Monitoring Avian Productivity and Survivorship (MAPS) 6-Year Summary, Naval Outlying Landing Field, Imperial Beach, Southwestern San Diego County, California, 2014–20

Open-File Report 2023-1055
Ecosystems Mission Area—Species Management Research Program
By: , and 

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Acknowledgments

This project was funded by Commander, Navy Region Southwest and the San Diego Association of Governments. Kurt Roblek and Brian Collins from the Tijuana Slough National Wildlife Refuge assisted in site logistics. The authors thank the many biologists who assisted in data collection for this project: Erica Harris from Helix Environmental Planning; Brett Hartl from the Center for Biological Diversity; Jessica Looney from the San Diego Zoo Safari Park; Melanie Madden and Tiffany Shepherd from the U.S. Navy; John Martin, Samantha Padilla, and Sabrina West from the U.S. Fish and Wildlife Service; and Alessandro Bartolo, Annabelle Bernabe, Thomas Dayton, Logan Derderian, Collin Farmer, Kim Geissler, Jonathan Gunther, Katherine Hall, Sara Harris, Alexandra Houston, Scarlett Howell, Marcus Hubbell, Brandon Miller, Christina Santa Maria, Rachelle McLaughlin, Ryan Pottinger, Michelle Treadwell, and Stéphane Vernet from the U.S. Geological Survey.

Executive Summary

From 2014 to 2020, a Monitoring Avian Productivity and Survivorship (MAPS) banding station (station) was operated at the Naval Outlying Landing Field (NOLF), Imperial Beach, in southwestern San Diego County, California. The station was established as part of a long-term monitoring program of Neotropical migratory bird populations on NOLF and helps Naval Base Coronado (NOLF is a component) meet the goals and objectives of the Department of Defense Partners in Flight program and the Birds and Migratory Birds Management Strategies of the Naval Base Coronado Integrated Natural Resources Management Plan. The station was established in 2009 and has been in operation during the spring and summer since 2009 except for 2016 when it was not funded. The station was operated by AMEC Earth and Environmental, Inc., from 2009 to 2011, by the U.S. Geological Survey from 2012 to 2015, the San Diego Natural History Museum in 2017, and the U.S. Geological Survey again from 2018 to 2023. This report synthesizes results from 2014 to 2020. A prior report presents summaries and analyses from 2009 to 2013.

The banding station at NOLF was operated according to the standard MAPS protocol with some exceptions. Ten mist nets used to capture birds were erected in fixed locations that remained consistent between and within years, with few minor relocations. Nets were open for 6 hours per day, once every 10 days (a netting period) for 13 netting periods starting April 1 each year. Occasionally, poor weather conditions (for example, rain, wind, or excessive heat) prevented net operation or forced nets to be closed early (or, rarely, late). Nets were checked periodically throughout the day and birds were removed, processed (leg bands affixed, measurements recorded), and released.

From 2014 to 2020, we had 3,543 captures (including initial captures and recaptures) of a maximum of 3,264 year-unique captures (543±143 year-unique captures [the total number of individual birds captured for the first time each year]). The count of year-unique captures included 2,702 newly banded birds, 258 individuals that were recaptured from previous years, and 304 birds that were released unbanded (218 hummingbirds and 86 other birds that were intentionally released unbanded [game birds, and so forth] or escaped before banding). Individuals of 68 species were captured, 39 of which breed at or in the immediate vicinity of the MAPS banding station. Bird capture rate averaged 43±30 captures per day (corrected to account for variation in effort) for all years (range 7–163 effort-corrected captures per day) and species richness per year averaged 43±4. Bushtit (Psaltriparus minimus) was the most abundant species captured, followed by Orange-crowned Warbler (Leiothlypis celata), Wilson’s Warbler (Cardellina pusilla), House Finch (Haemorhous mexicanus), Song Sparrow (Melospiza melodia), and Common Yellowthroat (Geothlypis trichas). The mean adult sex ratio of all species combined across all years was 54:46 male:female. Adults averaged 73±12 percent of known age captures per year (range 59–94 percent), and juveniles averaged 27±12 percent (range 6–41 percent).

Nineteen sensitive species were detected at NOLF (12 captured and 7 observed only). During 2014–20, we captured one State and federally endangered species, Least Bell’s Vireo (Vireo bellii pusillus); one federally threatened species, California Gnatcatcher (Polioptila californica); one State endangered species, Willow Flycatcher (Empidonax traillii); and two State species of concern, Yellow-breasted Chat (Icteria virens) and Yellow Warbler (Setophaga petechia). One additional State species of concern, Northern Harrier (Circus hudsonius), was observed at the MAPS banding station but not captured. Peregrine Falcon (Falco peregrinus) and White-tailed Kite (Elanus leucurus), California State fully protected species, also were observed at the MAPS banding station. Seven federal bird species of conservation concern—Calliope Hummingbird (Selasphorus calliope), Rufous Hummingbird (Selasphorus rufus), Allen’s Hummingbird (Selasphorus sasin), Nuttall’s Woodpecker (Dryobates nuttallii), Wrentit (Chamaea fasciata), California Thrasher (Toxostoma redivivum), and Lawrence’s Goldfinch (Spinus lawrencei)—also were captured, and four additional federal bird species of conservation concern—Willet (Tringa semipalmata), Western Gull (Larus occidentalis), California Gull (Larus californicus), and Bullock’s Oriole (Icterus bullockii)—were observed but not captured.

Local population trends varied among species and years. From 2012 to 2019, year-round residents Bushtit, Song Sparrow, and Common Yellowthroat significantly decreased, whereas the migrant Least Bell’s Vireo increased. The total number of captures for all species except Least Bell’s Vireo was lowest in 2017, corresponding to the habitat damage caused by Kuroshio shot hole borer beetle (Euwallacea kuroshio) in the Tijuana River Valley.

Annual productivity and annual adult survival were calculated for seven breeding species based on criteria used by the Institute for Bird Populations (Least Bell’s Vireo, Bushtit, Wrentit, House Wren [Troglodytes aedon], Song Sparrow, Orange-crowned Warbler, and Common Yellowthroat). Productivity was highest for most species in 2010 and 2019, years with high precipitation, and lowest in 2014 and 2018, years with low precipitation. Song Sparrow demonstrated the highest productivity among species and Least Bell’s Vireo had the lowest productivity. Annual adult survival was generally high from 2011 to 2012 and from 2018 to 2019. Bushtit had higher annual survival with lower late winter precipitation. Either temperature or precipitation was associated with productivity for all species except Wrentit, and with survival for all species except Least Bell’s Vireo and Common Yellowthroat. For most species, productivity was positively associated with precipitation, and both productivity and survival were negatively associated with temperature. Other studies have found that higher temperatures led to increased predation by snakes and birds and also increased vector-borne disease transmission, such as West Nile virus. Predicted regional increases in temperature over the next 30 years will likely affect the demographics of these species.

The Song Sparrow population increased with higher breeding productivity during the previous year, and the Bushtit population increased with higher annual survival and higher productivity during the previous year. Aside from a possible positive association between survivorship and Common Yellowthroat population growth, productivity and survival rates did not appear to influence population change for other focal species.

