Avian Diversity and Functional Insectivory on North-Central Florida Farmlands
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Avian Diversity and Functional Insectivory on North-Central Florida Farmlands GREGORY A. JONES,∗ KATHRYN E. SIEVING, AND SUSAN K. JACOBSON Department of Wildlife Ecology and Conservation 110 Newins-Ziegler Hall, University of Florida, Gainesville, FL 32611-0430, U.S.A. Abstract: We studied the potential for native birds to control insect pests on farms. We assessed habitat factors correlated with diversity, distribution, and insect-foraging activity of native birds on farms in north-central Florida and then characterized common bird species that consumed insect biomass in crops as “functional insectivores” (birds most likely to contribute to pest control). Analyses of point-count survey data and foraging observations collected over 2 years on paired organic and conventional farm sites indicated that (1) farms supported most (82–96%) land birds known to breed in the region; (2) bird species richness and abundance varied significantly with matrix habitat and field border type (but not with year or farm management type); (3) the highest bird abundances were associated with mixed crop plantings, field borders, and adjacent matrix composed of forest and hedge; and (4) abundances of 10 species identified as functional insectivores were primarily influenced by crop type (mixed crops attracted significantly more insect foragers into fields than monocrops). We documented birds eating pest insects in crops and did not observe substantive crop damage by birds during growing-season observations. We advocate use of the term functional insectivore to emphasize the potential positive role of avian insectivory on farms during the growing season. Key Words: agroecosystems, avian biodiversity, avian conservation, birds and farmlands, functional insectivores Diversidad Aviar e Insectivorı́a Funcional en Tierras Agrı́colas del Norte-Centro de Florida Resumen: Estudiamos el potencial de aves nativas para controlar plagas de insectos en tierras agrı́colas. Evaluamos factores del hábitat correlacionados con la diversidad, distribución y actividad de forrajeo de insectos de aves nativas en tierras agrı́colas del norte-centro de Florida y posteriormente caracterizamos como “insectı́voros funcionales” (aves que más probablemente contribuyen al control de plagas) a las especies comunes de aves que consumı́an biomasa de insectos en los cultivos. El análisis de datos de conteos por puntos y de observaciones de forrajeo recolectados a lo largo de 2 años en ranchos orgánicos y convencionales pareados indicó que (1) los ranchos sostenı́an a la mayorı́a (82%-96%) de las especies de aves terrestres residentes conocidas en la región; (2) la riqueza y abundancia de especies de aves variaron significativamente con el tipo de matriz de hábitat y borde (pero no con el año o tipo de manejo del rancho); (3) las mayores abundancias de aves se asociaron con cultivos mixtos, bordes, y matriz adyacente compuesta de bosque y setos; y (4) la abundancia de las 10 especies consideradas insectı́voros funcionales fue influida por el tipo de cultivo principalmente (los cultivos mixtos significativamente atrajeron a mas insectı́voros que los monocultivos). Documentamos a aves alimentándose de insectos plaga en los cultivos y no observamos daño sustancial de las aves en los cultivos. Recomendamos el uso del término insectı́voro funcional para enfatizar el papel positivo potencial de la insectivorı́a de aves en tierras agrı́colas durante el perı́odo de crecimiento. Palabras Clave: agroecosistemas, aves y tierras agrı́colas, biodiversidad aviar, conservación aviar, insectı́voros funcionales ∗ emailgreg.a.jones@sfcc.edu Paper submitted November 11, 2003; revised manuscript accepted November 2, 2004. 1234 Conservation Biology 1234–1245 C 2005 Society for Conservation Biology DOI: 10.1111/j.1523-1739.2005.00211.x
Jones et al. Functional Insectivory on Farms 1235
Introduction of avian communities and insect foraging activity on farms
in north-central Florida and identified farm characteristics
Wildlife conservation is a natural partner in cultivation that could be managed to influence richness and abun-
of ecologically sensitive agriculture to foster biodiversity dance of native birds that actively forage for insects in
protection on food-production lands (Vandermeer & Per- cropped vegetation. This study represents a preliminary
fecto 1997; McNeely & Scherr 2003). But this partnership step toward assessment of the economic efficacy of in-
is currently underdeveloped because conventional farm- tegrating native insectivorous birds into modern agricul-
ing operations have caused habitat destruction and devas- tural systems.
tation of native biodiversity worldwide. This generates un-
derstandable pessimism among conservationists (Best et
al. 1995; McLaughlin & Mineau 1995; Pain & Pienkowski Methods
1997; Vitousek et al. 1997; Stattersfield et al. 1998; Peter-
john 2003; Solh et al. 2003). Encouragingly, sustainable Study Design
agriculture is on the rise and, by definition, sustainable
practices are intended to maintain ecological integrity. Certified organic farming is defined as crop production
In practice, protection of native however biodiversity is without use of conventional pesticides, synthetic fertiliz-
rarely included in existing sustainable agriculture pro- ers, sewage sludge, or bioengineered food plants (USDA
grams (Swaminathan 1991; Kirchmann & Thorvaldsson 2002). Because bird and insect biomass can be higher
2000; Pala et al. 2004), and research to fully integrate on organic than conventional farms (Christensen et al.
