge regarding the impact of the flyway on individual migration strategies is scarce. By using satellite tracking and neckband resightings, we reveal the existence and structure of a gradual migratory divide between two European flyway populations of greylag geese Anser anser. Birds breeding at the far end of the Gulf of Bothnia in the Baltic Sea coast use the Western Flyway; those breeding in the Gulf of Finland the Central Flyway and those breeding between these extremes scatter to the two flyways. By using Gaussian process modelling, we show that migration strategies differed between the flyways. The birds using Western Flyway migrated earlier in autumn, performed longer annual migration and made a clear stopover during migration, ..., The data is satellite tracking data collected at the University of Turku and at the Natural Resources Institute Finland (contact information: Tuomas Seimola, tuomas.seimola@luke.fi). The data has been subsetted by removing several variables (accelerometer, magnetometer measurements, etc.) and including only one location per hour. For the complete data, please contact Antti Piironen and Tuomas Seimola., , GENERAL INFORMATION

1. Content: This dataset contains data used in the following publication: Piironen, A. & Laaksonen, T. 2023: A gradual migratory divide determines not only the direction of migration but also migration strategy of a social migrant bird. Proceedings of the Royal Society B: Biological Sciences. https://doi.org/10.1098/rspb.2023.1528

2. Author information for the data: Name: Antti Piironen Institution: University of Turku Email: antti.p.piironen@utu.fi, antti.p.piironen@gmail.com

Name: Toni Laaksonen Institution: University of Turku Email: tokrla@utu.fi

Name: Tuomas Seimola Institution: Natural Resources Institute Finland Email: tuomas.seimola@luke.fi

3. Date of data collection: Years 2019-2022

4. Geographic location of data collection: Finland

SHARING/ACCESS INFORMATION

1. Links to publications that cite or use the data: Piironen, A. & Laaksonen, T. 2023: A gradual migratory divide determines not only the direction of migration but also migration...

In the Laurentian Great Lakes region, the double-crested cormorant (Phalacrocorax auritus) has seen a thousand-fold population increase in recent decades. These large colonies of birds now often conflict with socioeconomic interests, particularly due to perceived competition with fisheries and the destruction of terrestrial vegetation in nesting habitats. Here we use dated sediment cores from ponds on islands in eastern Lake Ontario that receive waste inputs from dense colonies of cormorants and ring-billed gulls (Larus delawarensis) to chronicle the population rise of these species and assess their long-term ecological impacts. Modern water chemistry sampling from these sites reveals drastically elevated nutrient and major ion concentrations compared to reference ponds not influenced by waterbirds. Geochemical tracers in dated sediment cores, particularly δ15N and chlorophyll-a concentrations, track waterbird influences over time. Fossil diatom assemblages were dominated by species tolerant of hyper-eutrophic and polluted systems, which is in marked contrast to assemblages in reference sites. In addition to establishing long-term ecological impacts, this multi-proxy paleoecological approach can be used to determine whether islands of concern have been long-term nesting sites or were only recently colonized by cormorant or ring-billed gull populations across the Great Lakes, facilitating informed management decisions about controversial culling programs.