Introduction

Monitoring Avian Productivity and Survivorship (MAPS) is an international monitoring program coordinated by the Institute for Bird Populations (IBP), which uses bird capture and banding data to compile basic demographic parameters of resident and migratory species, many of which are imperiled regionally and even globally. Age- and sex-specific data on annual survival, reproduction, and recruitment can be gathered and compared across stations to identify population trends for species of interest and to identify proximate factors responsible for trends, particularly negative trends. In turn, information obtained from long-term monitoring of bird populations can be used to guide management activities intended to maintain or re-establish viable populations throughout the ranges of species.

A MAPS banding station was established in 2009 at the Naval Outlying Landing Field (NOLF), Imperial Beach, in southwestern San Diego County, California (S. Myers, AMEC Earth and Environmental, Inc., unpub. data, 2011). The station was established as part of a long-term monitoring program of Neotropical migratory bird populations on NOLF and helps Naval Base Coronado meet the goals and objectives of the Department of Defense Partners in Flight (DOD PIF) program and the Birds and Migratory Birds Management Strategies of the Naval Base Coronado Integrated Natural Resources Management Plan (U.S. Navy, 2013). This project also supports the Memorandum of Understanding between the DOD and U.S. Fish and Wildlife Service (USFWS) to promote the conservation of migratory birds by implementing an existing, nationwide bird monitoring program at NOLF (U.S. Navy, 2013). The station is operated in a manner consistent with other banding stations participating in an effort to monitor birds worldwide. The station was operated by AMEC Earth and Environmental, Inc. from 2009 to 2011, by the U.S. Geological Survey (USGS) from 2012 to 2015, by the San Diego Natural History Museum in 2017, and again by USGS from 2018 to 2023. The station was not operated in 2016.

There were four objectives for this project: (1) to estimate population sizes and trends for various Neotropical migratory bird species, (2) to estimate demographic and survival parameters for Neotropical migratory bird species, (3) to estimate annual productivity for these species, and (4) to augment existing distributional information for sensitive avian species. This report summarizes banding efforts and results for 2014–20 and population trends, survival parameters, and productivity for 2009–20.

Methods

Site Description

The MAPS banding station was located on NOLF, which encompasses about 509 hectares (ha) in southwestern San Diego County, including 112 ha of roads and developed areas. The site is 16 kilometers (km) south of Naval Air Station North Island (NASNI) and 2.4 km north of the United States-Mexico border. Navy lands extend into the Tijuana River National Estuarine Research Reserve, co-managed by USFWS, the National Oceanic and Atmospheric Administration, and California State Parks (fig. 1). Parts of NOLF are managed cooperatively with the Tijuana Slough National Wildlife Refuge under a memorandum of understanding between NASNI and the USFWS relating to the protection of natural resources. Vegetation at the station was a mix of riparian willow (Salix spp.) forest dominated by arroyo willow (S. lasiolepis), red willow (S. laevigata), black willow (S. gooddingii), and mule fat (Baccharis salicifolia); and riparian scrub dominated by mule fat and sandbar willow (S. exigua).

1. Aerial view of southern San Diego County with the Naval Base boundary, the banding
                        station boundary, and net locations.
Figure 1.

Location of the Monitoring Avian Productivity and Survivorship banding station, Naval Outlying Landing Field, Imperial Beach, California.

Bird Banding

Bird banding at NOLF followed the standardized MAPS protocol (DeSante and others, 2021). Ten mist nets, placed a minimum of 65 meters (m) apart, were erected in fixed locations selected for their potential to capture birds moving through vegetation (table 1; fig. 2). In 2015, two nets were discontinued when trails were closed to discourage unlawful access and were replaced by two new net lanes within the station. Mist nets were made of 30-millimeter (mm) mesh black nylon and were 12-m long by 2.6-m high with four trammels (pockets) running the length of the net. Nets were suspended from vertical aluminum poles anchored by permanent rebar stakes and covered a vertical area ranging from about 0.25 to 2.50 m above ground. Nets were opened within 30 minutes of dawn and remained open for 6 hours, typically until between 1200 and 1300 Pacific Daylight Time (PDT). Nets were not operated during inclement weather such as strong wind, rain, extreme heat, or cold. If nets were not operated for a minimum of 3 hours during a particular period (for instance, if nets were closed early because of inclement weather), we scheduled a make-up day during the same period. On the make-up day, we opened the nets at the approximate time that nets were closed on the short day and then closed the nets when the 6 hours intended for the period were reached.

Table 1.    

Global Positioning System locations of mist nets at Monitoring Avian Productivity and Survivorship banding station, Naval Outlying Landing Field, Imperial Beach, California.

[Coordinates are in World Geodetic System of 1984 (WGS 84). Nets 5 and 6 were operated 2009–14; nets 11 and 12 were operated 2015, 2017–20. All other nets were operated 2009–15 and 2017–20. For net numbers, see figure 2]

Net number Longitude Latitude
1 −117.10307 32.55817
2 −117.10341 32.55808
3 −117.10425 32.55813
4 −117.10594 32.55818
5 −117.10689 32.55857
6 −117.10833 32.55804
7 −117.10831 32.55862
8 −117.10837 32.55948
9 −117.10489 32.55864
10 −117.10386 32.55895
11 −117.10616 32.55928
12 −117.10677 32.55981
Table 1.    Global Positioning System locations of mist nets at Monitoring Avian Productivity and Survivorship banding station, Naval Outlying Landing Field, Imperial Beach, California.
2. Aerial view of station with net locations in red squares and yellow triangles.
Figure 2.

Net locations at Monitoring Avian Productivity and Survivorship banding station, Naval Outlying Landing Field, Imperial Beach, California.

Nets were checked every 30–40 minutes by operators working circuits. Hummingbirds, game birds, and other non-passerines were not banded but were identified by species, age, and sex (when possible) and then released. Birds were removed from nets, held in cloth bags labeled with the net number, and taken to a central processing location where they were banded with numbered Federal aluminum bands. From 2014 to 2019, Least Bell’s Vireo (Vireo bellii pusillus) captured at this MAPS banding station were color-banded with a unique color combination for visual identification as part of a separate survey effort for this species (10[A][1][a] federal recovery permit number ESPER0004080). Using the Identification Guide to North American Birds (Pyle, 1997) as a reference, data recorded for each individual captured (all species) included age, sex, skull ossification, breeding condition, weight, wing chord, fat deposition, feather wear, and molt status. Birds that already had bands when captured also were processed, and their band numbers were recorded. These birds were considered recaptures. We recorded only the initial capture of a bird on each banding day (we did not record same-day recaptures). A bird was considered a recapture on each unique day it was captured after its original banding. Birds were held for 5–45 minutes depending on the number of birds captured during one net run. After processing, juveniles, brooding females, and resident birds from the more distant nets were released near the net in which they had been captured, whereas all other birds were released at the central processing location. A list of all birds observed was kept for each banding day, including species not captured and their possible breeding status at the MAPS banding station. A minimum of four personnel typically operated the MAPS banding station.

Banding Schedule

The MAPS banding station was operated 1 day during every 10-day period from April 1 to August 8 (for a total of 13 banding days per year), except in 2020, when flooding prevented our access to the banding station for the first period in April. Most North American MAPS stations operate during the standard MAPS season (May 1–August 8). Starting in 2012, we added netting periods in April to accommodate earlier breeding species, such as Orange-crowned Warbler (Leiothlypis celata), and for comparisons with other MAPS banding stations in San Diego County, which begin operation in April (Lynn and others, 2018; B. Kus, U.S. Geological Survey, unpub. data, 2021).