biodiversity conservation with agricultural production re- 1996; Feber et al. 1997; O’Leske et al. 1997; Chamberlain
mains uncommon (Hess 1991; McNeely & Scherr 2003). et al. 1999), we paired sampling sites on both organic
This is because the concept of ecoagriculture, although and conventional farms and included farm management
compelling to ecologists, has not engaged agricultural ed- type as an a priori predictor variable. We estimated avian
ucators and producers in adoption of biodiversity-friendly species richness and relative abundance at field edges and
practices (Pimentel et al. 1992; Hobbs & Norton 1996; Ty- observed individual birds foraging in cropped fields to
birk et al. 2004). One explanation for this lack of engage- determine which species were eating insects during the
ment is the fact that few studies have demonstrated how spring growing seasons. We designated the most abun-
producer constraints (labor and economic efficiency) can dant insect-foraging species as functional insectivores
be accommodated in the context of biodiversity-friendly (i.e., species most likely to consume significant herbiv-
farming (Moser & Barrett 2003; Pandey et al. 2003; Boern- orous insect biomass during the growing season). We se-
gen & Bullock 2004). lected three additional predictors of bird diversity (rich-
Among the economic constraints facing farmers is the ness and abundance) in cropped fields and at field edges
high cost of labor and chemical use associated with and of insect foraging activity in cropped fields: crop di-
arthropod pest control in crops (Abate et al. 2000). A vari- versity (mixed versus mono crops; e.g., Elliott et al. 1998);
ety of evidence indicates that insectivorous birds may play field border vegetation type (e.g., Deschenes et al. 2003);
important functional roles in determining arthropod pop- and type of habitat matrix adjacent to each sampled field
ulation dynamics. Avian insectivores eat commercially im- (Dauber et al. 2003).
portant pest insects in forest and coffee agroecosystems
(Dahlston et al. 1990; Greenberg et al. 2000) and the- Site Selection
oretically they could stabilize outbreaks of pest insects
In April 2000, we established 30 survey points on cer-
(Beddington et al. 1978; Holling 1988). In forest ecosys-
tified organic farms and a paired reference site for each
tems, birds appear to exert constant damping controls on
of these points on a nearby conventional farm (n = 60
insect herbivores, with positive effects on plant growth
total points across 20 farm properties) and matched each
(Marquis and Whelan 1994; Dial and Roughgarden 1995;
organic point’s crop diversity, field border type, and ma-
Van Bael et al. 2003). If native insect-eating birds can prey
trix vegetation type, where possible (Rogers & Freemark
on pests of row crops at levels that increase economic ef-
1991; Christensen et al. 1996). One organic farm lay fal-
ficiency (less pesticide, increased yield), then integrated
low in 2001; therefore, we used five fewer points in that
approaches to ecological agriculture could more realisti-
year. The 20 farm properties were relatively small opera-
cally be encouraged (McNeely & Scherr 2003). We tested
tions, ranging in size from 4 to 104 ha and were in Alachua,
the hypothesis that insectivorous birds can participate in
Gilchrist, Marion, and Jefferson counties of north-central
control of agricultural pests in row crops. If valid, this
Florida.
hypothesis predicts (among other things) that insectiv-
orous birds should be abundant on farms and at field
Bird Species Richness and Abundance
edges, and actively foraging for insects in cropped veg-
etation during critical growing times. To assess these pre- We used point-count methods to estimate bird species
dictions we conducted a comparative observational study richness and abundance in cropped and uncropped
Conservation Biology
Volume 19, No. 4, August 20051236 Functional Insectivory on Farms Jones et al.
habitats (Bibby et al. 1992; Freemark & Rogers 1995). areas on each farm unit and recorded species not noted
Sampling points with a 50-m fixed radius were situated on during the formal point counts.
the border between cropped fields and uncropped areas.
Survey points were at least 200 m apart if they occurred
Farm and Field Characteristics
on any single farm management unit with the exception
of four points; at two different fields, survey points on We classified each farm (and all points occurring on it)
opposite sides of the fields were slightly < 200 m apart. as organic or conventional management (Table 1). In sur-
We sampled all points a minimum of four times between vey plots, we classified field borders (vegetation lining the
25 April and 30 June in both years. The order of visita- edge of fields) and crop diversity (one crop species versus
tion to sites in the pair (organic versus conventional) and two or more intercrops). Monocropped fields included
the order of points visited on each farm management unit corn, beans, watermelon, and yellow or zucchini squash.
