ECOLOGY AND CONSERVATION OF BIRDS IN ...

ECOLOGY AND CONSERVATION OF BIRDS IN COFFEE PLANTATIONS OF EL SALVADOR, CENTRAL AMERICA By Oliver Komar B.A., Ohio Wesleyan University, 1997 Submitted to the Department of Ecology and Evolutionary Biology and the Faculty of the Graduate School of the University of Kansas In partial fulfillment of the requirements for the degree of Doctor of Philosophy.

_______________________________ chairperson _______________________________ Committee members _______________________________ _______________________________ _______________________________

Date defended: ____________________

© 2006 Oliver Komar

The Dissertation Committee for Oliver Komar certifies that this is the approved version of the following dissertation:

ECOLOGY AND CONSERVATION OF BIRDS IN COFFEE PLANTATIONS OF EL SALVADOR, CENTRAL AMERICA

Committee: ________________________ Chairperson ________________________

_________________________

_________________________

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Date approved _________________

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KOMAR, OLIVER, B. A., Ph. D. Dept. of Ecology and Evolutionary Biology The University of Kansas, Lawrence, Kansas USA

DISSERTATION ABSTRACT

Since the early 1990s, much interest in avian use of coffee plantations was inspired by hypotheses proposing that conversion of traditional coffee plantations, grown under a diverse canopy of shade trees, into modern, technified plantations with severely reduced shade canopies, contributed to declines of long-distance migratory birds. Published literature has not yet tested that hypothesis nor demonstrated a clear conservation benefit for birds of conservation concern (i.e., greater survivability, fitness, or productivity) in shaded coffee plantations compared with other available habitats. I field tested the hypothesis that coffee canopy characteristics influence migratory bird abundances in El Salvador. Migratory birds as a group were significantly more abundant in coffee plantations than in forest, but the pattern was not significant for individual species. Because conservation programs certify coffee plantations as ecologically sustainable and “bird-friendly” if they have ≥40% canopy cover, ≥12 native tree species ha-1, and many emergent trees, I regressed migratory bird abundance against these variables. Only 4 of 23 species analyzed were positively correlated to the variables. The results did not support the supposition that certification programs generally benefit migratory birds, or that coffee technification

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has harmed migratory bird populations. I also evaluated potential affects of existing certification criteria on 16 resident bird species that were potential beneficiaries of ecological certification, each being negatively associated with habitat disturbance. A coffee plot with 40% canopy cover and 12 tree species ha-1 would likely hold 2 km from large (>100 ha) natural forest patches. Most plantations were associated with some small (generally 21 ha, to place a 5 ha plot (500 m x 100 m) in the interior of a homogeneous patch. To maximize efficiency and reduce travel time, we located up to four plots at each site, permitting sampling of two plots per morning. Plots located at a single site were placed as far apart as possible given landscape constraints (100–400 m). Sites were generally several km apart, and the farthest two sites were separated by ~40 km. We looked for significant effects of independent variables on abundances of 23 long-distance Nearctic–Neotropical migratory bird species recorded at ≥3 plots. Most analyses did not include 11 migratory species recorded at 50% of trees sampled on some farms. We analyzed data twice, once including and once excluding windbreak trees in the data (except for canopy cover since effects on shade could not be removed). We also included elevation and date (days after 1 November, roughly equivalent to the beginning of the dry season) as independent variables. We established nine sampling circles located at 50 m intervals along the long axis of each 100 × 500 m study plot, where we measured canopy cover and all tree stems within a radius of 13.3 m. As each circle had an area of 555.7 m2, we thus sampled 0.5 ha total in each study plot. To estimate canopy cover, we used a convex spherical crown densiometer (Forestry Suppliers, Inc., Jackson, Mississippi, USA) held at the height of the tops of coffee shrubs. When necessary, we climbed a step ladder, or tied back coffee shrubs to avoid recording shade caused by the shrubs themselves. We took four densiometer readings at the circle midpoint while facing in each of the four cardinal directions (determined by compass), and four additional readings in the same manner at each of four points 13.3 m to the N, S, E, and W of the midpoint; hence, we took 20 readings in each circle, and 180 readings in each study plot. We used the mean of all percent shade cover readings as the estimate of canopy cover for the entire plot (Lemmon 1956, 1957). For calculations of tree basal area, we included all trees both ≥3 m height and ≥5 cm diameter at breast height (DBH). With a tape measure, we recorded circumference at breast height and converted to basal area as area = c2/4π. Tree basal area was the sum of basal areas of all trees in all sampling circles in a given plot. Tree

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species diversity was tree species richness found in the 0.5 ha sampled per plot. We identified all trees meeting the size criteria (above) to species or morphotype; when possible, we collected samples for determination at the La Laguna Botanical Garden. Identifications of trees were more accurate during the wet season, when more species were fruiting or flowering and when field workers had accumulated more experience with tree identification; therefore, we derived tree diversity estimates from visits to all sites during April–September 2000. We estimated canopy structure by calculating standardized relative variation in tree height as estimated by inspection. For this calculation, we used the coefficient of variation (CV = 100 σ /mean, Sokal and Rohlf 1995, also used by Greenberg et al. 1997a) of tree height in the 0.5 ha intensively sampled in each plot. We defined emergent trees as those ≥13 m tall, 50–100% taller than the average trees at our coffee sites. The density of emergent trees was the number of trees ≥13 m tall present in the vegetation plots at each site. Tree density was the count of all trees meeting the size criteria (above). We also created a combined habitat predictor metric, using principal components analysis (PCA) to generate linear combinations combining the six variables measured. Because the habitat variables had widely varying scales, we based the PCA on a correlation matrix. The first principal component—with all variables loading negatively—described vegetation “size,” essentially equivalent to a measure of disturbance across sites. Two PCAs, with windbreaks included and excluded, produced similar results (Table 2-1). Natural forest sites scored at one end of the axis while the most intervened (“technified” sensu Rice and Ward 1996) coffee