Data Analysis

Captures

All banding data were entered into MAPSPROG (the IBP data entry program) for verification and error-checking, which also included cross-checking against data from previous years. Finalized MAPSPROG data were submitted to IBP and Naval Base Coronado each year. This report presents a summary of banding data from 2014 to 2020 and analyses of longer-term population trends, productivity, and survivorship from 2009 to 2020 (2009–13 data are available in Lynn and others, 2015).

Bird captures were quantified by species, age, sex, and number of captures for each year. The total number of captures (including newly banded birds, captured but unbanded birds, and all recaptures) was used to create a captured species list and a total count of captures per species for the MAPS banding station. For analyses, year-unique captures were the total number of individuals captured for the first time each year, including newly banded birds, first-time recaptures of birds originally banded in previous years, and unbanded birds. The population size for each species was the number of year-unique adult captures, corrected for effort (see the “Effort Corrections” section). Hummingbirds and other unbanded birds were included in the total count of captures, the captured species list, and year-unique captures, but they were not included in further analyses of productivity or survival because we could not determine individual identity. We included hummingbirds and other unbanded captures as separate individuals in year-unique captures even though some may have been captured more than once during the season. We calculated species richness defined as the number of species captured at the MAPS banding station, relative species abundance defined as the proportion of all year-unique captures, corrected for effort (see the “Captures” and “Effort Corrections” sections) represented by a particular species, and sex and age ratios (to determine the structure of the population) for all species captured.

Effort Corrections

Netting effort varied between years as a result of adding netting periods in April (starting in 2012) and missing periods or truncating days in response to inclement weather or other logistical constraints. Because of this variation, the intended effort (10 nets run for 6 hours per period or 60 intended net-hours per period) in a survey was not always met. The timing of missed or gained effort during a season or period can alter capture rate estimates and thus skew vital rate calculations. For example, the ratio of juveniles to adults resulting from not capturing adults during times when nets were closed before young-of-the-year fledge or not capturing juveniles during times when nets were closed after fledging, could result in over- or under-estimating productivity, respectively.

We followed methods developed by DeSante and others (2015) to summarize effort and capture data for a single station and to correct capture data for inconsistencies in seasonal effort with modifications for time of capture during the day. Effort corrections began by dividing the banding day into five time bins relative to sunrise: (1) 1 hour before sunrise to 1 hour after sunrise; (2) 1‒2 hours after sunrise; (3) 2‒3 hours after sunrise; (4) 3‒4 hours after sunrise; and (5) more than 4 hours after sunrise. We then compiled the actual effort expended (number of hours nets were open multiplied by number of nets that were open) for each time bin, each sampling period, and each year (Ab,p,t, where b is time bin [1‒5], p is sampling period [1‒13], and t is year [2009‒20, excluding 2016 when the station was not operated]). Second, we summed actual effort for all time bins within a period to get the total actual effort per period:

(1)
where

e

is total actual effort,

p

is sampling period (1–13),

t

is year 2009–20 (excluding 2016 when the station was not operated),

b

is time bin (1–5), and

A

is actual effort for each time bin.

Third, we calculated the proportion of total actual effort per period represented by each time bin:
(2)
where

H

is the proportion of actual effort per period represented by each time bin,

b

is time bin (1–5),

p

is sampling period (1–13),

t

is year 2009–20 (excluding 2016 when the station was not operated),

A

is actual effort for each time bin, and

e

is total actual effort.

Fourth, we set intended effort (Ib,p,t) as 10 net-hours for time bins 1‒4 and 20 net-hours for time bin 5. Finally, we calculated the proportional difference between intended and actual effort to produce a correction for missed or gained effort within each period for each time bin. If actual effort was less than intended effort, a positive correction would be generated.
(3)
where

h

is the proportional difference between intended and actual effort,

b

is time bin (1–5),

p

is sampling period (1–13),

t

is year 2009–20 (excluding 2016 when the station was not operated),

I

is intended effort per time bin, and

A

is actual effort per time bin.

Captures per year were calculated by age and by species for all year-unique captures (including birds of undetermined age). To calculate captures per year using effort correction, we began by summing the number of year-unique captures for each species by time bin (nAb,p,t for adults, nJb,p,t for juveniles, and nTb,p,t for all captures). Next, we summed the total number of year-unique captures for each species by period by year:

(4)
where

NA

is total number of year-unique adults captured per period per year,

p

is sampling period (1–13),

t

is year 2009–20 (excluding 2016 when the station was not operated),

b

is time bin (1–5), and

nAb,p,t

is the number of year-unique adults captured for each time bin.

(5)
where

is total number of year-unique juveniles captured per period per year,

p

is sampling period (1–13),

t

is year 2009–20 (excluding 2016 when the station was not operated),

b

is time bin (1–5), and

is the number of year-unique juveniles captured for each time bin.

(6)
where

NT

is total number of year-unique captures of all ages per period per year,

p

is sampling period (1–13),

t

is year 2009–20 (excluding 2016 when the station was not operated),

b

is time bin (1–5), and

nTb,p,t

is the number of year-unique captures of all ages for each time bin.

Then, we calculated the proportion of period captures represented by each time bin for each species:
(7)
where

δA

is the proportion of adult captures in a period represented by each time bin,

b

is time bin (1–5),

p

is sampling period (1–13),

t

is year 2009–20 (excluding 2016 when the station was not operated),

nAb,p,t

is the number of year-unique adults captured for each time bin, and

NA

is the total number of year-unique adults captured per period per year.

(8)
where

is for the proportion of juveniles captured in a period represented by each time bin,

b

is time bin (1–5),

p

is sampling period (1–13),

t

is year 2009–20 (excluding 2016 when the station was not operated),

is the number of year-unique juveniles captured for each time bin, and

is total number of year-unique juveniles captured per period per year.

(9)
where

is for proportion of all ages captured in a period represented by each time bin,

b

is time bin (1–5),

p

is sampling period (1–13),

t

is year 2009–20 (excluding 2016 when the station was not operated),

is the number of year-unique captures of all ages for each time bin, and

is total number of year-unique captures of all ages per period per year.

We then calculated an effort correction factor to approximate the proportion of birds missed or gained in a time bin in each period and year that were a result of missing or extra effort:
(10)
where

is the effort correction factor for adults,

b

is time bin (1–5),

p

is sampling period (1–13),

t

is year 2009–20 (excluding 2016 when the station was not operated),

is the proportion of adult captures in a period represented by each time bin,

h

is the proportional difference between intended and actual effort, and

H

is the proportion of actual effort per period represented by each time bin.

(11)
where

is the effort correction factor for juveniles,

b

is time bin (1–5),

p

is sampling period (1–13),

t

is year 2009–20 (excluding 2016 when the station was not operated),

is the proportion of juvenile captures in a period represented by each time bin,

is the proportional difference between intended and actual effort, and

is the proportion of actual effort per period represented by each time bin.

(12)
where

is the effort correction factor for all captures,

b

is time bin (1–5),

p

is sampling period (1–13),

t

is year 2009–20 (excluding 2016 when the station was not operated),

is the proportion of all captures in a period represented by each time bin,

is the proportional difference between intended and actual effort, and

is the proportion of actual effort per period represented by each time bin.

Finally, we calculated the corrected numbers of adults, juveniles, and all captures by species for each year based on the observed number of year-unique captures and effort correction factors:
(13)
where

is the corrected number of adults,

t

is year 2009–20 (excluding 2016 when the station was not operated),

p

is sampling period (1–13),

b

is time bin (1–5),

is the total number of year-unique adults captured per period per year, and

is the effort correction factor for all adult captures.