were reversed each visit. We surveyed between dawn and Mixed-crop fields included varieties of greens such as kale
1100 hours on fair-weather days. All birds seen or heard (Brassica oleracea L.), tomatoes (Lycopersicon esculen-
within the 50-m radius during a 10-minute period were tum Mill.), beans (Phaseolus spp.), or okra (Abelmoschus
recorded. We mapped locations of individuals counted esculentus L.) in addition to corn (Zea mays L.), melons
onto two 180◦ semicircles (in the cropped field and the (Cucumis melo L.), squash (Cucurbita spp.), or strawber-
uncropped area) to avoid double counting of individual ries (Fragaria ananassa Duch.). Dominant matrix type
birds. was defined by the ecosystem adjacent to field edges in a
Observers began counting birds 2–3 minutes after ar- 200-m radius semicircle (6.3 ha) around the survey point
rival. Birds observed outside the count circle or flying that occupied more than 50% of the semicircle. Coverage
overhead were noted but excluded from point-count data of vegetation types was quantified based on 1999 digital
with one exception. We considered aerial-feeding birds ortho quarter-quad aerial photos (Florida Department of
flying low (< 10 m) over field vegetation to be “using” Environmental Protection), with ESRI ArcView software
the fields for foraging on insects (Boutin et al. 1999). Birds and the Xtools extension package (Oregon Department
flushed in count circles during approach were counted if of Forestry 2001). The dominant community types ob-
they were not recorded during the count period. Because served in the matrix were verified via ground inspection,
we sampled during the breeding season only, we assumed and they occupied from 62% to 90% of sampled area (Ta-
singing males observed repeatedly during counts were ble 1).
paired breeders and recorded them as two individuals One potential bias arises in interpreting data from small
(Bibby et al. 1992). To describe species richness on en- fields with a variety of surrounding habitat types. For
tire farms, we also conducted 30-minute search surveys example, if a survey point is on an edge with adjacent
(Freemark & Rogers 1995) in cropped and noncropped matrix of crop or pine and a nearby edge is hardwood
Table 1. Predictor and response variables used in RM-MANOVA analyses of avian community structure based on point-count data.
Variable Categorya Sampling scale Definition
Predictor
year 2000 time (repeated measure)
2001
farm type conventional (31) whole farm conventional management
organic (30) whole farm certified organic management
crop diversity mono (29) 50-m plot 1 crop species in field
mixed (32) 50-m plot 2 or more crop species in field
border type hardwood (22) 50-m plot broad-leaved trees > 5 m tall
hedge (16) 50-m plot linear strip of woody vegetation
open (9) 50-m plot grazed pasture, crops, lake
pine plantation (4) 50-m plot planted pines > 5m tall
suburb (7) 50-m plot residential development
matrix typeb hardwood (25) 200-m semicircle broad-leaved trees > 5 m tall
open (24) 200-m semicircle grazed pasture, crops, lake
pine plantation (5) 200-m semicircle planted pines > 5m tall
suburb (7) 200-m semicircle residential development
Response
abundance (AP, AC, AB)c 50-m plot mean number of birds/ha
species richness (SP, SC, SB)c 50-m plot total number of species counted
a Numbers in parentheses are point-count circles within each factor level.
b Dominant matrix type is habitat type occupying at least 50% of the 200-m semicircle.
c Three measures each for abundance (A) and species (S) richness: whole point (P)-count circle, crop (C) half, and field border (B) half of circle.
Conservation Biology
Volume 19, No. 4, August 2005Jones et al. Functional Insectivory on Farms 1237
forest, birds attracted to the hardwood might travel radius plot during point counts, and during search sur-
through the point-count circle and be counted as crop- veys (Freemark & Rogers 1995).
or pine-associated species. We have no estimate of how
frequently this may have occurred but assume our point-
AVIAN COMMUNITY STRUCTURE AT FIELD EDGES
count circles were small enough that birds entering them
were associating with the nearest border (the one inside To determine how cross-scale habitat characteristics in-
the count circle). Another potential bias derives from fluenced bird species richness and abundance, we used
having more than one survey point per farm. Individ- only point-count data in the following way. The number
ual farmers can implement unique practices introducing of individuals and species counted in each circle was av-
unknown sources of data variation, thereby challenging eraged over all counts done in each circle in each year. We
the assumption that each farm is a replicate treatment separated the point-count data by crop versus field border
within management type. In preliminary analyses, signif- portions of each count circle because birds frequenting
icant variation in the data was associated with individ- border vegetation often do not enter more open field habi-
ual farms. However, we did not block for farm in final tats (Sieving et al. 1996), and we wanted to distinguish
analyses because the number of points per farm (2–6) those species actively using crops from those present at
was relatively evenly represented, and by purposefully field edges. For each count circle we derived the follow-
not controlling for individual farmer influences, signif- ing six response variables: mean number of species per
icant outcomes are statistically conservative (i.e., more point count circle (SP); mean number of species in the
general) measures of field-scale influences on habitat use field border vegetation (SB); mean number of species in
and foraging activity on farmlands. crop vegetation (SC) (species richness measures); mean
abundance of birds per point-count circle (standardized
to number per hectare; AP); mean abundance of birds
Determination of Functional Insectivores
per hectare of field border (AB); and mean abundance
To identify species that consumed arthropods in fields, of birds per hectare of crop (AC) (abundance measures).
