Pacifica City Council
November 14, 2022

1 Shawn Smallwood, PhD
Christian Murdock, Deputy Planning Director
City of Pacifica
Planning Department
540 Crespi Drive
Pacifica, CA 94044 7 November 2022
[email protected]
Via Email
RE: 570 Crespi Drive Project
Dear Mr. Murdock,
I write to comment on potential biological impacts of a proposed mixed-use, largely residential development described in biological resources reports (Monk & Associates 2014, Wood Biological Consulting 2020) and an Initial Study / Mitigated Negative Declaration (“IS/MND”) prepared for the site at 540 and 570 Crespi Drive, Pacifica (City of Pacifica 2021). I understand the site is 1.68 acres, where natural vegetation and supporting soils would be replaced by three buildings 2 to 3 stories tall. To prepare my comments, I also consulted eBird -- an online database of bird observations managed by the Cornell Lab of Ornithology, and iNaturalist -- another online data base of animal and plant observations. I also visited the site of the proposed project.

My qualifications for preparing expert comments are the following. I hold a Ph.D. degree in Ecology from University of California at Davis, where I also worked as a postgraduate researcher in the Department of Agronomy and Range Sciences. My research has been on animal density and distribution, habitat selection, wildlife interactions with the anthrosphere, and conservation of rare and endangered species. I have authored many papers on these and other topics. I served as Chair of the Conservation Affairs Committee for The Wildlife Society – Western Section. I am a member of The Wildlife Society and Raptor Research Foundation, and I’ve lectured part-time at California State University, Sacramento. I was Associate Editor of wildlife biology’s premier scientific journal, The Journal of Wildlife Management, as well as of Biological Conservation, and I was on the Editorial Board of Environmental Management. I have performed wildlife surveys in California for thirty-seven years. My CV is attached.

SITE VISIT
I visited the site of the proposed project to perform a visual-scan survey on 27 July 2022, starting at 06:00 hours and lasting 3 hours 5 minutes. Conditions were initially foggy, but the fog lifted. Temperatures ranged 53° F to 57° F. The site is covered by an 2 extensive, dense willow thicket, marsh vegetation, annual grassland and Monterey cypress (Photos 1 ― 3).

The site supports fossorial mammals such as California voles and Botta’s pocket gophers (Photo 4), which are keystone species that provision many other species with forage and burrow refugia. In fact, during my brief survey, I detected 28 species of vertebrate wildlife on, over and next to the project site (Table 1), including 7 special-status species.

Special-status species composing 25% of the species I detect is unusually high, and is indicative of a project area that is naturally rich in wildlife species.

Photos 1 and 2. Views of project site, 27 July 2022.
3 Photo 3. Another view of project site, 27 July 2022.

Photo 4. Pocket
gopher burrows
covered the site’s
annual grassland,
and from which I
watched 2 redshouldered hawks
pluck several
gophers and voles,
which the hawks
consumed on the
site’s Monterey
cypress and on the
roof of The Crespi
Center, 27 July
2022.
4 Table 1. Species of wildlife I observed at the proposed project site on 27 July 2022.

Species Scientific name Status1 Notes
Mourning dove Zenaida macroura Flyover
Rock pigeon Columba livia Non-native Flyover
Band-tailed pigeon Patagioenus fasciata Flyover
Anna's hummingbird Calypte anna territory defence
California gull Larus californicus BCC, TWL Flyover
Western gull Larus occidentalis BCC Flyover
Double-crested cormorant Nannopterum auritum TWL flight Turkey vulture Cathartes aura BOP Foraging
Osprey Pandion haliaetus TWL, BOP Flyover
Red-shouldered hawk Buteo lineatus BOP Fledgling
Black phoebe Sayornis nigricans Foraging
European starling Sturnus vulgaris Non-native
Common raven Corvus corax Foraging
American crow Corvus brachyrhynchos
Bewick's wren Thryomanes bewickii Fledgling
Oak titmouse Baeolophus inornatus BCC
Chestnut-backed chickadee Poecile rufescens
Barn swallow Hirundo rustica Flyover
American goldfinch Spinus tristis Flyover
House finch Haemorphous mexicanus Territory vigilance
California towhee Melozone crissalis Territory vigilance Spotted towhee Pipilo maculatus
Song sparrow Melospiza melodia Territory vigilance
Lincoln's sparrow Melospiza lincolnii
Wilson's warbler Wilsonia pusilla Foraging
California vole Microtus californicus
Botta's pocket gopher Thomomys bottae
Black-tailed deer Odocoileus hemionus Foraging
1 Listed as BCC = U.S. Fish Bird Species of Conservation Concern, California Department of Fish and Wildlife Service’s TWL = Taxa to Watch List (Shuford and Gardali 2008), BOP = Birds of Prey (California Fish and Game Code 3503.5).
5 Photo 5. Red-shouldered hawk on the fence between the project applicant’s property and the City’s property, early morning, 27 July 2022.
6 Photos 6 and 7.

A very young male
red-shouldered
hawk seeks the
comfort of his
mother on The
Crespi Center,
adjacent to the
project site, 27 July
2022. These two
hawks foraged on
the project site all
morning. Their
center of activity
was a Monterey
cypress on the
north end of the
site.
7 Photo 8. Black
phoebe on the
project site, 27
July 2022.

Photos 9 and 10. Lincoln’s sparrow (left) and Anna’s hummingbird (right) on the project site, 27 July 2022.
8 Photo 11. Bewick’s
wren on the project
site, 27 July 2022.

This wren was
constantly pursued by
a fledgling.

Photo 12. Wilson’s warbler on
the project site, 27 July 2022.
9 Photos 13―15. California towhee (top), purple finch (left) and song sparrow (right) on the project site, 27 July 2022.
10 Photo 16. Black-tailed deer on the project site, 27 July 2022. 11 Photos 17 and 18. Part
of a flock of double-crested
cormorants (top) and an
osprey (bottom) returning
along the route it had
headed out to catch a fish,
selectively flying over the
project site, 27 July 2022.
12 CURRENT ENVIRONMENTAL SETTING
The first step in analysis of potential project impacts to biological resources is to accurately characterize the existing environmental setting, including the biological species that use the site, their relative abundances, how they use the site, key ecological relationships, and known and ongoing threats to those species with special status. A reasonably accurate characterization of the environmental setting can provide the basis for determining whether and to what degree the site holds habitat value to wildlife, as well as a baseline against which to analyze potential project impacts. For these reasons, characterization of the environmental setting, including the project’s site’s regional setting, is one of CEQA’s essential analytical steps (CEQA Guideline §15125). Methods to achieve this first step typically include (1) surveys of the site for biological resources, and (2) reviews of literature, databases and local experts for documented occurrences of special-status species. In the case of this project, these essential steps remain incomplete and conclusions stemming from them are pseudoscientific.

Biological Setting informed by Field Surveys
Ideally, the purpose of a field survey in support of environmental review is to identify which species use a project site, how they use it, and in what numbers. Identifying the presence of certain species – special-status species – is more important than the presence of others. Analysts need this information to identify the environmental baseline, and as a basis for opining on (predicting) potential project impacts to biological resources. In reality, a biological survey to inventory species is costly in time and effort, and its product uncertain. Some species are large or loud, and can be seen during diurnal surveys, whereas others are tiny and quiet and are detectable only by night, by trapping or by remote-sensing technology. Membership on an inventory can also carry different meanings based on how each species occurs at the site. Whereas some species are resident year-round, others can be seasonal or ephemeral in their occurrences at a site. Should a species be included on an inventory depends on the investigator’s standard of what counts as presence. Does a single 5-minute occurrence over a decade qualify a species as present? And if such a record was made, who can know whether many other brief occurrences truly occurred without having been documented?
The dilemma is that environmental review really needs species inventory, but biologists are imperfect observers of wildlife at any given site. Obtaining a true species inventory is unlikely, given the brief windows of time and budget that project applicants and their permitting authorities allow for biologists to surveil the site. The wildlife species that are detected by reconnaissance-level survey represent only a sampling of the species that truly use the site. This is because biologists vary in their skill at detecting wildlife species, and because species of wildlife vary in their detection probabilities during a typical reconnaissance-level survey, ranging from near 0% among rare or nocturnal species to 100% among species that consulting biologists often refer to as “common.” In truth, “common” species can number fewer than the “rare” or cryptic species that are more difficult to detect. Rare or cryptic species often require specialized survey 13 methods, begging the question of whether reconnaissance-level surveys can reveal any reliable information to readers of the environmental review.

Reconnaissance-level surveys occasionally reveal the presence of special-status species, sometimes due to the skill of the observer but often due to luck of survey timing. What these surveys cannot reveal is the absences of any species whose geographic ranges overlap the site and whose habitat associations at all resemble conditions of the site.

And it is habitat associations that consulting biologists often rely upon to determine likelihoods of occurrence of special-status species. Unfortunately, habitat associations often poorly comport with the habitat concept, which is that habitat is that part of the environment that is used by a species (Hall et al. 1997), and which is described by scientists through measurement (Smallwood 2002). Habitat associations defined by consulting biologists typically lack foundation in actual measurements of habitat use, and are therefore speculative and prone to error. One source of error is to map vegetation complexes as habitat types, to which consulting biologists assign species by association without concern for the unrealistically hard boundaries that divide the mapped habitat types. Another source of error is to pigeon-hole species into unrealistically narrow portions of the environment, which can then be said not to exist on the project site. A third source of error is to assign functions to habitat for the purpose of dividing habitat into unrealistic functional parts, such as between breeding habitat versus foraging habitat. Primacy is assigned to breeding habitat, which often can be said not to exist on the project site. In reality, all parts of an animal’s habitat are essential to breeding success, regardless of where breeding opportunities occur.1 Given the true cost of species inventory, the temptation to shortcut the analysis of occurrence likelihoods is understandable. In the spirit and intent of CEQA, a reasonably feasible species inventory should be the first objective of reconnaissance-level surveys.