(14)
where

is the corrected number of juveniles,

t

is year 2009–20 (excluding 2016 when the station was not operated),

p

is sampling period (1–13),

b

is time bin (1–5),

is the total number of year-unique juveniles captured per period per year, and

is the effort correction factor for all juvenile captures.

(15)
where

is the corrected number of all captures,

t

is year 2009–20 (excluding 2016 when the station was not operated),

p

is sampling period (1–13),

b

is time bin (1–5),

is the total number of year-unique captured of all ages per period per year, and

is the effort correction factor for all captures.

For all analyses and results, captures=year-unique effort-corrected captures, unless otherwise indicated.

In table 2, we present an example of effort correction for a hypothetical period 5 banding day in 2016. For this example, 10 nets were open for 5 hours each, and all nets were closed 1 hour early because of excessive wind. Total actual effort (e5,2016) was 50 hours, and total year-unique captures in period 5 (NT5,2016) was 100. For this example, the actual effort in time bin 5 (that is, more than 4 hours after sunrise) was 10 hours, while the intended effort was 20 hours. This corrected the number of captures (nT5,5,2016) upward for that time bin, from 10 captures to 12.5 captures. Therefore, the total number of effort-corrected captures for period 5 in 2016 (CT2016) was 103 (rounded from 102.5).

Table 2.    

Example of effort correction for a hypothetical banding period when actual netting hours were less than intended netting hours.

Time bin
(b)
Actual effort in hours
(Ab,5,2016)
Intended effort in hours
(Ib,5,2016)
Proportion of actual effort per time bin
(Hb,5,2016)
Proportional difference between intended and actual effort per time bin
(hb,5,2016)
Number of year-unique captures per time bin
(nTb,5,2016)
Proportion of captures per time bin
Tb,5,2016)
Effort correction factor per time bin
(cTb,5,2016)
Corrected captures per time bin
(CTb,5,2016)
1 10 10 0.2 0 10 0.1 0 10
2 10 10 0.2 0 30 0.3 0 30
3 10 10 0.2 0 30 0.3 0 30
4 10 10 0.2 0 20 0.2 0 20
5 10 20 0.2 0.5 10 0.1 0.25 12.5
Table 2.    Example of effort correction for a hypothetical banding period when actual netting hours were less than intended netting hours.

Focal Species

For a subset of resident and migratory focal species that breed at the station, we examined seasonal and annual variation in capture rates, productivity (the ratio of juveniles to adults captured, as described later in the “Annual Productivity” section), adult survival (based on analysis of recapture rates using Program MARK, as described later in the “Annual Survival” section), and population trends. All species captured at the MAPS station, except Black-throated Magpie-jay (Calocitta colliei), were considered migratory species covered under the Migratory Bird Treaty Act (U.S. Fish and Wildlife Service, 2020; appendix 1, tables 1.1, 1.2); however, some species considered migratory birds under the Act are known to be year-round residents in southwestern San Diego County, and therefore, were considered resident species in our analyses. According to the MAPS protocol, species were considered breeders if they exhibited persistent territorial singing during the height of the breeding season, or hard evidence of breeding (observation of nest, fledglings, etc.) at the station (as opposed to within the larger surrounding area) at least once during station operation. Year-round resident species in analyses of population trends, productivity, survival, and predictors of population change included Bushtit (Psaltriparus minimus), Wrentit (Chamaea fasciata), House Wren (Troglodytes aedon), Song Sparrow (Melospiza melodia), Common Yellowthroat (Geothlypis trichas), and Orange-crowned Warbler. We considered Orange-crowned Warbler to be resident because the species was present at the MAPS station year-round although it was possible that different subspecies occupied the area in the winter than during the breeding season. Nevertheless, Orange-crowned Warbler populations likely did not move long distances between seasons and therefore were subject to climatic conditions similar to the MAPS station during the non-breeding season. One migratory species, Least Bell’s Vireo, known to winter outside southwestern San Diego County, also was included as a focal species in analyses of population trends, productivity, survival, and predictors of population change.

Seasonal and Annual Variation in Captures

Seasonal and annual variations in capture rates for adults and juveniles were examined for locally breeding focal species that constituted 5 percent or more of captures in at least 6 years over the entire span of the MAPS station operation (2009–20). Bushtit and Orange-crowned Warbler constituted more than 5 percent of captures in all 11 years. Song Sparrow constituted more than 5 percent of captures in 10 of the 11 years, and Common Yellowthroat constituted more than 5 percent of captures in 9 of the 11 years. Wilson’s Warbler (Cardellina pusilla) constituted 5 percent or more of captures in 7 of the 11 years, but only wintered at or migrated through the MAPS banding station; therefore, we did not include it as a focal species. We included a fifth species, Least Bell’s Vireo (a migratory species that breeds at the station and winters south of the station), which constituted 1–5 percent of captures each year, to examine the status of this Federal- and State-protected species at NOLF. We examined the seasonal variation in captures for each of these species by plotting captures by MAPS period. We calculated mean captures from 2014 to 2020 by MAPS period for species that could be assigned an age (adults versus juveniles) and compared these to the annual capture rates of adults and juveniles to examine age-related seasonal trends.

We also examined age structure in captures over the entire span of the MAPS station operation by plotting annual captures of each focal species by age from 2012 to 2019, excluding years when early banding periods were missed (2009, 2010, 2011, and 2020). We examined annual population trends in adult captures from 2012 to 2019 for each of the five focal species using Pearson’s correlations. Any P-values less than 0.10 indicated that populations of that species significantly increased or decreased from 2012 to 2019.

Annual Productivity, Survival, and Predictors of Population Size

Seven focal species, the five focal species analyzed for population trends plus two additional resident species (Wrentit and House Wren), were selected for calculations of annual productivity and survival from 2009 to 2020, based on criteria presented by IBP for survival analyses. These criteria include (1) at least 2.5 individuals of the species captured per year, with a minimum of 30 year-unique captures; (2) at least 2 recaptures; and (3) survival and recapture probability not equal to 0 or 1.

Climate Variables

A number of climate variables had the potential to influence productivity and survival of the seven species we selected for these analyses. We selected climate variables based on their potential to explain annual life stages of the focal species. Specifically, we selected bio-year precipitation, or total precipitation from July 1 (year x−1) to June 30 (year x), a date range which encompasses the entire winter, the typical period of high rainfall in southern California. We also divided annual precipitation into two periods, early winter precipitation (October 1[year x−1]–December 31[year x−1]) and late winter precipitation (January 1[year x]–March 31[year x]), which likely influences the timing of increased availability of food resources (seeds, fruits, and insects). We also selected mean maximum daily temperature in August[year x−1] and mean minimum daily temperature in December[year x−1] to represent the hottest and coldest periods of the year. Mean breeding season temperature (mean temperature from March 1[year x] to June 30[year x]) had the potential to influence breeding productivity. Mean bio-year temperature (mean temperature from July 1 [year x−1] to June 30 [year x]) provided an annual measure of potential climate change within the same period as bio-year precipitation, and it can be useful in comparing with results from other regions. Daily temperature and precipitation data were gathered from the Brown Field Municipal Airport (National Oceanic and Atmospheric Administration, 2022), 11 km east of the MAPS station, for the years that the MAPS station was operated. Daily temperature and precipitation data also were gathered from Brown Field Municipal Airport for the years prior to station operation, when available, including 1945–46, 1954–61, and 1997–2008, to compare historical trends to trends during station operation. We used two-sample Student’s t-tests and Wilcoxon signed-rank tests to compare the means of precipitation and temperature before and during station operation. Any P-values less than 0.10 indicated that precipitation and temperature were significantly different before station operation than they were during station operation.