we conducted a minimum of two 1-hour ad libitum for- Abundance and richness variables were submitted to two
aging observation sessions per survey point during each separate repeated measures multivariate analysis of vari-
of the two breeding seasons (Rodenhouse & Best 1994). ance models (RM-MANOVA; SPSS, version 11.01, SPSS,
Observations were taken within the cropped portions of Chicago) with the following predictor variables: year (re-
the 50-m point-count circles by one observer. After com- peated measure), farm type, crop diversity, border type,
pleting 2 hours of foraging observations at each survey and matrix type (Table 1). We used separate models for
point each year, we focused further sampling effort (2 abundance and richness data because the two metrics are
additional hours) on each of the 30 points with the most associated with distinct questions.
foraging activity (360 hours of foraging observations in We specified a custom model with main effects and
cropped fields). We specifically noted when a bird took two-way interaction terms only and limited our conclu-
invertebrate prey from crop vegetation or from the air sions accordingly because matrix and border type were
above crop plants. Species observed capturing prey in not fully crossed with each other (i.e., empty matrix ×
fields were classified as insect foragers. The 10 insect- border type cells included open × suburb, pine × open
foraging species with the highest abundances in crops and suburb, suburb × open and pine) and higher order
during the growing season were designated functional in- interactions could not be computed. Roy’s greatest root
sectivores ( based on point-count data from the cropped was used to identify significant main effects and inter-
half of survey points). Although we did not assess the actions in the RM-MANOVA models (Scheiner 2001). We
impacts of functional insectivores on either plant growth used a significance level of p ≤ 0.10 in the multivariate
(damage) or on economic returns for farmers, our meth- models. Variables in univariate tests that were significant
ods established that these species were the most likely to ( p ≤ 0.05) and associated with significant terms in the
have such impacts. multivariate model are reported in the text. Bonferroni
multiple comparisons were used to order the means for
significant model variables with more than two factor
Data Analysis
levels.
Because multivariate methods are primarily descriptive
BIRD SPECIES RICHNESS ON FARMS
and our comparative observational study design assumes
To determine whether farm management influences avian no control over several to many unknown influences on
biodiversity, we compared entire farm species counts for our data (James & McCulloch 1995; McGarigal et al. 2000),
organic and conventional farms with Breeding Bird Sur- we used a relaxed alpha level for the MANOVA models to
vey data (FFWCC 2003) and species lists maintained by help ensure that farm characteristics (variables) with po-
the Alachua Audubon Society (2001). Total species counts tential causal relationships to bird community structure
for each farm were determined by adding the number were not missed (minimizing Type II error; James 1985).
of species detected on point counts, outside the fixed- In contrast, given our design constraints, we wanted to
Conservation Biology
Volume 19, No. 4, August 20051238 Functional Insectivory on Farms Jones et al.
minimize Type I error for the univariate tests derived from subjects contrasts) and all but one of the main effects
the MANOVA analyses. This avoids placing undue weight (farm type) were significant (Table 2; Fig. 1). Bird species
on particular factor levels that should not be interpreted richness response variables were significantly correlated
as specific management recommendations without fur- with type of field border and adjacent matrix type and
ther testing. marginally correlated with crop type. Two of five two-
way interaction terms were also significant ( border ×
FUNCTIONAL INSECTIVORE ABUNDANCES crop and border × matrix type; Table 2).
In univariate analyses the between-subjects models for
To determine what habitat features might influence in-
SP and SB were significant ( p ≤ 0.01; F 1,34 = 41.2 and
sectivore abundances in cropped fields, we applied a
51.3, respectively). Both crop type (on SP, F 1,34 = 4.1, p
model of univariate repeated measures analysis of vari-
= 0.05, and SC, F 1,34 = 6.3, p = 0.02) and border type
ance (RM-ANOVA) with the same predictor variables as
(on SP, F 4,34 = 3.8, p = 0.01, and SB, F 1,34 = 3.5, p =
above and mean abundance of the 10 functional insecti-
0.02) were significant main effects. Mixed crops attracted
vore species as the response variable. To address potential
more species than monocrops (per point, mean 10.7 ±
pseudoreplication at the four points that were closer than
0.65 [1 SE] and in crops, 7.4 ± 0.68). Bonferoni multiple
200 m to adjacent point-count circles, we ran all analyses
comparison tests (α = 0.05) indicated that significantly
without two of the adjacent points (randomly selected).
more bird species per point occurred where field borders
We observed no changes in the significance of variables
included hardwood or hedge versus open habitats, and
and a tiny variation in test statistics; therefore, we report
more species occurred in the border half of point-count
results for the complete data set.
circles where borders were hardwood and hedge versus
open or planted pine borders (suburb borders were in-
Results termediate; Fig. 1).