But a reasonably feasible inventory is only a sampling of the inventory and not a true inventory. What, then, is the appropriate approach for informing a CEQA review with a reconnaissance-level biological survey? One is to commit to a survey effort that results in the detection of a sufficient number of species to accurately estimate the number of species yet to be detected. Another is to honestly report the uncertainties of the characterizations of the species inventory and of the likelihoods of occurrence of specialstatus species. The analyst can also assume species are present until suitable evidence is acquired in support of an absence determination. This last approach would be consistent with the precautionary principle of risk analysis directed toward rare and precious resources (National Research Council 1986).
1 Animals unable to find sufficient forage, refugia, or travel opportunities are just as unable to reproduce as those unable to find sufficient nest-site opportunities. Per the precautionary principle of risk analysis and consistent with the habitat concept, CEQA review should be based on the broadest of available habitat characterizations, which should be interpreted on the whole rather than contrived functional parts. Any detections of a species on or over a site, regardless of time of year, should be interpreted as that species’ use of habitat, any part of which is critical to breeding success.
14 How did the consulting biologists address the wildlife species inventory and special-status species occurrence likelihoods at the project site? Geoff Monk visited the project site on 17 September 2014 “to evaluate biological resources on the project site and to determine if proposed development of the project site would affect special-status species” (Monk & Associates 2014). Although his stated objectives are vague, it would seem that Mr. Monk intended to rely on habitat associations. No report is provided of what time Mr. Monk began his survey, how long his survey lasted, under what conditions he surveyed, nor which species of wildlife he saw. Monk & Associates (2014) fail to report the most fundamental methodological attributes and survey results needed to assess whether the survey met the stated objectives. Monk & Associates (2014) reported no data that could inform a species inventory or the likelihoods of occurrence of special-status species.

Chris Rogers of Wood Biological Consulting visited the project site on 19 July 2020 to observe “habitats plant and wildlife species [sic].” The objectives, though poorly worded, appear directed toward the preparation of a species inventory. However, Wood Biological Consulting (2020) repeats the gross reporting shortfalls of Monk & Associates (2014) by not reporting when the survey started, how long it lasted, under what conditions it was performed, and which species of wildlife were seen or heard. The survey and its reporting are uninformative of the wildlife species inventory and of the occurrence likelihoods of special-status species.

Neither Monk & Associates (2014) nor Wood Biological Consulting (2020) describe standards of field assessment intended for determining occurrence likelihoods, but instead imply a level of understanding of wildlife habitat that biologists lack. The most reliable indicator of habitat occupancy is detection of the species at the site, which is why species experts have painstakingly formulated protocol-level detection surveys for each of multiple special-status species. These detection surveys are formulated to give survey personnel high likelihoods of detecting the species if the species are indeed present, and otherwise to support absence determinations if the species are not detected despite full implementation of the detection surveys. Neither Monk & Associates (2014) nor Wood Biological Consulting (2020) made use of these detection surveys, and furthermore committed only brief reconnaissance-level survey efforts that were not up to the tasks of species inventory nor determining occurrence likelihoods. Monk & Associates (2014) and Wood Biological Consulting (2020) leave readers of the IS/MND ill-informed about the baseline conditions of the project site’s wildlife community.

Without appropriate surveys for special-status species, the appropriate determinations in most cases would be to assume presence, consistent with the precautionary principle in risk analysis directed towards rare and precious resources (National Research Council 1986). Monk & Associates (2014), Wood Biological Consulting (2020), and the IS/MND do not do this, however, and instead they most often assume absence. Determining absence without the support of detection surveys is inappropriate. 15 As discussed earlier, a reconnaissance-level survey can be useful for confirming presence of species that were detected, but it can also be useful for estimating the number of species that were not detected. One can model the pattern in species detections during a survey as a means to estimate the number of species that used the site but were undetected during the survey. To support such a modeling effort, the observer needs to record the times into the survey when each species was first detected.

The cumulative number of species’ detections increases with increasing survey time, but eventually with diminishing returns (Figure 1). In the case of my survey, the pattern in the data (Figure 1) predicts that had I spent more time on site, or had I help from additional biologists, I would have detected 47 species of vertebrate wildlife during the morning of 27 July 2022. The site supports plenty of species of wildlife, and there can be no doubt that it provides ample habitat value to wildlife – more than this model can predict, because the model is based on one survey of one morning. However, although this modeling approach is useful for more realistically representing the species richness of the site at the time of a survey, it cannot represent the species richness throughout the year or across multiple years because many species are seasonal or even multi-annual in their movement patterns and in their occupancy of habitat.

Figure 1. Actual (red
circles) and predicted (red
line) relationships between
the number of vertebrate
wildlife species detected and
the elapsed survey time
based on my visual-scan
survey on 27 July 2022 of
the 540 and 570 Crespi
Drive Project site. Note that
the relationship would differ
if the survey was based on
another method or during
another season.

By use of an analytical bridge, a modeling effort applied to data collected elsewhere can predict the number of vertebrate wildlife species likely making use of the site over the longer term. As part of my prior research, I completed a much larger survey effort across 167 km2 of annual grasslands of the Altamont Pass Wind Resource Area (APWRA), where from 2015 through 2019 I performed 721 1-hour visual-scan surveys, or 721 hours of surveys, at 46 stations in the APWRA. I used binoculars and otherwise 0 100 200 300 400 500 600
0 5
10 15
20 25
30 35
40 Y
Model r
2 = 0.99, loss = 18
Species count,
Minutes into survey
Cumulative number of wildlife species detected
16 the methods were the same as the methods I and other consulting biologists use for surveys at proposed project sites. At each of the 46 survey stations, I tallied new species detected with each sequential survey at that station, and then related the cumulative species detected to the hours (number of surveys, as each survey lasted 1 hour) used to accumulate my counts of species detected. I used combined quadratic and simplex methods of estimation in Statistica to estimate least-squares, best-fit nonlinear models of the number of cumulative species detected regressed on hours of survey (number of surveys) at the station: 𝑅̂ =
1 1⁄𝑎+𝑏×(𝐻𝑜𝑢𝑟𝑠)
𝑐
, where 𝑅̂ represented cumulative species
richness detected. The coefficients of determination, r 2, of the models ranged 0.88 to

1.00, with a mean of 0.97 (95% CI: 0.96, 0.98); or in other words, the models were excellent fits to the data.

I projected the predictions of each model to thousands of hours to find predicted asymptotes of wildlife species richness detectable by day in the APWRA. The mean model-predicted asymptote of species richness was 57 after 11,857 hours of visual-scan surveys among the 46 stations. I also averaged model predictions of species richness at each incremental increase of number of surveys, i.e., number of hours (Figure 2). On average I detected 12.72 species over the first 3 hours of surveys in the APWRA (3 hours to match the number of hours I surveyed at the project site), which composed 22.3% of the total predicted species I would detect with a much larger survey effort. Given the example illustrated in Figure 2, the 28 species I detected after my 3 hours of survey at the project site likely represented 22.3% of the species to be detected after many more visual-scan surveys over another year or longer. With many more repeat surveys through the year, I would likely detect 28

0.223 ⁄ = 126 species of vertebrate wildlife at
the 540 and 570 Crespi Drive project site.

Again, however, my prediction of 126 species of vertebrate wildlife is derived from visual-scan surveys during the daytime, and would not detect nocturnal mammals. The true number of species composing the wildlife community of the site must be larger. A reconnaissance-level survey should serve only as a starting point toward characterization of a site’s wildlife community, but it certainly cannot alone inform of the inventory of species that use the site. Without careful interpretation, the outcomes of the IS/MND’s supporting surveys should not represent baseline conditions, because there were truly many more species that used the site at the time of the surveys than whatever numbers of species were detected by Monk & Associates (2014) and Wood Biological Consulting (2020).

Additionally, the likelihood of detecting special-status species is typically lower than that of more common species. This difference can be explained by the fact that specialstatus species tend to be rarer and thus less detectable than common species. Specialstatus species also tend to be more cryptic, fossorial, or active during nocturnal periods when reconnaissance surveys are not performed. Another useful relationship from careful recording of species detections and subsequent comparative analysis is the probability of detection of listed species as a function of an increasing number of vertebrate wildlife species detected (Figure 3). (Note that listed species number fewer 17 than special-status species, which are inclusive of listed species. Also note that I include California Fully Protected species and federal Candidate species as “listed” species.) Figure 2. Mean (95% CI)
predicted wildlife species
richness, 𝑅̂, as a nonlinear
function of hour-long
survey increments across
46 visual-scan survey
stations across the
Altamont Pass Wind
Resource Area, Alameda
and Contra Costa
Counties, 2015‒2019.

Figure 3. Probability of
detecting ≥1 Candidate,
Threatened or Endangered
Species of wildlife listed under
California or federal Endangered
Species Acts, based on survey
outcomes logit-regressed on the
number of wildlife species Noriko
Smallwood (who has completed
many surveys for me) and I
detected during surveys at 199
project sites in California, 1999-
2022. The solid vertical line
represents the number of species
Noriko and I detected, and the
dashed vertical line represents
the number of species predicted
by my model in Figure 2 had I the
opportunity to repeatedly survey
the site over a year or longer.
0 20 40 60 80 100
0 10
20 30
40 50
Cumulative number of surveys (hours)
(95% CI)
0 20 40 60 80 100 120

0.0 0.2

0.4 0.6

0.8 1.0
Number of species detected
Probability of detecting Fully Protected,
Candidate, Threatened or Endangered Species
Hosmer Lemeshow =3.48, P = 0.90
95% CI
199 sites
18 As demonstrated in Figures 1 and 2, the number of species detected is largely a function of survey effort. Greater survey effort also increases the likelihood that listed species will be detected (which is the first tenet of detection surveys for special-status species).