Annual Productivity

We used generalized linear models with a gaussian probability structure to model the effects of climate variables on annual productivity. Annual productivity is defined as the ratio of effort-corrected young (juvenile) captures to effort-corrected adult captures (CJt/CAt). For each of the seven focal-plus species, we created models relating annual productivity (the response variable) to mean breeding season temperature, mean bio-year temperature, bio-year precipitation, early winter precipitation, and late winter precipitation (predictor variables). To simplify interpretation of model results, we standardized the predictor variables before analysis by subtracting the mean and dividing by the standard deviation. We excluded 2018 Wrentit productivity from our analyses because unique-year captures were unusually low (5 individuals), and 80 percent (4/5) were juveniles, creating an artificially high productivity estimate for that year.

We created a set of a priori models containing the predictor variables and used an information-theoretic approach (Akaike’s Information Criterion for small sample sizes, or AICc) to evaluate support for each model (Burnham and Anderson, 2002). To build our model set, we first generated a constant (null) model to serve as a reference and a set of simple models, each of which contained a single predictor variable. Next, we began creating more complex models by adding other predictor variables to each of the simple models and evaluating them relative to the simpler model, eliminating those that did not improve on the simpler model by at least 2 AICc. All remaining models were ranked such that the highest-ranked model had the lowest AICc. Models were considered well supported if the ΔAICc (difference in AICc from the highest-ranked model) was less than 2. Only models with an AICc weight of at least 0.05 were presented in the final model set. After finalizing our model set, we evaluated the contribution of predictor variables to each model by examining the 90-percent confidence interval associated with the beta estimate for each variable. If the 90-percent confidence interval did not include 0, we had 90-percent confidence that the beta estimate differed from 0, and therefore, we determined that the variable likely contributed to the model. Models were created and summarized using the MuMIn package (version 1.43.17; Bartoń, 2020) in R (R Core Team, 2022).

Annual Survival

We analyzed annual survival of adults for the seven focal-plus species in Program MARK (White and Burnham, 1999) using the RMark package (Laake, 2013) in R (R Core Team, 2022). Survival analysis in Program MARK accounts for individuals that were present but not captured by modeling both survivorship and recapture probability. We estimated adult survival but not first-year survival because first-year survival was low for all species, and therefore, we could not differentiate the probability of survival from recapture probability. Birds that originally were banded as juveniles (during their hatching year) were included in analyses as adults in subsequent years. We created encounter histories for each year from 2009 to 2020, coding capture or recapture as 1 and no capture as 0.

Effort was not constant across years because no nets were opened in early banding periods in some years (2009, 2010, 2011, and 2020). To determine whether differences in effort had an effect on survival analyses, we modeled recapture probability in two ways for each species: (1) one model with constant recapture probability and (2) one model with time-varying recapture probability (allowing recapture probability to vary by year), using constant survival in both models. We compared the AICc of the two models and selected the model with the lowest AICc. Models with constant recapture probability ranked well above models with time-varying recapture probability for all species except Orange-crowned Warbler. Therefore, for all species except Orange-crowned Warbler, we used constant recapture probability in all models. For Orange-crowned Warbler, we allowed recapture probability to vary by year in all models. Because the MAPS station was not operated in 2016, annual survival for 2015–16 and 2016–17 was estimated by MARK by interpolating from other years.

Survival models were created to examine the effects of sex and climate variables on annual survival of adults. Climate variables included bio-year precipitation, early winter precipitation, late winter precipitation, mean bio-year temperature, mean maximum daily temperature in August, and mean minimum daily temperature in December. For species that remained at the MAPS station during the winter (Bushtit, Orange-crowned Warbler, Song Sparrow, Common Yellowthroat, Wrentit, and House Wren), survival models were created with precipitation and temperature during the bio-year ending in the current MAPS season. For species that migrated away from the MAPS station during the winter (Least Bell’s Vireo), survival models were created with precipitation during the bio-year ending in the previous MAPS season because migrants were absent from the MAPS banding station from September to March of the current bio-year and, thus, their survival likely was more influenced by precipitation at the MAPS banding station during the previous bio-year than the current bio-year. Similarly, we did not include mean minimum daily temperature in December in models for Least Bell’s Vireo because the species was not present at the MAPS banding station during December. Model sets were created and evaluated using information theoretic approach (AICc; see the “Annual Productivity” section).

Predictors of Population Change

Breeding productivity and annual survival are inherently linked to changes in bird populations. Absent other influences, higher breeding productivity and higher annual survival should result in increased population size. We used multiple regression to evaluate the contribution of breeding productivity and annual survival to population change (λ, or N[year x+1]/N[year x]) for each of the seven focal-plus species. First, we estimated λ using Pradel reverse-time capture-mark-recapture models (Pradel, 1996) in Program MARK. For all Pradel models, we used constant survival and recapture probabilities to isolate annual λ. Then, we used annual productivity in yearx−1 and annual survival estimates from yearx−1 to yearx as predictors, and λ from yearx−1 to yearx as the response variable in multiple regression analysis. For each predictor within a multiple regression model, P-values less than 0.10 indicate that the predictor, in isolation, significantly influenced the population change of that species. An overall P-value less than 0.10 for the overall multiple regression model indicates that population change was influenced by the combination of predictors.

Data were analyzed using Program R. Analyses were considered significant if P≤0.10. Means are presented with standard deviations. All data from NOLF 2009 to 2013 used in analyses can be found in Lynn and others (2015).

Results

Overview of Captures

In 4,603 net-hours (751±51 net-hours per year) during the 2014–20 MAPS seasons, we had a total of 3,543 captures (591±176 captures per year; table 3). Of the 3,543 total captures, 2,702 were newly banded, 258 were individuals recaptured from previous years, and 304 were released unbanded (218 hummingbirds and 86 other birds that escaped before banding or were intentionally released unbanded, such as game birds) for a total of 3,264 year-unique captures (544±155 unique captures per year). We captured 68 species, 39 of which were confirmed or likely breeders at the MAPS banding station (table 3; appendix 1, table 1.1; unidentified species were not included in the species total).

Table 3.    

Total number of birds captured, banded, recaptured, and released unbanded at Naval Outlying Landing Field, Imperial Beach, California, 2014–20.