Based on the same RM-MANOVA model with the three
Bird Species Richness on Farms abundance responses (AP, AB, AC; Table 1), there again
were no year effects, and all main effects except farm type
Farm management (organic versus conventional) was not were significant. Matrix × farm type and matrix × bor-
a significant predictor of species richness in statistical der type interactions appeared to be the two most impor-
models based on point-count data alone. Summarizing tant of four that were significant (Table 2). In univariate
both point count and search survey data, however, we tests, the between-subjects models for AP and AB were
observed more bird species, and more unique ones, on or- significant ( p ≤ 0.01; F 1,34 = 20.1 and 28.7, respectively).
ganic than conventionally managed farms (Appendix 1). Bird abundances were significantly higher (p ≤ 0.01) at
Sixty-four different bird species were recorded in point points (F 1,34 = 8.5) and in the crop half of points (F 1,34
counts during the first field season (1 May–30 June 2000). = 13.4) when mixed crops were planted in fields. Abun-
Sixty species were observed in or near organic crops, 49 dances in crops were influenced by an interaction be-
were observed in or near conventional fields, 45 were tween farm type and crop type (F 1,34 = 6.5, p = 0.01).
common to both farm types, 4 were unique to conven- The two most abundant species we sampled were the
tional, and 15 were unique to organic systems. Seventy- Northern Cardinal (Cardinalis cardinalis) and North-
two species were counted in 2001 (25 April–30 June). ern Mockingbird (Mimus polyglottos)—both twice as
Sixty-six of these species were observed in or near organic abundant as the next most abundant species (Summer
and 58 in or near conventionally managed fields. Fifty-two Tanager [Piranga rubra] and Eastern Bluebird [Sialia
species were common to both farm types, 6 were unique sialis]; Appendix 1). Because both species are edge and
to conventional systems, and 14 were unique to organic disturbance associated (Derrickson & Breitwisch 1992;
systems (Appendix 1). Halkin & Linville 1999), we repeated the analysis of
Species we recorded represented 82% of resident and abundance variation without them to gain insights into
migratory landbird species listed as breeders in Alachua whether species with other habitat associations might
County and 96% of those in recent breeding bird surveys respond differently to farm habitat configuration. Year
(along two local routes). We observed 24 listed species on effects (within-subjects contrasts) were unimportant in
organic farms (18 state, 6 federal) and 18 listed species on fitting the multivariate model, and the between-subjects
conventional farms (14 state, 4 federal; Appendix 1). Of model was significant (Table 2). Although farm type was
the five farms with the most bird species, three were or- not significant, the same three main effects and all three
ganic and two conventional. All 10 functional insectivore interaction terms that included matrix type were signifi-
species were observed in both organic and conventional cant. Significant univariate results include the following:
farm fields. between-subjects overall model (AP, F 1,34 = 24.2, p ≤
0.01; AB, F 1,34 = 26.9, p ≤ 0.01); crop type (AP, F 1,34 =
Bird Community Structure at Field Edges
7.4, p = 0.01; AC, F 1,34 = 26.9, p ≤ 0.01 higher abun-
In the RM-MANOVA model with the three species richness dances associated with mixed cropping); border type (all
responses (SP, SB, SC; Table 1), no year effects (within- p ≤ 0.03; AP, F 4,34 = 5.5; AB, F 4,34 = 3.1; AC, F 4,34 = 4.4;
Conservation Biology
Volume 19, No. 4, August 2005Jones et al. Functional Insectivory on Farms 1239 Table 2. Multivariate (RM-MANOVA) results for variation in species richness and bird abundances, including overall model terms (within and between), all main effects, and only significant interaction terms. Source of variation Roy’s largest root F Hypothesis df Error df p Species richness year (within) 0.05 0.57 3 32 0.64 intercept ( between) 1.5 16.22 3 32
1240 Functional Insectivory on Farms Jones et al.
Discussion
In contrast to studies of farmland bird diversity on larger
industrialized farms (Chamberlain & Vickery 2002; Mur-
phy 2003; Peterjohn 2003), we found that farmlands in
north-central Florida support a large proportion of bird
species native to the region. Moreover, nearly all birds
we watched foraging were not being destructive to crops
but were eating invertebrates that eat crop plants. These
patterns are reminiscent of findings by early farmland
bird researchers, before the rise of industrial agriculture,
when native birds interacted in primarily positive ways
with farming systems (Forbush 1907; Weed and Dearborn
1935).
Avifauna on Organic and Conventional Farms
Figure 1. Mean number of bird species detected on A few more species on average were found on organic
point counts by (a) crop, (b) matrix, and (c) than on conventional farms, but overall species richness
field-border type (error bars, 1 SE; white bars, was similar on the two farm types. Unlike similar studies
birds/point; black bars, birds in border; striped bars,
birds in crop).
Table 3. Results of model for functional insectivore abundances in
crops (crop half of survey points; no. birds/ha).∗
Type III SS Mean F p
56 times/season (Northern Cardinals) in cropped fields.
The two most abundant functional insectivores were also Within (df )
the most abundant species overall (cardinal and mock- year (1) 0.25 0.2 0.11 0.74
error (34) 79.00 2.3
ingbird). Using an RM-ANOVA model, we found no ef- Between df
fect of year, and the only significant main effect on mean intercept (1) 0.54 0.5 0.03 0.85
abundances of functional insectivores in crops was crop crop (1) 109.6 109.6 7.10 0.01
diversity. Mixed crops hosted higher abundances of in- error (34) 525.00 15.0
sectivores than monocrops (Table 3; mixed crops, mean ∗ Onlymodel summary terms and significant main effects and
= 3.7 birds/ha ± 0.5 [1 SE]; monocrops, 1.5 ± 0.5). interaction terms are reported.