Based on the outcomes of surveys earlier completed at 199 project sites, my survey effort at the 540 and 570 Crespi Drive project site carried an 35% chance of detecting a listed species, whereas the survey effort needed to achieve my Figure 2 model prediction of detecting 126 species carried a 100% chance of detecting a listed species. Listed species of vertebrate wildlife likely use the site, but conclusively documenting their use would take more survey effort to achieve a reasonable likelihood of detection. No reconnaissance-level survey is capable of detecting enough of the wildlife species that occur at a site to realistically characterize the site’s wildlife community, including the site’s special-status species. Based on these facts and reasonable inferences therefrom, I believe any environmental review of the proposed project should have been based on sufficient wildlife surveys to support wildlife absence determinations or a general assumption of species’ presence in the absence of supporting detection surveys.

Biological Setting informed by Data Base Review
The purpose of literature and database review, and of consulting with local experts, is to inform the reconnaissance-level survey, to augment it, and to help determine which protocol-level detection surveys should be implemented. Analysts need this information to identify which species are known to have occurred at or near the project site, and to identify which other special-status species could conceivably occur at the site due to geographic range overlap and site conditions. This step is important because the reconnaissance-level survey is not going to detect all of the species of wildlife that make use of the site. This step can identity those species yet to be detected at the site but which have been documented to occur nearby or whose available habitat associations are consistent with site conditions. Some special-status species can be ruled out of further analysis, but only if compelling evidence is available in support of such determinations (see below).

The IS/MND is inadequately informed by a literature and data base review. The IS/MND inappropriately uses the California Natural Diversity Data Base (CNDDB) to determine which species have potential to occur in the project area. By including only species whose documented occurrences within 5 miles of the project site can be found in the CNDDB, the IS/MND screens out many special-status species from further consideration in its characterization of the wildlife community as a component of the baseline biological setting. The CNDDB was not designed to support absence determinations or to screen out species from characterization of a site’s wildlife community. The IS/MND misuses the CNDDB.

The CNDDB relies entirely on volunteer reporting from biologists who were allowed access to whatever properties they report from. Many properties have never been surveyed by biologists. Many properties have been surveyed, but the survey outcomes never reported to the CNDDB. Many properties have been surveyed multiple times, but 19 not all survey outcomes have been reported to the CNDDB. Furthermore, the CNDDB is interested only in the findings of special-status species, which means that species more recently assigned special status will have been reported many fewer times to the CNDDB than were species assigned special status since the inception of the CNDDB. For example, because wrentit and Bullock’s oriole and multiple other species were not assigned special status until 2021, these species would have lacked records in the CNDDB when Monk & Associates prepared their assessment for the City. This lack of CNDDB records had nothing to do with true geographic distributions. And because negative findings are not reported to the CNDDB, the CNDDB cannot provide the basis for estimating occurrence likelihoods, either.

Negative findings from the CNDDB queries are inappropriate as a basis for narrowing a list of potentially occurring species. The limitations of the CNDDB are well-known, and summarized by the California Department of Fish and Wildlife in a warning presented on its CNDDB web site (https://wildlife.ca.gov/Data/CNDDB/Maps-and-Data):
“CNDDB staff work very hard to keep the database as current and up-to-date as possible given our capabilities and resources. However, we cannot and do not portray the CNDDB as an exhaustive and comprehensive inventory of all rare species statewide. Field verification for the presence or absence of sensitive species will always be an important obligation of our users.” And according to the CNDDB Data Use Guidelines, “The CNDDB is a positive sighting database. It does not predict where something may be found. We map occurrences only where we have documentation that the species was found at the site. There are many areas of the state where no surveys have been conducted and therefore there is nothing on the map. That does not mean that there are no special status species present.” The IS/MND’s use of CNDDB records to filter out species from its characterization of the baseline biological setting is therefore inconsistent with the CNDDB’s purpose. If the CNDDB was appropriate to the task to which the IS/MND applies it, then there would be no need for implementation of protocol-level detection surveys for special-status species. But this is not the case. For the above-stated reasons, the IS/MND’s list of special-status species assessed for occurrence likelihoods is misleading. Assuming absence of any special-status species based on absence of CNDDB records is inappropriate.

Had the IS/MND applied the CNDDB as CDFW intended, and had the IS/MND also made use of other occurrence data bases, then the list of potentially occurring specialstatus species of wildlife would have been much larger than 16. My review of eBird and iNaturalist revealed nearby occurrence records of 119 special-status species of wildlife, including 7 on the project site, 59 within 1.5 miles, another 12 within 1.5 and 4 miles, and 38 within 4 and 30 miles of the project site (Table 2). Two-thirds (78) of the 119 species in Table 2 have been recorded within only 4 miles from the project site, which means the site carries a lot of potential for supporting special-status species of wildlife. 20 Table 2. Occurrence likelihoods of special-status bird species at or near the proposed project site, according to eBird/iNaturalist records (https://eBird.org, https://www.inaturalist.org) and on-site survey findings. ‘Very close’ indicates within 1.5 miles of the site, “nearby” indicates within 1.5 and 4 miles, and “in region” indicates within 4 and 30 miles, and bold font denotes species I detected on 27 July 2022.