[Species: See appendix 1 (tables 1.1, 1.2) for common and scientific names. Total captures: Includes multiple captures of some individuals]

Species Total number
of birds captured
New
individuals banded
Number of
recaptured individuals
Number of
unbanded birds captured
Year Total Year Total Year Total Year Total
2014 2015 2017 2018 2019 2020 2014 2015 2017 2018 2019 2020 2014 2015 2017 2018 2019 2020 2014 2015 2017 2018 2019 2020
SSHA 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1
COHA 2 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 2
MODO 0 2 1 0 2 0 5 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 2 0 0 2 0 4
CGDO 1 3 4 3 3 0 14 0 3 4 3 0 0 10 1 0 0 0 0 0 1 0 0 0 0 3 0 3
GRRO 0 0 1 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 0 0 2
BCHU 8 4 0 2 5 6 25 0 0 0 0 0 0 0 1 0 0 0 0 0 1 7 4 0 2 5 6 24
ANHU 23 24 11 26 20 23 127 0 0 0 0 0 0 0 1 0 0 0 0 0 1 22 24 11 26 20 23 126
COHU 0 1 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 2
CAHU 1 0 0 0 1 4 6 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 1 4 6
RUHU 2 2 1 13 2 7 27 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1 2 1 13 2 7 26
ALHU 3 1 0 8 7 11 30 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 1 0 8 7 11 30
USHU 1 0 0 1 2 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 2 0 4
NUWO 3 1 2 5 8 3 22 2 1 2 4 5 2 16 1 0 0 1 1 1 4 0 0 0 0 0 0 0
DOWO 7 8 8 12 7 10 52 2 7 7 8 6 9 39 2 1 1 1 1 0 6 0 0 0 1 0 0 1
WEWP 1 1 0 1 0 0 3 1 1 0 1 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0
WIFL 7 1 0 0 0 2 10 7 1 0 0 0 2 10 0 0 0 0 0 0 0 0 0 0 0 0 0 0
HAFL 1 1 0 0 0 0 2 1 1 0 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0
GRFL 1 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
PSFL 54 26 12 24 12 25 153 53 24 12 21 12 22 144 0 0 0 0 0 2 2 1 1 0 1 0 0 3
BLPH 0 0 0 2 3 0 5 0 0 0 2 3 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0
ATFL 5 4 5 9 11 4 38 5 4 5 8 10 4 36 0 0 0 1 1 0 2 0 0 0 0 0 0 0
WEKI 0 0 1 1 0 0 2 0 0 1 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0
LBVI 10 10 15 14 36 28 113 4 6 12 6 22 15 65 3 1 2 3 4 3 16 0 0 0 0 0 0 0
HUVI 0 2 4 2 3 2 13 0 2 4 1 3 1 11 0 0 0 1 0 1 2 0 0 0 0 0 0 0
WAVI 37 17 12 36 16 5 123 36 17 12 36 16 5 122 0 0 0 0 0 0 0 0 0 0 0 0 0 0
REVI 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
BTMJ 1 0 0 1 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0 2
TRES 0 0 0 0 1 3 4 0 0 0 0 0 3 3 0 0 0 0 1 0 1 0 0 0 0 0 0 0
NRWS 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
CLSW 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
BUSH 68 75 43 47 79 122 434 32 56 30 31 59 84 292 24 11 2 7 4 12 60 6 0 8 1 1 1 17
BEWR 12 13 8 10 36 8 87 3 9 4 6 25 5 52 6 0 2 3 5 2 18 0 0 1 0 1 0 2
HOWR 16 15 16 17 42 53 159 7 9 10 12 33 37 108 4 1 0 1 3 2 11 0 1 1 3 2 3 10
BGGN 0 0 0 1 1 0 2 0 0 0 1 1 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0
CAGN 0 0 0 0 2 4 6 0 0 0 0 2 0 2 0 0 0 0 0 2 2 0 0 0 0 0 0 0
SWTH 51 0 4 5 6 4 70 51 0 4 5 6 4 70 0 0 0 0 0 0 0 0 0 0 0 0 0 0
HETH 2 2 1 1 1 0 7 2 2 1 1 1 0 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0
WREN 9 16 15 5 33 11 89 4 10 12 5 19 7 57 4 4 1 0 5 2 16 0 0 2 0 0 1 3
CATH 1 0 1 1 1 1 5 1 0 0 1 1 1 4 0 0 1 0 0 0 1 0 0 0 0 0 0 0
OCWA 49 73 18 44 82 77 343 42 54 16 40 66 61 279 5 14 1 1 7 3 31 0 0 1 2 1 0 4
NAWA 1 0 1 2 1 0 5 1 0 1 2 1 0 5 0 0 0 0 0 0 0 0 0 0 0 0 0 0
NOPA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
YEWA 23 18 8 25 21 26 121 20 18 8 25 18 25 114 3 0 0 0 1 0 4 0 0 0 0 0 0 0
AUWA 0 17 1 6 61 1 86 0 17 1 6 61 1 86 0 0 0 0 0 0 0 0 0 0 0 0 0 0
BTYW 0 0 0 4 1 2 7 0 0 0 4 0 2 6 0 0 0 0 0 0 0 0 0 0 0 1 0 1
TOWA 1 2 0 0 1 0 4 1 2 0 0 1 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0
THWH 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
HEWA 2 0 1 0 0 0 3 2 0 1 0 0 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0
PAWA 0 1 2 0 0 0 3 0 1 1 0 0 0 2 0 0 0 0 0 0 0 0 0 1 0 0 0 1
BAWW 0 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
NOWA 0 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
MGWA 11 7 0 2 8 3 31 10 6 0 2 8 3 29 0 0 0 0 0 0 0 0 1 0 0 0 0 1
COYE 37 34 13 16 67 26 193 25 23 10 12 59 24 153 6 4 1 1 2 0 14 0 1 2 3 2 0 8
HOWA 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
WIWA 99 65 5 31 52 34 286 95 65 5 29 50 33 277 0 0 0 0 0 0 0 4 0 0 2 1 1 8
YBCH 11 5 7 1 23 27 74 7 2 6 1 17 22 55 2 3 0 0 0 0 5 0 0 0 0 0 0 0
WETA 1 0 0 0 0 0 1 1 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
GTTO 0 0 1 0 0 0 1 0 0 1 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
SPTO 5 6 0 0 0 0 11 3 2 0 0 0 0 5 2 1 0 0 0 0 3 0 0 0 0 0 0 0
CALT 5 2 4 3 7 4 25 3 1 4 2 5 3 18 1 1 0 0 1 0 3 0 0 0 0 0 1 1
CHSP 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
BRSP 0 0 0 0 0 1 1 0 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0
FOSP 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
SOSP 64 57 29 19 52 48 269 35 36 22 16 38 34 181 19 13 3 2 6 6 49 0 0 1 0 2 0 3
LISP 4 12 2 4 17 5 44 4 12 1 4 17 5 43 0 0 0 0 0 0 0 0 0 1 0 0 0 1
WCSP 4 9 4 8 15 26 66 4 9 4 7 14 25 63 0 0 0 0 0 0 0 0 0 0 1 1 1 3
GCSP 0 2 0 0 1 0 3 0 2 0 0 1 0 3 0 0 0 0 0 0 0 0 0 0 0 0 0 0
NOCA 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
BHGR 1 3 0 0 2 1 7 1 3 0 0 2 1 7 0 0 0 0 0 0 0 0 0 0 0 0 0 0
BLGR 1 0 0 3 3 1 8 1 0 0 2 2 1 6 0 0 0 0 1 0 1 0 0 0 0 0 0 0
LAZB 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
BHCO 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
HOOR 0 0 0 1 3 9 13 0 0 0 1 3 9 13 0 0 0 0 0 0 0 0 0 0 0 0 0 0
HOFI 57 49 25 78 23 15 247 57 48 24 76 22 15 242 0 0 1 0 0 0 1 0 1 0 2 1 0 4
LEGO 4 5 5 1 7 12 34 4 5 4 1 7 11 32 0 0 0 0 0 1 1 0 0 1 0 0 0 1
LAGO 0 0 0 0 0 2 2 0 0 0 0 0 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0
AMGO 0 0 0 1 3 0 4 0 0 0 1 2 0 3 0 0 0 0 1 0 1 0 0 0 0 0 0 0
Total captures 707 596 292 500 790 658 3543 528 459 230 386 618 481 2702 86 54 15 22 44 37 258 49 39 33 69 55 59 304
Total species 44 40 37 46 46 42 67 36 34 32 39 37 36 57 18 11 10 11 16 12 28 10 11 14 16 17 11 30
Table 3.    Total number of birds captured, banded, recaptured, and released unbanded at Naval Outlying Landing Field, Imperial Beach, California, 2014–20.