Conservation Biology
Volume 19, No. 4, August 2005Jones et al. Functional Insectivory on Farms 1241
Figure 2. Mean bird abundance (excluding Northern
Figure 3. Field border × adjacent matrix type
Cardinal and Mockingbird) by field-border vegetation
interaction for mean bird abundances in crop half of
type (white bars, birds/point; black bars, birds in
point-count circles (excluding Northern Cardinal and
border; stripe bars, birds in crop; error bars, 1 SE).
Mockingbird; error bars = 1 SE).
Bird Community Structure at Field Edges
(Canada, Freemark & Kirk 2001; United States, Beecher
et al. 2002; Europe, Christensen et al. 1996; Chamber- Bird abundance variation, whether cardinals and mock-
lain et al. 1999), statistical analyses of point-count data ingbirds were included or not, was similar in overall pat-
revealed no differences in bird community structure be- tern to species richness variation (Table 2). Crop type
tween organic and conventional farm fields in north- (mixed or monoculture) was strongly associated with bird
central Florida. Two factors most likely contributed to abundances in cropped fields, and both matrix and field
this contrasting result. First, mixed crops were uncom- border vegetation type figured prominently as explana-
mon or absent in fields surveyed in the other studies. But tory variables for both abundance and species richness
in our study, crop diversity was a strong predictor, and variation (Figs. 1, 2, & 3). Matrix type had more influ-
both conventional and organic farms had mixed crops. ence on abundances after the two edge species were
Mixed-cropping systems generate greater biomass of in- removed because many of the remaining species were
vertebrate foods for birds (Andow 1991; Elliott et al. 1998; forest birds (Table 2). This could explain why forested
see below), and this may offset reduced bird occurrence field borders and matrix types (i.e., hardwood forest,
that could be caused by chemical suppression of food pine plantations, and suburbs) were associated with high
sources (e.g., Nyffeler et al. 1994) on the conventional species richness and abundance. These findings confirm
farms that had mixed crops in our study. that structurally complex windbreaks, hedgerows, and
Second, both organic and conventional farms in north- field borders support more farmland birds than conven-
central Florida are relatively small (10 out of 20 were < 10 tional “clean-farming” practices that suppress noncrop
ha) compared with farm areas used in other studies span- vegetation (Green et al. 1994; Chamberlain & Wilson
ning 2–3 orders of magnitude. As a largely forested region 2000; Deschenes et al. 2003). Furthermore, our findings
with diverse industries (FNAI 2004), north-central Florida suggest that farmland bird communities in north-central
presents a “patch mosaic” of diverse habitat types essen- Florida can be managed at the scale of landowner influ-
tial for the maintenance of bird (and other) species on ence (sensu Hostetler 1999). Cropping practices, field
farmlands. Thus, in regions with larger farms and fields, border plantings, and field placement with respect to ad-
with distant sources of birds, and where mixed cropping jacent blocks of noncrop vegetation might be manipu-
and maintenance of hedgerows and woodlots are less lated to enhance species richness at the farm-field scale.
common, organic farm practices may be more important On-farm management to enhance bird diversity may be
in determining bird species diversity via production of relevant, however, only in landscapes with sufficient na-
bird foods (Christensen et al. 1996). tive habitat elements (like this one; FNAI 2004), where
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Volume 19, No. 4, August 20051242 Functional Insectivory on Farms Jones et al.
native biodiversity and nearby source habitats are abun- served in crops. We observed, however, primarily insec-
dant (Rice & Greenberg 2000; Luck & Daily 2003). tivory by birds in crops, frequent consumption of known
pest insects, no large flocks of crop-depredating birds,
Functional Insectivores in Cropped Fields and only isolated and minor instances of crop damage.
Blueberries (Vaccinium spp.) in the area suffer heavy
In contrast to community-level patterns at field edges,
bird damage in the growing season (Avery et al. 1993),
abundance of the 10 functional insectivores in crops
but they were absent from our sites. In our study system
was predicted solely by crop type (Table 3). In both
birds were not agricultural pests.
years, fields planted with polycultures attracted higher
Imprecise descriptions of avian diets may help distort
abundances of functional insectivores than monocropped
perceptions of species’ functional roles in agroecosys-
fields, regardless of other factors. The relative lack of im-
tems. Although many species we observed taking insects
portance of field border and matrix habitats in predict-
in crops are classified as insectivores, several of the func-
ing functional insectivore distributions is understandable
tional insectivores we identified are not. The Northern
because Northern Cardinals and Mockingbirds are both
Cardinal is usually classified as an omnivore (De Graaf et
edge-associated species and numerically dominated our
al. 1985) and popularly known as a seedeater because
data. Because they both frequent all types of edges, the
it frequents backyard bird feeders. Yet the cardinal was
suitability of the crop as foraging habitat becomes the
the most abundant functional insectivore in our study, and
most important influence on their willingness to use it.