Common name Species name Status1 IS/MND
Data base
records,
Site visits
Monarch Danaus plexippus FC None Very close
San Bruno elfin butterfly Callophrys mossii bayensis FE None Very close Myrtle's silverspot butterfly Speyeria zerene myrtleae FE None In region California tiger salamander Ambystoma californiense FT, CT, WL In region California giant salamander Dicamptodon ensatus SSC In region Red-bellied newt Taricha rivularis SSC In region
Santa Cruz black salamander Aneides niger SSC In region Foothill yellow-legged frog Rana boylii CE, SSC No habitat In region California red-legged frog Rana draytonii FT, SSC None Very close Western pond turtle Emys marmorata SSC Nearby
San Francisco garter snake Thamnophis sirtalis tetrataenia FE, CE, CFP None Very close Brant Branta bernicla SSC2 Very close
Cackling goose (Aleutian) Branta hutchinsii leucopareia WL Very close Redhead Aythya americana SSC3 Very close
Harlequin duck Histrionicus histrionicus SSC Very close Barrow’s goldeneye Bucephala islandica SSC In region
Western grebe Aechmophorus occidentalis BCC Very close
Clark’s grebe Aechmophorus clarkii BCC Very close
Western yellow-billed cuckoo Coccyzus americanus occidentalis FT, CE, BCC In region Black swift Cypseloides niger SSC, BCC Nearby
Vaux’s swift Chaetura vauxi SSC2 Very close
Costa’s hummingbird Calypte costae BCC Very close
Rufous hummingbird Selasphorus rufus BCC Very close
Allen’s hummingbird Selasphorus sasin BCC Very close
21 Common name Species name Status
1 IS/MND
Data base
records,
Site visits
Mountain plover Charadrius montanus SSC, BCC In region
Snowy plover Charadrius nivosus BCC Very close
Western snowy plover Charadrius nivosus nivosus FT, SSC, BCC In region Whimbrel Numenius phaeopus BCC Very close
Long-billed curlew Numenius americanus BCC, WL Very close Marbled godwit Limosa fedoa BCC Very close
Red knot (Pacific) Calidris canutus BCC Very close
Short-billed dowitcher Limnodromus griseus BCC On site
Willet Tringa semipalmata BCC Very close
Marbled murrelet Brachyramphus marmoratus FT, CE Very close Laughing gull Leucophaeus atricilla WL In region
Heermann’s gull Larus heermanni BCC Very close
Western gull Larus occidentalis BCC On site
California gull Larus californicus WL, BCC On site
California least tern Sternula antillarum browni FE, CE, FP In region Caspian tern Hydroprogne caspia BCC Very close
Black tern Chlidonias niger SSC, BCC In region
Elegant tern Thalasseus elegans WL, BCC Very close
Black skimmer Rynchops niger SSC, BCC Nearby
Common loon Gavia immer SSC Very close
Brandt’s cormorant Urile penicillatus BCC Very close
Double-crested cormorant Phalacrocorax auritus WL Very close American white pelican Pelacanus erythrorhynchos SSC1 In region California brown pelican Pelecanus occidentalis californicus FP Very close Least bittern Ixobrychus exilis SSC, BCC In region
White-faced ibis Plegadis chihi WL Nearby
Turkey vulture Cathartes aura BOP On site
Osprey Pandion haliaetus WL, BOP On site
22 Common name Species name Status
1 IS/MND
Data base
records,
Site visits
White-tailed kite Elanus luecurus CFP, BOP Very close
Golden eagle Aquila chrysaetos BGEPA, BOP, BCC,
CFP
Very close
Northern harrier Circus cyaneus SSC3, BOP Very close
Sharp-shinned hawk Accipiter striatus WL, BOP Very close Cooper’s hawk Accipiter cooperii WL, BOP Very close
Northern goshawk Accipiter gentilis SSC In region
Bald eagle Haliaeetus leucocephalus BGEPA, BCC, CFP Very close Red-shouldered hawk Buteo lineatus BOP On site
Swainson’s hawk Buteo swainsoni CT, BCC, BOP Nearby
Red-tailed hawk Buteo jamaicensis BOP Very close
Rough-legged hawk Buteo regalis BOP In region
Ferruginous hawk Buteo regalis WL, BOP Nearby
Barn owl Tyto alba BOP Very close
Western screech-owl Megascops kennicotti BOP Nearby
Great horned owl Bubo virginianus BOP Very close
Burrowing owl Athene cunicularia BCC, SSC2, BOP Very close Long-eared owl Asio Otis SSC3, BCC, BOP Very close
Short-eared owl Asia flammeus SSC3, BOP Very close
Lewis’s woodpecker Melanerpes lewis BCC In region
Nuttall’s woodpecker Picoides nuttallii BCC Very close
American kestrel Falco sparverius BOP Very close
Merlin Falco columbarius WL, BOP None Very close
Peregrine falcon Falco peregrinus CFP, BOP, BCC Very close Prairie falcon Falco mexicanus BCC, WL, BOP In region
Olive-sided flycatcher Contopus cooperi BCC, SSC2 Very close Willow flycatcher Empidonax trailii CE, BCC Very close
Vermilion flycatcher Pyrocephalus rubinus SSC2 In region 23 Common name Species name Status1 IS/MND
Data base
records,
Site visits
Loggerhead shrike Lanius ludovicianus BCC, SSC2 Very close Yellow-billed magpie Pica nuttalli BCC In region
Oak titmouse Baeolophus inornatus BCC On site
California horned lark Eremophila alpestris actia WL Nearby Bank swallow Riparia riparia CT Very close
Purple martin Progne subis SSC2 Very close
Wrentit Chamaea fasciata BCC Very close
California thrasher Toxostoma redivivum BCC Very close
Cassin’s finch Haemorhous cassinii BCC In region
Lawrence’s goldfinch Spinus lawrencei BCC In region
Grasshopper sparrow Ammodramus savannarum SSC2 In region Black-chinned sparrow Spizella atrogularis BCC In region Brewer’s sparrow Spizella breweri BCC Very close
Bell’s sparrow Amphispiza b. belli WL, BCC Nearby
Oregon vesper sparrow Pooecetes gramineus affinis SSC2, BCC In region Alameda song sparrow Melospiza melodia pusillula SSC, BCC No habitat In region Large-billed savannah sparrow 2 Passerculus sandwichensis rostratus SSC2 In region Yellow-breasted chat Icteria virens SSC3 Very close
Yellow-headed blackbird Xanthocephalus xanthocephalus SSC3 In region Bullock’s oriole Icterus bullockii BCC Very close
Tricolored blackbird Agelaius tricolor CT, BCC, SSC Very close Lucy’s warbler Leiothlypis luciae SSC, BCC Very close
Virginia’s warbler Leiothlypis virginiae WL, BCC In region San Francisco common
yellowthroat
Geothlypis trichas sinuosa SSC3, BCC Unlikely In region Yellow warbler Dendroica petechia BCC, SSC2 Very close
Summer tanager Piranga rubra SSC1 Nearby
Pallid bat Antrozous pallidus SSC, WBWG H In region
24 Common name Species name Status1 IS/MND
Data base
records,
Site visits
Townsend’s big-eared bat Corynorhinus townsendii SSC, WBWG H No habitat In region Western red bat Lasiurus blossevillii SSC, WBWG H In region Hoary bat Lasiurus cinereus WBWG M Unlikely not
expected
In region
Western small-footed myotis Myotis cililabrum WBWG: M In range Miller’s myotis Myotis evotis WBWG: M In region
Fringed myotis Myotis thysanodes WBWG: H No habitat In range Long-legged myotis Myotis volans WBWG: H In range
Yuma myotis Myotis yumanensis WBWG: LM In region
San Francisco dusky-footed
woodrat
Neotoma fuscipes annectens SSC Very close
Ringtail Bassariscus astutus CFP Nearby
Salt-marsh harvest mouse Reithrodontomys raviventris FE, CE, FP In region American badger Taxidea taxus SSC No habitat Nearby
Mountain lion Puma concolor CCT Very close
1 Listed as FT & FE = federal threatened & endangered, FC = federal candidate for listing, BCC = U.S. Fish and Wildlife Service Bird of Conservation Concern, CT & CE = California threatened & endangered, CCE & CCT = Candidate California Endangered & Threatened, CFP = California Fully Protected (CDFG Code 3511), SSC = California species of special concern (not threatened with extinction, but rare, very restricted in range, declining throughout range, peripheral portion of species' range, associated with habitat that is declining in extent), SSC1, SSC2 and SSC3 = California Bird Species of Special Concern priorities 1, 2 and 3, respectively (Shuford and Gardali 2008), WL = Taxa to Watch List (Shuford and Gardali 2008), and BOP = Birds of Prey (California Fish and Game Code 3503.5), and WBWG = Western Bat Working Group with priority rankings, of low, moderate, and high.

25 The IS/MND addresses only 13 (11%) of the special-status species listed in my Table 2, supra.
2 The IS/MND determines all 13 of the species as unlikely or to have no likelihood of occurrence. Of these, 5 species have been recorded within 1.5 miles of the site, and another has been documented within 1.5 and 4 miles of the site. Six of the other 7 species have been documented within 30 miles of the site. The IS/MND’s occurrence likelihood determinations fail to comport with occurrence records, nor does the IS/MND’s explanations for their absence determinations comport with sound analytical practice. According to the IS/MND (p. 42), “Of the 16 special-status wildlife species that have been documented within the five-mile radius of the project site, only one was identified to have the potential to occur on the project site: a bird protected under the MBTA, the Saltmarsh common yellowthroat (SCY). The remaining species are considered to be unlikely or not possible to occur on the project site based on habitat features, such as the location of the site outside of the species’ historical range, the lack of suitable aquatic habitat, lack of suitable foraging or nesting habitat, and lack of a den or cave development area.”
Wood Biological Consulting (2020) describes winter habitat of Monarch as “tall trees along the coast. Prefers eucalyptus, Monterey pine and Monterey cypress.” Wood Biological Consulting (2020) determines this species has no likelihood of occurrence because “Migration and overwintering roosts are highly visible and well-documented.” Some migration and overwintering roosts are indeed highly visible, but much remains to be learned about overwintering and migration patterns of Monarchs (Xerces Society, www.xerces.org). The reason given by Wood Biological Consulting (2020) is insufficiently founded in evidence. Neither Monk & Associates (2014) nor Wood Biological Consulting (2020) visited the site when overwintering Monarchs would have been present, so they did not even look for the species during the appropriate season, if ever. The site includes trees of the species known to be used by Monarch, and it is near the coast and very close to documented over-wintering roost sites. The appropriate determination is high likelihood of occurrence of overwintering Monarchs at one time or another.

Wood Biological Consulting (2020) describes habitat of California red-legged frog as “lowlands and foothills in pools and streams, usually with emergent wetland vegetation.

Requires 11-20 weeks of permanent water for larval development.” Wood Biological Consulting (2020) determines this species has no likelihood of occurrence because “Wetland in study area dries in late spring or early summer...therefore not suitable breeding habitat. This urban infill site is isolated from nearest population, with no migration potential.” However, contrary to the Wood habitat description, permanent water is not required for California red-legged frog habitat. The species needs pools that remain inundated long enough for larvae to mature, but otherwise I have found California red-legged frogs at vegetated and unvegetated stock ponds, wells, streams, 2 The IS/MND addresses 16 special-status species, of which I included only 13 in my Table 2. I do not include steelhead, big free-tailed bat and North American porcupine. Steelhead would require a stream, which does not exist on the project site. Big free-tailed bat is known to occur in extreme southern California, but not in the project area. Porcupine lacks special status according to state and federal statutes and agency designations. 26 upland areas far from water pools, and even on road culverts. Last year I found California red-legged frogs on a road culvert on Higgins Way in Pacifica, only 0.9 miles from the project site. The project is only 0.29 miles from the outfall of San Pedro Creek, and only one to two roadways separate natural cover between San Pedro Creek and the project site. The project site includes fossorial mammal burrows that are useable as California red-legged frog refugia, and a large portion of the site is obviously inundated at times. I disagree with the IS/MND that there is no occurrence potential for California red-legged frog, and I agree with Dr. Peter Baye that California red-legged frogs are perfectly capable of moving between San Pedro Creek and the proposed project site, and that protocol-level detection surveys are needed to better inform the CEQA review (15 June 2022 memo from Peter R. Baye to Margaret Goodale, Pacifica).

Wood Biological Consulting (2020) describes habitat of merlin as “Seacoast, tidal estuaries, open woodlands, savannahs, edges of grasslands...clumps of trees are required for roosting in open country.” Wood Biological Consulting (2020) determines this species has no likelihood of occurrence because it “Does not nest in California.

Migrating birds would not be affected by proposed project.” I do not know where Wood Biological Consulting (2020) obtained their habitat description, but I have found merlin in various environmental settings, and would not rule out the project site. Since 2018, I found one merlin in scrub vegetation near a wetlands in Hayward, on a vacant lot in Hayward, on a nearly barren lot with ruderal vegetation and a tree-row border in San Bernardino, on a grassland/vernal pool complex in Placer County, on grassland that had been recently disked in Bakersfield (no trees nearby), on scrub next to a disked field in Oxnard, on a wheat field in Modesto, on alfalfa next to a strip of dense shrubs in Brawley, in an almond orchard in Visalia, on successional scrub in Thousand Oaks, on a disked field in Fresno (no trees nearby), and on wetlands and a wheat field in Davis.