Of note, in 2014, we recaptured a Rufous Hummingbird (Selasphorus rufus) that originally had been banded in Tallahassee, Florida, in January 2014. This hummingbird travelled 3,100 km between its original banding station and our nets.

Sensitive Species

Nineteen sensitive species were detected at NOLF (12 captured and 7 observed only; appendix 1, tables 1.1, 1.2). We captured one State and Federally endangered species, Least Bell’s Vireo, one Federally threatened species, Coastal California Gnatcatcher (Polioptila californica californica), one State endangered species, Willow Flycatcher (Empidonax traillii), and two State species of concern, Yellow-breasted Chat (Icteria virens), and Yellow Warbler (Setophaga petechia; appendix 1, table 1.1; Shuford and Gardali, 2008; U.S. Fish and Wildlife Service, 2020; California Department of Fish and Wildlife, 2023). One additional State species of concern, Northern Harrier (Circus hudsonius), was observed at the MAPS banding station but was not captured (appendix 1, table 1.2; Shuford and Gardali, 2008). Peregrine Falcon (Falco peregrinus) and White-tailed Kite (Elanus leucurus), California State fully protected species, also were observed at the MAPS banding station (California Department of Fish and Wildlife, 2021). Seven Federal bird species of conservation concern—Calliope Hummingbird (Selasphorus calliope), Rufous Hummingbird, Allen’s Hummingbird (Selasphorus sasin), Nuttall’s Woodpecker (Dryobates nuttallii), Wrentit, California Thrasher (Toxostoma redivivum), and Lawrence’s Goldfinch (Spinus lawrencei)—were captured. Four additional Federal bird species of conservation concern—Willet (Tringa semipalmata), Western Gull (Larus occidentalis), California Gull (Larus californicus), and Bullock’s Oriole (Icterus bullockii)—were observed but not captured (appendix 1, tables 1.1, 1.2). Eleven of the sensitive species breed at NOLF (nine captured and two observed only).

Sixty-five Least Bell’s Vireo were captured and banded from 2014 to 2020. Four additional Least Bell’s Vireos captured prior to 2014 were recaptured between 2014 and 2020, for a total of 69 individual Least Bell’s Vireos captured from 2014 to 2020. Nine of the 69 vireos were recaptured in subsequent years (12 total recaptures between 2014 and 2020). Of the 69 individually banded vireos, 49 were given unique color band combinations, and 20 were banded with a single numbered metal band.

Capture Rates

The overall effort-corrected capture rate was 43±30 captures per MAPS period for all years combined (range 7–163 captures; table 4). Effort-corrected capture rates by year ranged from 240 to 745 captures with 2014 and 2018 being the highest capture years. Period 2 in 2014 had the highest effort-corrected capture rate of 163, a result of capturing a large number of birds (128 individuals) during a truncated survey day (0555–0910 PDT) when nets were closed early because of rain.

Table 4.    

Capture rate of year-unique individuals by Monitoring Avian Productivity and Survivorship (MAPS) period and year at Naval Outlying Landing Field, Imperial Beach, California, 2014–20.

[Year-unique captures were the total number of new captures, first-time recaptures, and unbanded birds captured in that year. Effort-corrected captures were year-unique captures corrected for effort following methods in DeSante and others (2015). Abbreviation: —, no data]

MAPS
period
Category Year
2014 2015 2017 2018 2019 2020
−3 Net-hours 60:00 60:00 65:00 61:40 55:19
Year-unique captures 34 108 18 31 82
Effort-corrected captures 33 108 17 30 102
−2 Net-hours 60:00 57:00 63:19 52:39 56:00 60:00
Year-unique captures 84 38 23 28 79 122
Effort-corrected captures 83 40 17 30 80 119
−1 Net-hours 60:00 60:00 68:19 55:19 60:00 53:00
Year-unique captures 39 100 10 53 93 59
Effort-corrected captures 39 98 7 54 92 63
1 Net-hours 60:00 59:19 63:19 53:19 56:39 60:00
Year-unique captures 128 57 19 74 66 66
Effort-corrected captures 123 57 15 77 67 64
2 Net-hours 33:19 58:30 65:00 53:19 57:19 60:00
Year-unique captures 148 47 34 52 42 59
Effort-corrected captures 163 47 26 57 42 58
3 Net-hours 60:00 48:00 66:40 60:00 60:00 58:19
Year-unique captures 79 41 11 40 36 53
Effort-corrected captures 78 61 10 37 34 53
4 Net-hours 60:00 60:00 66:40 60:00 60:00 60:00
Year-unique captures 20 15 12 24 53 35
Effort-corrected captures 20 14 11 22 51 34
5 Net-hours 60:00 60:00 68:19 60:00 60:00 57:19
Year-unique captures 5 21 24 14 35 31
Effort-corrected captures 15 20 20 13 33 31
6 Net-hours 60:00 60:00 61:40 53:19 59:19 60:00
Year-unique captures 15 15 20 26 64 36
Effort-corrected captures 15 15 16 27 63 36
7 Net-hours 60:00 60:00 61:40 56:00 54:39 58:39
Year-unique captures 22 26 19 28 45 21
Effort-corrected captures 22 26 16 28 46 21
8 Net-hours 60:00 60:00 65:00 52:40 60:00 58:30
Year-unique captures 9 17 32 48 36 31
Effort-corrected captures 9 17 22 62 36 31
9 Net-hours 60:00 58:39 63:19 52:30 54:30 57:29
Year-unique captures 26 9 36 32 48 30
Effort-corrected captures 20 9 40 38 56 32
10 Net-hours 60:00 58:09 63:19 40:00 53:00 51:19
Year-unique captures 44 58 20 27 38 34
Effort-corrected captures 43 61 23 45 42 35
Totals
by
year
Net-hours 753:19 759:39 841:39 710:49 746:49 694:39
Year-unique captures 663 552 278 477 717 577
Effort-corrected captures 664 572 240 521 745 578
Table 4.    Capture rate of year-unique individuals by Monitoring Avian Productivity and Survivorship (MAPS) period and year at Naval Outlying Landing Field, Imperial Beach, California, 2014–20.

Species Richness

The number of species captured ranged from 37 to 46 per year (tables 510). Daily species richness among captures averaged highest in early May, although in 3 years (2015, 2017, and 2020), species richness peaked in early to mid-April. Overall, species richness averaged 43±4 per year.

Table 5.    

Number of captures by Monitoring Avian Productivity and Survivorship (MAPS) period and date at Naval Outlying Landing Field, Imperial Beach, California, 2014.