they made longer foraging bouts and took more prey than
Consistent with findings of Rodenhouse and Best
other species. Two other species not typically classified as
(1994) and Stallman and Best (1996), the most attractive
insectivores, Blue Grosbeaks (Guiraca caerulea) and In-
fields in our study had the greatest structural complex-
digo Buntings (Passerina cyanea), were among the func-
ity (vegetables with cut-flower intercrops) followed by
tional insectivores (Appendix 1) and caused no crop dam-
multiple vegetable crops. Monocropped systems had the
age that we observed. These birds’ diets are omnivorous
fewest birds (watermelon least attractive). An additional
when summarized over an entire year and a few species
attraction of mixed crops is likely to be increased food
(e.g., Red-winged Blackbirds [Agelaius phoeniceus]) may
availability because insect species richness and diversity
cause crop damage outside the breeding season. But be-
are correlated with vegetative diversity in cropped fields
cause most omnivores and granivores become highly in-
(Andow 1991; Elliott et al. 1998). Given that organic fields
sectivorous during the breeding season to support repro-
support greater arthropod diversity (Dritschillo & Wanner
duction and nestling growth (Beal et al. 1941; Martin et
1980; Feber et al. 1997; O’Leske et al. 1997), and thus a
al. 1951), we advocate the utility of a functional insecti-
greater diversity of food for birds (Brea et al. 1988), the
vore designation in the context of farmland birds. More
use of polyculture cropping on our conventional farms
accurate assessments of positive and negative interactions
may have equalized bird diversity between organic and
with cropping systems can be made if the seasonality of
conventional sites.
bird diets is emphasized.
Birds perched on sprinkler heads (in 13 sample points)
Our results strongly suggest that in some cropping
and on stalks of mature corn or sunflower plants late in
systems the integration of avian insectivory into pest-
the growing season (for a total perch availability of 20 in
management schemes may provide measurable benefits
mixed crops, 12 in monocrop, 15 in conventional, and
to growers in terms of plant growth and economic returns
17 in organic samples). To test for the possibility that
(McFarlane 1976; Kirk et al. 1996). Increased awareness
perches may have influenced bird use of fields, we con-
of the functional role insectivorous species may have in
ducted a three-way RM-ANOVA to test for the influence
cropping systems should encourage further research and
of farm type, crop diversity, and the presence of perches
avian conservation efforts, particularly on farms in hetero-
within point-count circles on mean bird abundance and
geneous, seminatural landscapes that still support func-
species richness in the crop half of count circles. Crop
tionally significant populations of native insectivores. En-
type was a highly significant factor (of main effects and
couragingly, 91% of Florida farmers surveyed statewide
interactions) for both abundance (F 1,53 = 4.4, p = 0.042)
(conventional and organic) believed birds could help
and richness (F 1,53 = 9.0, p = 0.004). Perch availability
lower insect populations on their farms. Eighty-five per-
was less influential (abundance, F 1,53 = 2.6, p = 0.115;
cent also indicated they would like to attract such birds,
richness, F 1,53 = 1.6, p = 0.213). Although perch availabil-
and more than one-third of farmers surveyed were already
ity can influence bird distributions (e.g., Holl 1998), the
engaged in attracting birds to their farms ( Jacobson et al.
post hoc analysis indicated that perches did not swamp
2003). The potential exists for integrating bird conser-
the influence of crop diversity in our study.
vation with farm production, particularly if research is
devoted to illuminating the benefits to farmers. As con-
Overcoming Pessimism for Biodiversity-Friendly Agriculture
ventional agriculture is pushed to embrace sustainability,
Because some bird species can be pests in farms, a nega- research results are needed to guide the integration of
tive role is often the first or only one ascribed to birds ob- ecological complexity (McNeely & Scherr 2003).
Conservation Biology
Volume 19, No. 4, August 2005Jones et al. Functional Insectivory on Farms 1243
Acknowledgments Chamberlain, D. E., J. D. Wilson, and R. J. Fuller. 1999. A comparison
of bird populations on organic and conventional farm systems in
southern Britain. Biological Conservation 88:307–320.
The Florida First/Institute of Food and Agricultural Sci- Christensen, K. D., E. M. Jacobsen, and H. Nohr. 1996. A comparative
ence initiative of the University of Florida funded this study of bird faunas in conventionally and organically farmed areas.
study. We acknowledge the participation of numerous Dansk Ornithologisk Forenings Tidsskrift 90:21–28.
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sion agent G. Brinen and M. Mesh of the Florida Certified in Avian foraging: theory, methodology, and applications. Studies
Organic Growers and Consumers; M. Reetz, L. Santiste- in avian biology, no. 13. Cooper Ornithological Society, Camarillo,
ban, and K. Smith for field assistance; and M. Hostetler and California.
two anonymous reviewers for helpful comments. This is Dauber, J., M. Hirsch, D. Simmering, R. Waldhart, A. Otte, and V. Wolters.
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Appendix 1. Bird species observed in all surveys by farm and habitat type and mean abundance of 10 functional insectivores (n = 127) observed.