Merlin are not as constrained as Wood Biological Consulting (2020) claims, nor is roosting opportunities in trees required. This said, the project site offers ample roosting opportunities for merlin. And the fact that merlin does not nest in California is irrelevant, because merlin that cannot find sufficient forage during migration will not breed successfully in spring. Merlin is one of multiple species that were designated with special status with full awareness that they do not breed here.

Wood Biological Consulting (2020) describes habitat of San Francisco common yellowthroat as “freshwater and saltwater marshes in the SF Bay Region. Requires dense continuous cover for foraging and tall grasses, tules or willows for nesting.” This habitat description resembles conditions on the project site. Nevertheless, Wood Biological Consulting (2020) determines this species is not expected to nest because the species was “Observed during 2017-2018. Willow scrub in study area could provide migration habitat, but is only a small, limited area of suitable habitat in an urban setting.” In this case, the species has been detected on the project site, and still Wood Biological Consulting (2020) contrives an argument for concluding the species does not nest there.

The IS/MND needs a stronger argument than this. It needs to present evidence that the site is too small, as alleged. It needs to present evidence that the urban setting would prevent nesting by San Francisco common yellowthroat, and it needs to explain why it is 27 that the species would be harmed only if nesting opportunities are destroyed by the project.

Wood Biological Consulting (2020) describes only roosting habitat of each bat species, thereby implying that foraging habitat is unimportant. The occurrence likelihood of each species is dismissed for lack of roosting habitat. However, bat roosts are more varied than described by Wood Biological Consulting (2020) (see Kunz and Lumsden 2003). Roosting opportunities are available to bats at the project site, but if the IS/MND is intent on concluding they are not, then a qualified bat biologist ought to have surveyed the site.

IMPACTS TO BIOLOGICAL RESOURCES
Determination of occurrence likelihoods of special-status species is not, in and of itself, an analysis of potential project impacts. But this is where the IS/MND left the analysis.

No mention was made of the habitat loss that would result from replacement of natural vegetation cover with buildings and driveway. None of the available literature on these impacts is cited. A proper impacts analysis should consider whether and how a proposed project would affect members of a species, larger demographic units of the species, or the whole of a species. In the following, I analyze several types of impacts likely to result from the project, none of which are analyzed in the IS/MND.

WILDLIFE MOVEMENT
According to the IS/MND, the project site does not occur within a wildlife movement corridor. However, the IS/MND’s conclusion is not based on any collection or analysis of data needed to characterize wildlife movement patterns. Regardless of whether the site is situated within a wildlife movement corridor, the IS/MND employs a standard of analysis that does not exist in CEQA. The CEQA standard is whether a project will “Interfere substantially with the movement of any native resident or migratory fish or wildlife species or with established native resident or migratory wildlife corridors…” The primary phrase of the standard goes to wildlife movement regardless of whether the movement is channeled by a corridor or a linkage. In addition, corridors are typically regarded in science as human-created landscape structures intended to reduce the effects of habitat fragmentation, and only infrequently as a channelization of wildlife movement caused by landscape structure (Smallwood 2015). Wildlife movement in a region is often diffuse rather than channeled (Runge et al. 2014, Taylor et al. 2011) unless anthropogenic changes have forced channeling or targeting of “island” patches of habitat (Smallwood 2015).

According to the IS/MND (p. 46), “The project site is surrounded by existing development and does not connect to any existing habitat areas, which eliminates the possibility that the site could act as a wildlife movement corridor.” However, this conclusion regarding wildlife corridor ignores that many species of wildlife have wings, and so can fly to or away from the project site without encountering the same barriers as non-volant wildlife. Wildlife movement must include stopover opportunities for birds 28 and bats (Taylor et al. 2011), and staging opportunities (Warnock 2010) during dispersal, migration or home range patrol. The project, with its buildings, would cut wildlife off from stopover and staging opportunities, and would lengthen the distances that wildlife must travel before finding alternate stopover opportunities. Therefore, it is my expert opinion based on what I saw of wildlife movement at the project site that the project would result in a potentially significant impact due to its interference with wildlife movement in the region.

HABITAT LOSS
The IS/MND does not address the loss of wildlife that would result from habitat loss caused by the project. No mention is made of the project site’s role as stopover and staging opportunities for migratory wildlife. An EIR should be prepared to more clearly explain the magnitude of the losses of habitat to wildlife and for how long those losses would persist.

Habitat loss not only results in the immediate numerical decline of wildlife, but also in permanent loss of productive capacity (Smallwood 2015). For example, two study sites in grassland/wetland/woodland complexes had total bird nesting densities of 32.8 and

35.8 nests per acre (Young 1948, Yahner 1982) for an average 34.3 nests per acre.

Assuming the nest density at the project site is equal to the average of the two study sites I cited, 34.3 nests/acre multiplied against 1.68 acres would predict a loss of 58 bird nests. The average number of fledglings per nest in Young’s (1948) study was 2.9.

Assuming Young’s (1948) study site typifies bird productivity, then the project’s removal of nest opportunities would prevent the production of 168 fledglings per year. After 100 years and assuming an average generation time of 5 years, the lost capacity of both breeders and annual fledgling production can be estimated from the following formula:
{(nests/year × chicks/nest × number of years) + ((2 adults/nest × nests/year) × (number of years ÷ years/generation))}. In the case of this project, and given my stated assumptions, this formula predicts the project would deny California 19,120 birds over the 100 years due solely to loss of terrestrial habitat. This predicted loss of 191 birds/year would be substantial, and therefore it is my expert opinion based on the facts and reasonable assumption that the project would result in a potentially significant impact from habitat loss, even with the proposed mitigations, that has not been addressed in the IS/MND.

BIRD-WINDOW COLLISIONS
The IS/MND neglects a large portion of habitat that is essential to many species. To understand this part of their habitat, one must consider the definition of habitat, which is a species’ use of the environment (Hall et al. 1997, Morrison et al. 1998, Smallwood 2002). Every species on Earth is morphologically adapted through thousands of generations of life and death to exist within an environmental medium. The gaseous atmosphere is a principal medium of life to volant animals such as birds (Davy et al. 2017, Diehl et al. 2017). The aerosphere is where birds and bats and other volant animals with wings migrate, disperse, forage, perform courtship and where some of 29 them mate. Birds are some of the many types of animals that evolved wings as a morphological adaptation to thrive by moving through the medium of the aerosphere.

The aerosphere is habitat. Indeed, an entire discipline of ecology has emerged to study this essential aspect of habitat – the discipline of aeroecology (Kunz et al. 2008).

Many special-status species of birds have been recorded at or near the aerosphere of the project site. My database review and site visits indicate there are 94 special-status species of birds with potential to use the site’s aerosphere (Table 2). Of these, 7 have been recorded over or adjacent to the project site, 53 within 1.5 miles of the site (‘Very close’), 9 within 1.5 and 4 miles (‘Nearby’), and another 25 within 4 to 30 miles (‘In region’). The birds reported within all these distance domains from the project site can quickly fly those distances, so they would all be within short flights of the proposed project’s windows.

Window collisions are often characterized as either the second or third largest source or human-caused bird mortality. The numbers behind these characterizations are often attributed to Klem’s (1990) and Dunn’s (1993) estimates of about 100 million to 1 billion bird fatalities in the USA, or more recently by Loss et al.’s (2014) estimate of 365-988 million bird fatalities in the USA or Calvert et al.’s (2013) and Machtans et al.’s (2013) estimates of 22.4 million and 25 million bird fatalities in Canada, respectively. The proposed project would impose windows in the airspace normally used by birds.

Glass-façades of buildings intercept and kill many birds, but these façades are differentially hazardous to birds based on spatial extent, contiguity, orientation, and other factors. At Washington State University, Johnson and Hudson (1976) found 266 bird fatalities of 41 species within 73 months of monitoring of a three-story glass walkway (no fatality adjustments attempted). Prior to marking the windows to warn birds of the collision hazard, the collision rate was 84.7 per year. At that rate, and not attempting to adjust the fatality estimate for the proportion of fatalities not found, 4,574 birds were likely killed over the 54 years since the start of their study, and that’s at a relatively small building façade. Accounting for the proportion of fatalities not found, the number of birds killed by this walkway over the last 54 years would have been about 14,270. And this is just for one 3-story, glass-sided walkway between two college campus buildings.

Klem’s (1990) estimate was based on speculation that 1 to 10 birds are killed per building per year, and this speculated range was extended to the number of buildings estimated by the US Census Bureau in 1986. Klem’s speculation was supported by fatality monitoring at only two houses, one in Illinois and the other in New York. Also, the basis of his fatality rate extension has changed greatly since 1986. Whereas his estimate served the need to alert the public of the possible magnitude of the birdwindow collision issue, it was highly uncertain at the time and undoubtedly outdated more than three decades hence. Indeed, by 2010 Klem (2010) characterized the upper end of his estimated range – 1 billion bird fatalities – as conservative. Furthermore, the estimate lumped species together as if all birds are the same and the loss of all birds to windows has the same level of impact.
30 By the time Loss et al. (2014) performed their effort to estimate annual USA birdwindow fatalities, many more fatality monitoring studies had been reported or were underway. Loss et al. (2014) incorporated many more fatality rates based on scientific monitoring, and they were more careful about which fatality rates to include. However, they included estimates based on fatality monitoring by homeowners, which in one study were found to detect only 38% of the available window fatalities (Bracey et al. 2016). Loss et al. (2014) excluded all fatality records lacking a dead bird in hand, such as injured birds or feather or blood spots on windows. Loss et al.’s (2014) fatality metric was the number of fatalities per building (where in this context a building can include a house, low-rise, or high-rise structure), but they assumed that this metric was based on window collisions. Because most of the bird-window collision studies were limited to migration seasons, Loss et al. (2014) developed an admittedly assumption-laden correction factor for making annual estimates. Also, only 2 of the studies included adjustments for carcass persistence and searcher detection error, and it was unclear how and to what degree fatality rates were adjusted for these factors. Although Loss et al. (2014) attempted to account for some biases as well as for large sources of uncertainty mostly resulting from an opportunistic rather than systematic sampling data source, their estimated annual fatality rate across the USA was highly uncertain and vulnerable to multiple biases, most of which would have resulted in fatality estimates biased low.