[Captures were corrected for effort following methods in DeSante and others (2015). Species: See appendix 1 (tables 1.1, 1.2) for common and scientific names. Effort-corrected totals were rounded to integers; annual effort corrected total captures were calculated from actual (non-integer) values. Abbreviations: mm-dd-yy, month-day-year; —, no data]

Species MAPS period Total Effort-
corrected
total
−3 −2 −1 1 2 3 4 5 6 7 8 9 10
Date (mm-dd-yy)
04-03-14 04-17-14 04-24-14 05-08-14 05-15-14 05-22-14 06-05-14 06-12-14 06-26-14 07-03-14 07-10-14 07-24-14 07-31-14
CGDO 0 0 0 0 0 0 1 0 0 0 0 0 0 1 1
BCHU 0 0 1 0 2 0 1 0 0 1 0 2 1 8 8
ANHU 1 4 0 1 2 4 2 3 4 2 0 0 0 23 22
CAHU 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1
RUHU 0 2 0 0 0 0 0 0 0 0 0 0 0 2 2
ALHU 0 0 0 0 0 0 0 0 0 1 0 1 1 3 3
USHU 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1
COHA 1 0 1 0 0 0 0 0 0 0 0 0 0 2 2
DOWO 0 2 0 1 1 0 0 0 0 0 0 0 0 4 7
NUWO 0 1 0 0 0 0 0 0 2 0 0 0 0 3 3
WEWP 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1
WIFL 0 0 0 0 5 2 0 0 0 0 0 0 0 7 7
HAFL 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1
GRFL 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1
PSFL 0 8 4 4 20 16 1 0 0 1 0 0 0 54 54
ATFL 0 2 0 0 1 0 0 0 0 0 0 0 2 5 5
LBVI 0 0 1 1 1 0 1 0 0 1 1 1 0 7 6
WAVI 0 1 2 14 10 9 0 0 0 0 0 0 0 36 38
BTMJ 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1
BUSH 5 7 0 8 8 11 4 1 2 14 0 0 2 62 61
WREN 0 0 3 1 1 0 0 1 0 1 0 1 0 8 8
HOWR 3 3 2 1 0 0 0 1 0 0 0 0 1 11 11
BEWR 0 3 1 1 1 1 1 0 1 0 0 0 0 9 9
CATH 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1
SWTH 0 0 0 14 29 8 0 0 0 0 0 0 0 51 51
HETH 2 0 0 0 0 0 0 0 0 0 0 0 0 2 2
HOFI 0 0 1 0 0 1 1 0 2 0 2 19 31 57 50
LEGO 0 3 0 0 1 0 0 0 0 0 0 0 0 4 4
WCSP 0 3 1 0 0 0 0 0 0 0 0 0 0 4 4
SOSP 1 10 7 5 2 8 6 5 2 1 2 2 3 54 54
LISP 2 1 1 0 0 0 0 0 0 0 0 0 0 4 4
CALT 2 0 0 0 0 0 0 0 0 0 1 0 1 4 4
SPTO 0 0 2 0 0 1 1 1 0 0 0 0 0 5 5
YBCH 0 0 0 2 2 1 0 0 2 0 1 0 1 9 9
OCWA 10 14 4 10 5 2 0 1 0 0 0 0 1 47 46
NAWA 0 1 0 0 0 0 0 0 0 0 0 0 0 1 1
MGWA 0 2 0 2 6 0 0 0 0 0 0 0 0 10 10
COYE 7 7 1 4 3 5 0 2 0 0 2 0 0 31 31
YEWA 0 1 1 12 4 4 1 0 0 0 0 0 0 23 23
TOWA 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1
HEWA 0 0 0 2 0 0 0 0 0 0 0 0 0 2 1
WIWA 0 8 6 43 40 2 0 0 0 0 0 0 0 99 108
WETA 0 0 0 1 0 0 0 0 0 0 0 0 0 1 1
BHGR 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1
BLGR 0 0 0 0 0 1 0 0 0 0 0 0 0 1 1
Captures
per day
34 84 39 128 148 79 20 15 15 22 9 26 44 663 664
Total species1 10 21 17 20 23 19 11 8 7 8 6 6 10 44
Table 5.    Number of captures by Monitoring Avian Productivity and Survivorship (MAPS) period and date at Naval Outlying Landing Field, Imperial Beach, California, 2014.
1

Total species does not include one Unidentified Selasphorus Hummingbird (USHU) captured.

Table 6.    

Number of captures by Monitoring Avian Productivity and Survivorship (MAPS) period and date at Naval Outlying Landing Field, Imperial Beach, California, 2015.

[Captures were corrected for effort following methods in DeSante and others (2015). Species: See appendix 1 (tables 1.1, 1.2) for common and scientific names. Effort-corrected totals were rounded to integers; annual effort corrected total captures were calculated from actual (non-integer) values. Abbreviations: mm-dd-yy, month-day-year; —, no data]

Species MAPS period Total Effort-
corrected
total
−3 −2 −1 1 2 3 4 5 6 7 8 9 10
Date (mm-dd-yy)
04-02-15 04-16-15 04-30-15 05-07-15 05-14-15 05-21-15 06-04-15 06-11-15 06-25-15 07-09-15 07-16-15 07-23-15 07-30-15
CGDO 0 0 1 0 0 1 0 1 0 0 0 0 0 3 4
MODO 0 0 0 0 0 1 0 0 0 0 1 0 0 2 3
BCHU 0 1 0 0 0 0 1 2 0 0 0 0 0 4 4
ANHU 1 2 2 4 5 4 0 0 1 1 3 1 0 24 26
COHU 0 0 1 0 0 0 0 0 0 0 0 0 0 1 1
RUHU 2 0 0 0 0 0 0 0 0 0 0 0 0 2 2
ALHU 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1
DOWO 0 0 0 0 2 0 0 2 1 2 0 0 1 8 8
NUWO 0 0 0 0 0 0 0 0 0 0 1 0 0 1 1
WEWP 0 0 0 0 0 1 0 0 0 0 0 0 0 1 2
WIFL 0 0 0 0 0 0 0 1 0 0 0 0 0 1 1
HAFL 0 0 0 0 1 0 0 0 0 0 0 0 0 1 1
PSFL 0 2 5 5 10 3 0 0 0 0 0 0 0 25 26
ATFL 0 0 1 0 1 0 1 0 0 0 0 1 0 4 4
LBVI 1 0 0 1 0 0 1 0 2 0 0 1 1 7 7
HUVI 0 0 0 0 0 0 0 0 1 1 0 0 0 2 2
WAVI 0 0 11 5 0 1 0 0 0 0 0 0 0 17 18
BUSH 3 1 2 4 8 16 0 3 1 15 4 1 9 67 75
WREN 2 2 0 2 2 0 2 0 0 3 0 0 1 14 14
HOWR 3 1 0 3 0 0 1 1 1 1 0 0 0 11 11
BEWR 0 1 0 0 1 1 2 3 0 0 0 0 1 9 9
HETH 2 0 0 0 0 0 0 0 0 0 0 0 0 2 2
HOFI 2 0 0 0 0 0 1 0 0 1 5 2 38 49 52
LEGO 1 0 3 0 0 1 0 0 0 0 0 0 0 5 5
WCSP 9 0 0 0 0 0 0 0 0 0 0 0 0 9 9
GCSP 0 2 0 0 0 0 0 0 0 0 0 0 0 2 2
SOSP 8 3 7 10 7 3 3 5 2 0 1 0 0 49 50
LISP 12 0 0 0 0 0 0 0 0 0 0 0 0 12 12
CALT 1 0 0 0 0 0 0 0 0