Functional insectivore Conservation
Common name, scientific name Farma Habitat b abundance, birds/ha (1 SE) statusc
Acadian Flycatcher, Empidonax virescens O M CC–FWC
American Bald Eagle, Haliaeetus leucocephalus C M T–FWS
American Crowd , Corvus brachyrhynchos B FM
American Kestrel, Falco sparverius O F SSC–FWS
American Redstartd , Setophaga ruticilla O FM CC–FWC
Barn Swallow, Hirundo rustica C FM
Bay-breasted Warblerd , Dendroica castanea O FM CC–FWC
Black Vulture, Coragyps atratus C FM
Black-and-white Warblerd , Mniotilta varia C FM CC–FWC
Blackpoll Warbled , Dendroica striata B FM CC–FWC
Blue Grosbeakd,e , Guiraca caerulea B FM 0.19 (0.07)
Blue Jayd , Cyanocitta cristata B FM
Blue-gray Gnatcatcherd , Polioptila caerulea B FM
Blue-headed Vireo, Vireo solitarius O M
Boat-tailed Grackled , Quiscalus major O F
Bobolinkd , Dolichonyx oryzivorus O FM CC–FWC
Brown Thrasherd,e , Toxostoma rufum B FM 0.06 (0.03)
Brown-headed Cowbirdd , Molothrus ater B FM
Carolina Chickadeed , Parus carolinensis B FM
Carolina Wrend , Thryothorus ludovicianus B FM
Cattle Egretd , Bubulcus ibis B F
Cedar Waxwing, Bombycilla cedrorum B M
Chimney Swift, Chaetura pelagica B FM
Common Grackle, Quiscalus quiscula B F
Common Ground Doved , Columbina passerina B FM SSC–FWS
Common Yellowthroatd , Geothlypis trichas B FM
Downy Woodpeckerd , Picoides pubescens B FM
Eastern Bluebirdd,e , Sialia sialis B FM 0.25 (0.11) CC–FWC
Eastern Kingbirdd , Tyrannus tyrannus B F CC–FWC
Eastern Meadowlarkd , Sturnella magna B FM CC–FWC
Eastern Towhee, Pipilo erythrophthalmus B M
Eastern Tufted Titmouse, Parus bicolor B M
Eastern Wood-pewee, Contopus virens O M
European Starling, Sturnus vulgaris B FM
Fish Crow, Corvus ossifragus B FM
Gray Catbirdd , Dumetella carolinensis B FM
Great Crested Flycatcherd,e , Myiarchus crinitus B FM 0.13 (0.05)
Great Horned Owl, Bubo virginianus O M
Green Heron, Butorides striatus O F
House Finchd , Carpodacus mexicanus B F
Indigo Buntingd,e , Passerina cyanea B FM 0.07 (0.03) CC–FWC
Killdeer, Charadrius vociferus C FM
Loggerhead Shriked,e , Lanius ludovicianus B FM 0.05 (0.03) SSC–FWS
Mississippi Kite, Ictinia mississippiensis B M CC–FWC
Mourning Doved , Zenaida macroura B FM
Northern Bobwhited , Colinus virginianus B FM CC–FWC
Northern Cardinald,e , Cardinalis cardinalis B FM 0.64 (0.13)
Northern Mockingbirdd,e , Mimus polyglottos B FM 0.51 (0.16)
Northern Parulad , Parula americana B FM
Orchard Orioled,e , Icterus spurius B FM 0.27 (0.12)
Ovenbird, Seiurus aurocapillus O M CC–FWC
Pileated Woodpecker, Dryocopus pileatus B M
Pine Warbler, Dendroica pinus B M CC–FWC
Purple Martin, Progne subis B FM CC–FWC
Red-bellied Woodpeckerd , Melanerpes carolinus B FM
Red-eyed Vireo, Vireo olivaceus B M CC - FWC
Red-headed Woodpeckerd , Melanerpes erythrocephalus O F SSC–FWS
Red-shouldered Hawkd , Buteo lineatus B FM
Red-winged Blackbirdd , Agelaius phoeniceus B FM
Rock Doved , Columba livia C F
Rough-winged Swallow, Stelgidopteryx ruficollis B FM
Rudy-throated Hummingbirdd , Archilochus colubris B FM CC–FWC
Sandhill Craned , Grus canadensis O FM T–FWS
Summer Tanagerd,e , Piranga rubra B FM 0.25 (0.11)
Turkey Vulture, Cathartes aura C FM
Western Palm Warblerd , Dendroica palmarum B FM CC–FWC
White Ibis, Eudocimus albus B FM SSC–FWC
White-eyed Vireo, Vireo griseus B M
Wild Turkeyd , Meleagris gallopavo B FM CC–FWC
Yellow-billed Cuckoo, Coccyzus americanus B M CC–FWC
Yellow-shafted Flicker, Colaptes auratus B M
Yellow-throated Vireo, Vireo flavifrons B F
a Farm type O, organic; C, conventionally managed; B, both farm types.
b Habitat type of 50-m survey points: F, cropped half; M, matrix.
c Conservation status of species according to U.S. Fish and Wildlife Service (FWS) and Florida Fish and Wildlife Conservation Commission (FWC) designations: CC, conservation concern; T,
threatened; SSC, species of special concern (Millsap 1990).
d Insect forager: species observed foraging for invertebrates in crop vegetation.
e Functional insectivore: the 10 most common species observed capturing invertebrates in crop vegetation.
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