In my review of bird-window collision monitoring, I found that the search radius around homes and buildings was very narrow, usually 2 meters. Based on my experience with bird collisions in other contexts, I would expect that a large portion of bird-window collision victims would end up farther than 2 m from the windows, especially when the windows are higher up on tall buildings. In my experience, searcher detection rates tend to be low for small birds deposited on ground with vegetation cover or woodchips or other types of organic matter. Also, vertebrate scavengers entrain on anthropogenic sources of mortality and quickly remove many of the carcasses, thereby preventing the fatality searcher from detecting these fatalities. Adjusting fatality rates for these factors – search radius bias, searcher detection error, and carcass persistence rates – would greatly increase nationwide estimates of bird-window collision fatalities.

Buildings can intercept many nocturnal migrants as well as birds flying in daylight. As mentioned above, Johnson and Hudson (1976) found 266 bird fatalities of 41 species within 73 months of monitoring of a four-story glass walkway at Washington State University (no adjustments attempted for undetected fatalities). Somerlot (2003) found 21 bird fatalities among 13 buildings on a university campus within only 61 days.

Monitoring twice per week, Hager at al. (2008) found 215 bird fatalities of 48 species, or 55 birds/building/year, and at another site they found 142 bird fatalities of 37 species for 24 birds/building/year. Gelb and Delacretaz (2009) recorded 5,400 bird fatalities under buildings in New York City, based on a decade of monitoring only during migration periods, and some of the high-rises were associated with hundreds of fatalities each. Klem et al. (2009) monitored 73 building façades in New York City during 114 days of two migratory periods, tallying 549 collision victims, nearly 5 birds per day. Borden et al. (2010) surveyed a 1.8 km route 3 times per week during 12-month 31 period and found 271 bird fatalities of 50 species. Parkins et al. (2015) found 35 bird fatalities of 16 species within only 45 days of monitoring under 4 building façades. From 24 days of survey over a 48-day span, Porter and Huang (2015) found 47 fatalities under 8 buildings on a university campus. Sabo et al. (2016) found 27 bird fatalities over 61 days of searches under 31 windows. In San Francisco, Kahle et al. (2016) found 355 collision victims within 1,762 days under a 5-story building. Ocampo-Peñuela et al. (2016) searched the perimeters of 6 buildings on a university campus, finding 86 fatalities after 63 days of surveys. One of these buildings produced 61 of the 86 fatalities, and another building with collision-deterrent glass caused only 2 of the fatalities, thereby indicating a wide range in impacts likely influenced by various factors.

There is ample evidence available to support my prediction that the proposed project would result in many collision fatalities of birds.

Project Impact Prediction
By the time of these comments, I had reviewed and processed results of bird collision monitoring at 213 buildings and façades for which bird collisions per m2 of glass per year could be calculated and averaged (Johnson and Hudson 1976, O’Connell 2001, Somerlot 2003, Hager et al. 2008, Borden et al. 2010, Hager et al. 2013, Porter and Huang 2015, Parkins et al. 2015, Kahle et al. 2016, Ocampo-Peñuela et al. 2016, Sabo et al. 2016, Barton et al. 2017, Gomez-Moreno et al. 2018, Schneider et al. 2018, Loss et al. 2019, Brown et al. 2020, City of Portland Bureau of Environmental Services and Portland Audubon 2020, Riding et al. 2020). These study results averaged 0.073 bird deaths per m2 of glass per year (95% CI: 0.042-0.102). This average and its 95% confidence interval provide a robust basis for predicting fatality rates at a proposed new project.

The IS/MND depicts windows on the proposed new buildings. Judging from the IS/MND’s depiction, I estimate the new glass windows added by the project would total about 363 m2.

Applying the mean fatality rate (above) to my estimate of 363 m2 of glass on the façades of the project’s buildings predicts 27 bird deaths per year (95% CI: 16‒37). The 100-year toll from this average annual fatality rate would be 2,654 bird deaths (95% CI:
1,575‒3,732), which would continue until the structures are either renovated to reduce bird collisions or they come down. The vast majority of these deaths would be of birds protected under the Migratory Bird Treaty Act and under the recently revised California Fish and Game Code §3513, thus causing significant unmitigated impacts. Given the predicted level of bird-window collision mortality, and the lack of any proposed mitigation, it is my opinion that the proposed project would result in potentially significant adverse biological impacts.

HOUSE CATS
Considering that the IS/MND is silent on whether ownership of house cats would be allowed in the project, it is safe to assume that house cats would be introduced to the 32 project site by residents of the proposed residential units. However, the IS/MND does not address the impacts of house cats on wildlife. House cats serve as one of the largest sources of avian mortality in North America (Dauphiné and Cooper 2009, Blancher 2013, Loss et al. 2013, Loyd et al. 2017). Loss et al. (2013) estimated 139 million cats in the USA in 2013 (range 114 to 164 million), which killed an estimated 16.95 billion vertebrate wildlife annually (range 7.6 to 26.3 billion). In 2012 there were 0.44 house cats per human, and 122 vertebrate animals were killed per cat, free-ranging members of which killed disproportionately larger numbers of vertebrate wildlife. According to the IS/MND, the proposed project would add 53 new residents. The above rates applied to this number of new residents would add 23 cats, which could potentially kill 2,806 vertebrate wildlife per year. Over 100 years, the toll from the project’s house cats would be 280,600 wild animal deaths. This outcome easily qualifies as an unmitigated significant impact to wildlife that has not been analyzed in the IS/MND.

Based on this, it is my expert opinion that the project, even with the proposed mitigations, would result in a potentially significant biological impact to wildlife from free-ranging house cats resulting from the project.

CUMULATIVE IMPACTS
The IS/MND’s cumulative impacts analysis is flawed in several ways. The analysis is not directed toward biological resources, and in fact makes no mention of biological resources. It also only vaguely implies the City’s General Plan policies from 1980 would somehow prevent cumulative impacts, which the IS/MND further implies would not be realized due to project-specific mitigation for project-specific impacts. According to the IS/MND (p. 106), “Applicable policies from the General Plan would be implemented as part of the proposed project, as well as the project-specific mitigation measures included in this IS/MND, to ensure any potential impacts of the proposed project would be individually limited and not cumulatively considerable. As demonstrated in this IS/MND, all potential environmental impacts that could occur as a result of project implementation would be reduced to less-than-significant.” However, according to CEQA Guidelines §15064(h)(3), “a project’s incremental contribution to a cumulative impact can be found not cumulatively considerable if the project would comply with an approved plan or mitigation program that provides specific requirements that would avoid or substantially lessen the cumulative problem within the geographic area of the project.” And “When relying on a plan, regulation or program, the lead agency should explain how implementing the particular requirements in the plan, regulation or program ensure that the project’s incremental contribution to the cumulative effect is not cumulatively considerable.” The IS/MND’s analysis provides no specifics on how specific policies of the 1980 General Plan would mitigate project impacts to biological resources.

The cumulative effects analysis also relies on a false standard for determining whether a project’s impacts will be cumulatively considerable. The IS/MND implies that a given project impact is cumulatively considerable only when it has not been fully mitigated.

In essence, the IS/MND implies that cumulative impacts are really residual impacts left 33 over by inadequate mitigation of project impacts. This notion of residual impacts being the source of cumulative impacts is inconsistent with CEQA’s definition of cumulative effects. Individually mitigated projects do not negate the significance of cumulative impacts. If they did, then CEQA would not require a cumulative effects analysis. To summarize, the IS/MND provides no cumulative effects analysis as defined in two ways by CEQA.

MITIGATION MEASURES
IV-1. Construction Timing or Preconstruction Survey to Avoid Take of Nesting Birds
I concur that this measure should be implemented, but I must add that preconstruction surveys typically detect small fractions of the animals targeted. Nesting birds are highly adept at concealment to avoid predation. The notion that more than a few nests would be detected in willow scrub, cattails, and large Monterey Cypress would be fantasy.

Furthermore, preconstruction, take-avoidance surveys ultimately fail to prevent the impacts of habitat loss, resulting in the loss of productive capacity of the site.

Preconstruction surveys should not be performed without first having performed detection surveys. Preconstruction surveys are no substitute for detection surveys.

RECOMMENDED MEASURES
Protocol-level Detection Surveys: If the project goes forward, species detection surveys are needed to (1) support negative findings of species when appropriate, (2) inform preconstruction surveys to improve their efficacy, (3) estimate project impacts, and (4) inform compensatory mitigation and other forms of mitigation. Detection survey protocols and guidelines are available from resource agencies for most specialstatus species. Otherwise, professional standards can be learned from the scientific literature and species’ experts.

Detection Surveys for Bats: Multiple special-status species of bats likely occur on the project site. A qualified bat biologist should be tasked with completing protocollevel detection surveys for bats.

Construction Monitoring: If the project goes forward, one or more qualified biologists need to serve as construction monitors. They should have the authority to stop construction when construction poses a threat to wildlife, and they should have the authority to rectify situations that pose threats to wildlife. The events associated with construction monitoring, such as efforts to avoid impacts and findings of dead and injured wildlife, need to be summarized in a report that is subsequently made available to the public.

Habitat Loss: If the project goes forward, compensatory mitigation would be warranted for habitat loss. An equal area of open space should be protected in perpetuity as close to the project site as possible. The impacts of interference with 34 wildlife movement by the security fence should be minimized by reducing the length of fence and using a different type of fencing that increases opacity and minimizes the risk of entanglement. The fence should also include gaps to enable non-volant wildlife to pass through. Elimination of the fence from the project would be optimal.

Guidelines on Building Design to Minimize Bird-Window Collisions If the project goes forward, it should at a minimum adhere to available Bird-Safe Guidelines, such as those prepared by American Bird Conservancy and New York and San Francisco. The American Bird Conservancy (ABC) produced an excellent set of guidelines recommending actions to: (1) Minimize use of glass; (2) Placing glass behind some type of screening (grilles, shutters, exterior shades); (3) Using glass with inherent properties to reduce collisions, such as patterns, window films, decals or tape; and (4) Turning off lights during migration seasons (Sheppard and Phillips 2015). The City of San Francisco (San Francisco Planning Department 2011) also has a set of building design guidelines, based on the excellent guidelines produced by the New York City Audubon Society (Orff et al. 2007). The ABC document and both the New York and San Francisco documents provide excellent alerting of potential bird-collision hazards as well as many visual examples. The San Francisco Planning Department’s (2011) building design guidelines are more comprehensive than those of New York City, but they could have gone further. For example, the San Francisco guidelines probably should have also covered scientific monitoring of impacts as well as compensatory mitigation for impacts that could not be avoided, minimized or reduced.

New research results inform of the efficacy of marking windows. Whereas Klem (1990) found no deterrent effect from decals on windows, Johnson and Hudson (1976) reported a fatality reduction of about 69% after placing decals on windows. In an experiment of opportunity, Ocampo-Peñuela et al. (2016) found only 2 of 86 fatalities at one of 6 buildings – the only building with windows treated with a bird deterrent film. At the building with fritted glass, bird collisions were 82% lower than at other buildings with untreated windows. Kahle et al. (2016) added external window shades to some windowed façades to reduce fatalities 82% and 95%. Brown et al. (2020) reported an 84% lower collision probability among fritted glass windows and windows treated with ORNILUX R UV. City of Portland Bureau of Environmental Services and Portland Audubon (2020) reduced bird collision fatalities 94% by affixing marked Solyx window film to existing glass panels of Portland’s Columbia Building. Many external and internal glass markers have been tested experimentally, some showing no effect and some showing strong deterrent effects (Klem 1989, 1990, 2009, 2011; Klem and Saenger 2013; Rössler et al. 2015).

Monitoring and the use of compensatory mitigation should be incorporated at any new building project because the measures recommended in the available guidelines remain of uncertain efficacy, and even if these measures are effective, they will not reduce collision fatalities to zero. The only way to assess mitigation efficacy and to quantify post-construction fatalities is to monitor the project for fatalities, including at residential dwelling units.

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Gómez-Moreno, V. del C., J. R. Herrera-Herrera, and S. Niño-Maldonado. 2018. Bird collisions in windows of Centro Universitario Victoria, Tamaulipas, México. Huitzil, Revista Mexicana de Ornitología 19(2): 227-236. https://doi.org/10.28947/ hrmo.2018.19.2.347
Hager, S. B., H. Trudell, K. J. McKay, S. M. Crandall, and L. Mayer. 2008. Bird density and mortality at windows. Wilson Journal of Ornithology 120:550-564.

Hager S. B., B. J. Cosentino, K J. McKay, C. Monson, W. Zuurdeeg, and B. Blevins. 2013. Window area and development drive spatial variation in bird-window collisions in an urban landscape. PLoS ONE 8(1): e53371. doi:10.1371/journal.pone.0053371
Hall, L. S., P. R. Krausman, and M. L. Morrison. 1997. “The habitat concept and a plea for standard terminology.” Wildlife Society Bulletin 25:173-82. 37 Johnson, R. E., and G. E. Hudson. 1976. Bird mortality at a glassed-in walkway in Washington State. Western Birds 7:99-107.

Kahle, L. Q., M. E. Flannery, and J. P. Dumbacher. 2016. Bird-window collisions at a west-coast urban park museum: analyses of bird biology and window attributes from Golden Gate Park, San Francisco. PLoS ONE 11(1):e144600 DOI

10.1371/journal.pone.0144600.

Klem, D., Jr. 1989. Bird-window collisions. Wilson Bulletin 101:606-620.

Klem, D., Jr. 1990. Collisions between birds and windows: mortality and prevention.

Journal of Field Ornithology 61:120-128.

Klem, D., Jr. 2009. Preventing bird-window collisions. The Wilson Journal of Ornithology 121:314-321.

Klem, D., Jr. 2011. Evaluating the effectiveness of Acopian Birdsavers to deter or prevent bird-glass collisions. Unpublished report.

Klem, D., Jr. and P. G. Saenger. 2013. Evaluating the effectiveness of select visual signals to prevent bird-window collisions. The Wilson Journal of Ornithology 125:406–411.

Kunz, T. H., and L. F. Lumsden. 2003. Ecology of cavity and foliage roosting bats. Pages 3–89 in T. H. Kunz and M. B. Fenton, Eds., Bat ecology. The University of Chicago Press, Chicago.

Kunz, T. H., S. A. Gauthreaux Jr., N. I. Hristov, J. W. Horn, G. Jones, E. K. V. Kalko, R.

P. Larkin, G. F. McCracken, S. M. Swartz, R. B. Srygley, R. Dudley, J. K. Westbrook, and M. Wikelski. 2008. Aeroecology: probing and modelling the aerosphere.

Integrative and Comparative Biology 48:1-11. doi:10.1093/icb/icn037 Loss, S. R., T. Will, and P. P. Marra. 2013. The impact of free-ranging domestic cats on wildlife of the United States. Nature Communications 2380. DOI:

10.1038/ncomms2380
Loss, S. R., T. Will, S. S. Loss, and P. P. Marra. 2014. Bird–building collisions in the United States: Estimates of annual mortality and species vulnerability. The Condor: Ornithological Applications 116:8-23. DOI: 10.1650/CONDOR-13-090.1 Loss, S. R., S. Lao, J. W. Eckles, A. W. Anderson, R. B. Blair, and R. J. Turner. 2019.

Factors influencing bird-building collisions in the downtown area of a major North American city. PLoS ONE 14(11): e0224164. https://doi.org/10.1371/journal. pone.0224164
38 Loyd, K. A. T., S. M. Hernandez, and D. L. McRuer. 2017. The role of domestic cats in the admission of injured wildlife at rehabilitation and rescue centers. Wildlife Society Bulletin 41:55-61.

Machtans, C. S., C. H. R. Wedeles, and E. M. Bayne. 2013. A first estimate for Canada of the number of birds killed by colliding with building windows. Avian Conservation and Ecology 8(2):6. http://dx.doi.org/10.5751/ACE-00568-080206 Mendelsohn, M., W. Dexter, E. Olson, and S. Weber. 2009. Vasco Road wildlife movement study report. Report to Contra Costa County Public Works Department, Martinez, California.

Monk and Associates. 2014. Biological Constraints Analysis 570 Crespi Drive, City of Pacifica.

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Concepts and Applications. 2nd edition. University of Wisconsin Press Madison, WI.

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Ocampo-Peñuela, N., R. S. Winton, C. J. Wu, E. Zambello, T. W. Wittig and N. L. Cagle . 2016. Patterns of bird-window collisions inform mitigation on a university campus.

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Gelb. 2007. Bird-safe buildings guidelines. New York City Audubon, New York.

Parkins, K. L., S. B. Elbin, and E. Barnes. 2015. Light, glass, and bird–building collisions in an urban park. Northeastern Naturalist 22:84-94.

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Riding, C. S., T. J. O’Connell, and S. R. Loss. 2020. Building façade-level correlates of bird–window collisions in a small urban area. The Condor: Ornithological Applications 122:1–14.
39 Rössler, M., E. Nemeth, and A. Bruckner. 2015. Glass pane markings to prevent birdwindow collisions: less can be more. Biologia 70: 535—541. DOI: 10.1515/biolog2015-0057 Runge, C. A., T. G. Martin, H. P. Possingham, S. G. Willis, and R. A. Fuller. 2014.

Conserving mobile species. Frontiers in Ecology and Environment 12(7): 395–402, doi:10.1890/130237.

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Year-round monitoring reveals prevalence of fatal bird-window collisions at the Virginia Tech Corporate Research Center. PeerJ 6:e4562 https://doi.org/10.7717/ peerj.4562
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Smallwood, K. S. 2015. Habitat fragmentation and corridors. Pages 84-101 in M. L.

Morrison and H. A. Mathewson, Eds., Wildlife habitat conservation: concepts, challenges, and solutions. John Hopkins University Press, Baltimore, Maryland, USA.

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40 Warnock, N. 2010. Stopping vs. staging: the difference between a hop and a jump.

Journal of Avian Biology 41:621-626.

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Photos 23 and 24. Wilson’s warbler and black phoebe on the project site, 27 July 2022. 1 LAW OFFICES OF BRIAN GAFFNEY, A Professional Corporation 2370 Market Street, Suite 103-318
San Francisco, CA 94114
(650) 219 3187 Phone
[email protected]
Via Email
November 8, 2022
Mayor Bier
Pacifica City Council
Pacifica Acting Planning Director
[email protected]
[email protected]
RE: 570 Crespi Drive Project – Violations of CEQA and the Endangered Species Act Pacifica File No. 2016-004
Dear Mayor Bier, Councilmembers and Director Murdock,
This comment is submitted on behalf of Ms. Margaret Goodale and in support of the appeal she filed March 17, 2022 regarding the proposed 570 Crespi Drive Project. For the reasons provided below, Ms. Goodale urges the City of Pacifica to prepare an Environmental Impact Report (EIR) on this proposed project, and to correct the legal issues identified below.

There Is Substantial Evidence of Potentially Significant Adverse Project Impacts, and Thus An EIR Must Be Prepared Prior to Project Approval
There is substantial evidence before the City that the proposed 570 Crespi Drive project will have potentially significant adverse biological effects even with the proposed mitigation measures.

An EIR “shall” be prepared where, as here, “there is substantial evidence, in light of the whole record before the lead agency, that the project may have a significant effect on the environment.” (Pub. Res. Code § 21080(d), emphasis added. If there is substantial evidence supporting a “fair argument” that a project “may” have a significant environmental effect, the lead agency “shall” prepare an EIR. (CEQA Guideline15064(a)(1); Laurel Heights Improvement Assn. v. Regents of University of California (1993) 6 Cal.4th 112, 1135.) The fair argument standard provides a “low threshold” for requiring the preparation of an EIR, with a preference for resolving doubts in favor of an EIR. (No Oil, Inc. v. City of Los Angeles 2 (1974) 13 Cal.3d 68, 84; Architectural Heritage Assn. v. County of Monterey (2004) 122 Cal.App. 4th 1095, 1110.)
“Substantial evidence” is “enough relevant information and reasonable inferences from this information that a fair argument can be made to support a conclusion, even though other conclusions might also be reached.” (CEQA Guideline 15384(a).) Notably, where some experts conclude there may be a potentially adverse impact, and other experts disagree, an EIR must still be prepared. (CEQA Guidelines 15064, subd. (g); Pocket Protectors v. City of Sacramento (2004) 124 Cal. App. 4th 903, 928.)
Dr. Peter Baye
Coastal ecologist Dr. Peter Baye on June 15, 2022 provided the City with his expert assessment of outstanding wetland and endangered species impacts associated with the proposed 570 Crespi Drive project.1 Dr. Baye concludes that the failure to accurately assess potential occurrence of California red-legged frogs (CRLF) at the project site would be significant, unmitigated impacts, which the Initial Study / Mitigated Negative Declaration inadequately assessed under CEQA.

Dr. Baye’s expert conclusion is based on the following facts: (1) the Project site is “suitable habitat” for CRLF, (2) there is a large nearby breeding population of CRLF in wetlands and pools of the mouth of San Pedro Creek, less than 1500 feet radius away from the Project site, (3) the Project site is within the known upland nocturnal dispersal distances of California red-legged frogs, (4) the nearby Highway 1 roadside seasonal wetland swale/ditch, adjacent to the Pacifica State Beach parking lot, provides a nearly continuous dispersal and foraging (feeding) corridor with moisture and cover for red-legged frog nocturnal movement, (5) adult California red-legged frogs have the ability to make long-distance overland forays into and across upland areas at night, and (6) Highway 1 does not act as a dispersal barrier to adult red-legged frogs during low-traffic periods in early morning and late night hours reaching the Project site.

So too, Woods Biological Consulting concluded that, based on observations of the emergent wetlands in the study area in July 2020 and conversations with the biologist Patrick Kobernus who monitored the construction of the City’s Wet-Weather Equalization Basin, the project site provides “suitable breeding or dispersal habitat” for the California red-legged frog. 1 Dr. Baye’s Statement of Qualifications is attached.
3 Dr. Shawn Smallwood
Dr. Smallwood has concluded that the proposed project would result in potentially significant impacts due to (1) its interference with wildlife movement in the region, (2) habitat loss, even with the proposed mitigations, (3) bird-window collision mortality, and (4) free-ranging house cats related to the project.

Dr. Smallwood is a well-qualified expert, having received a Ph.D. in Ecology from the University of California at Davis in 1990, and authoring over 485 professional publications and over 370 reports. Dr. Smallwood based his comments on his first-hand, eye-witness observations from a personal visit to the site; review of the Initial Study; the Monk & Associates 2014 Report; the Wood Biological Consulting 2020 Report; and records maintained by the Cornell Lab of Ornithology and the online database iNaturalist.

The Initial Study and Any EIR Need to Properly Analyze Baseline Conditions of California Red-legged Frogs on Site and Nearby the Project
The fundamental goal of CEQA is to inform decision makers and the public of any potentially significant adverse effects of a project. To make such an assessment, the agency must delineate environmental conditions prevailing absent the project, defining a “baseline” against which predicted effects can be described and quantified. (Neighbors for Smart Rail v. Exposition Metro Line Constr. Auth. (2013) 57 Cal. 4th 439, 447.) This baseline for CEQA analysis must be the “existing physical conditions in the affected area.” The California Supreme Court has made clear that this requirement applies to an initial study or negative declaration. (Communities for a Better Env't v. S. Coast Air Quality Mgmt. Dist. (2010) 48 Cal. 4th 310, 321.) The Initial Study for this project and the reports on which it is based, as Dr. Baye points out, fail to discuss either (1) the large nearby population of CRLF in wetlands and pools of the mouth of San Pedro Creek less than 1500 feet radius away from the Project site or (2) the dispersal and foraging corridor for red-legged frog nocturnal movement. In addition, the City has failed to conduct or require an assessment of CRLF population and individual presence at the Project site.

In addition, the Initial Study fails to analyze the existing baseline of the project site in regards to nesting birds, wetlands and heritage trees. “Further evaluation is required in order to identify if any other individual trees are protected under the City’s Preservation of Heritage Trees ordinance.” Initial Study, p 46.
4 So too, as Dr. Smallwood comments, the reports by Monk & Associates (2014) and Wood Biological Consulting (2020) leave readers of the Initial Study ill-informed about the baseline conditions of the project site’s wildlife community. The Initial Study is inadequately informed by a literature and data base review. The Initial Study inappropriately uses the California Natural Diversity Data Base (CNDDB) to determine which species have potential to occur in the project area. By including only species whose documented occurrences within 5 miles of the project site can be found in the CNDDB, the Initial Study screens out many special-status species from further consideration in its characterization of the wildlife community as a component of the baseline biological setting. The CNDDB was not designed to support absence determinations or to screen out species from characterization of a site’s wildlife community. The Initial Study misuses the CNDDB.

The City’s certification of a Mitigated Negative Declaration or an EIR based on this inadequate Initial Study, without a proper baseline analysis, would violate CEQA. This is particularly troubling given that the error occurs in relation to a federally threatened species.

The Initial Study and Any EIR Must Not Defer Analysis of Project Biological Resource Impacts Until After Project Approval.

The purpose of CEQA is to inform the public and public officials of the environmental consequences of decisions before they are made. (Citizens of Goleta Valley v. Board of Supervisors of Santa Barbara County (1990) 52 Cal.3d 553, 564.) Public agencies must comply with CEQA before approving a project. (CEQA Guideline 15004(a).) This Initial Study improperly defers the required analysis of Project impacts to nesting birds, wetlands and heritage trees until after project approval. Mitigation Measure IV-1 will defer analysis of nesting birds to a post-approval “preconstruction nesting bird survey.” Mitigation Measure IV-3 will defer analysis of the impact of the project on waters of the U.S until after project approval.” Mitigation Measure IV-5 will defer analysis of impacts to heritage trees until after project approval.

The City’s certification of a Mitigated Negative Declaration or an EIR based on this inadequate Initial Study, which defers the analysis of Project impacts to nesting birds, wetlands and heritage trees until after project approval, would violate CEQA. 5 The Initial Study and Any EIR Must Analyze Cumulative Biological Impacts There is no analysis of cumulative biological impacts in the Initial Study.

Further, the cumulative impact discussion at Initial Study p. 105 does not explain how specific policies of the 1980 General Plan would mitigate project impacts to biological resources.

The City’s certification of a Mitigated Negative Declaration or an EIR based on this inadequate Initial Study, which omits a robust analysis of cumulative biological impacts, would violate CEQA.

Take of Endangered Species is a Violation of the Federal Endangered Species Act.

California red-legged frog, a federally listed threatened species, may be present at the site. Any take of a single individual of such species is prohibited under federal law. (16 U.S.C. § 1538.) “Take” includes harass or harm. "Harm" includes any act which actually kills or injures fish or wildlife, including significant habitat modification or degradation that significantly impairs essential behavioral patterns. “Harass” includes an intentional or negligent act which creates the likelihood of injury to wildlife by annoying it to such an extent as to significantly disrupt normal behavioral patterns which include, but are not limited to, breeding, feeding, or sheltering.

The courts have held that State and local agencies may be held liable for licensing an activity that is likely to result in a violation of the federal Endangered Species Act. (See Strahan v. Coxe, 127 F.3d 155, 162-163 (1st Cir. 1997); see also Strahan v. Sec'y, Massachusetts Exec.

Off. of Energy & Env't Affs., 458 F. Supp. 3d 76, 89–90 (D. Mass. 2020).) Conclusion
The City has before it expert opinions supported by fact that the 570 Crespi Drive project will have potentially significant adverse biological impacts. (CEQA Guideline 15384(b).) A negative declaration is only permitted if there is no substantial evidence that the project or any of its aspects may cause a significant effect on the environment.

By law, the City is required to have an EIR prepared for this proposed project in order that the public and City decision makers are fully informed of project impacts, mitigations and alternatives prior to project approval. Any such EIR must not repeat the CEQA errors noted above.