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TABLE 2-1. Principal components and eigenanalysis of the correlation matrix for habitat variables in shaded coffee plantations and natural forest habitat. Windbreaks included PC1 PC2

Windbreaks excluded PC1 PC2

-0.48 -0.36 -0.48 -0.46 -0.20 -0.39

-0.12 -0.54 0.07 -0.15 0.72 0.37

-0.48 -0.42 -0.47 -0.47 -0.09 -0.38

0.12 0.41 -0.05 0.02 -0.83 -0.35

Eigenvalue Proportion Cumulative

3.94 0.66 0.66

1.39 0.23 0.89

3.99 0.67 0.67

1.21 0.20 0.87

Second Component

Variable Tree species richness Tree density Canopy cover (shade) Basal area (trees) Height-CV (trees) Abundance of emergent trees

2 1 0 -1 -2 -3 -4

-3

-2 -1 0 First Component

1

2

FIGURE 2-2. Plots of principal components analysis on habitat variables of coffee and natural forest sites. The first component describes variation in disturbance level across the study sites. Natural forest (relatively undisturbed) plots scored towards the left end of the horizontal axis (solid dots), while highly altered coffee plantations scored towards the right end of the axis (open dots). The equivalent plot with windbreaks excluded is similar.

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sites scored at the opposite end (Fig. 2-2); we thus considered the scores on this axis as an index of forest disturbance. We rescaled the range of scores for ease of interpretation, so that all scores were positive, forming an index of 0–12, with 0 being least and 12 being most disturbed.

MIST-NET CAPTURE DATA

We carried out ground-level mist-netting at three natural forest sites as well as two coffee sites (Cooperativa Concepción Miramar and Finca Nuevos Horizontes). Mistnetting at the coffee sites also included netting at forest fragments (forest similar in structure to the major forest sites) measuring 40 ha and 4 ha, respectively. Birds captured in small forest fragments were classified as forest captures. Mist-netting was carried out only during the 2001–2002 study period. Mist nets were generally standard black-nylon, 36 mm mesh, measuring 12 × 2.5 meters when fully extended; a few were shorter or had smaller mesh size and were considered ½ or ¾ nets in calculations of net-hrs. We left nets standing for 3–7 days, moving them when capture rates dropped notably. We opened up to 30 nets in a day, generally all day long, and checked them frequently. Mist-netting effort was 4562 net-hrs in natural forest and 1088 net-hrs in shaded coffee plantation. We used a subsample of netted birds (57 birds in coffee and 120 birds in natural forest) to compare age and sex classes in the two habitats. We determined sex by examination of gonads, and age by presence or absence of bursa of Fabricius (Glick 1983). In addition to collected birds, we recorded data from released birds of

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species for which sexing or aging was possible by standard plumage characters (Pyle 1997). We treated birds aged as first or second year as immatures, and third year as adults. At most sites, we marked released birds to avoid double counting of recaptured individuals. At El Imposible National Park, where some released birds were not marked, we adjusted capture numbers for a few species using recapture rates from other sites. We deposited collected birds at the University of Kansas Natural History Museum, the Field Museum, and the Museo de Historia Natural de El Salvador.

STATISTICAL ANALYSES

We used simple and multiple linear regression to assess the responses of bird abundance to predictor variables. For simple regression, we transformed variables as necessary (arc-sine or log transforms) when residuals were not normally distributed or homoscedastic, to improve fit to a linear trend line. We tested for normality of standardized residuals using the Anderson-Darling test, and for independence with the Durbin-Watson serial correlation test (Draper and Smith 1998). We tested homoscedasticity using Szroeter's test (Szroeter 1978, Dielman 1991). The first two tests were performed using Minitab Release 13.30 statistical software (Minitab 2000), with α = 0.05. For stepwise multiple regression analysis, we selected α = 0.15 as the criterion to enter or remove a variable from the models. For multiple regressions, abundances of individual species were log10 transformed. Two predictors, tree species richness and basal area, were highly correlated (r > 0.75) to canopy cover (Appendix)

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and were not considered for multiple regression models. Regressions were performed using Minitab (2000). To compare relative abundances of bird species between forest and coffee, we used the General Linear Model of analysis of variance (ANOVA), with mean counts of each species (individuals 5 ha-1) as response variables. Because study plots were grouped nonrandomly among 10 sites, we included site as a nested random factor, and habitat as a fixed factor. For comparisons of captures of all migrants and individual migrant species in each habitat type with total captures ≥20, we generated expected counts based on proportional mist-net effort in each habitat type, and tested differences with a log-likelihood ratio test (G-test) for goodness of fit (Sokal and Rohlf 1995), using the Williams (1976) correction. To maintain independence of captures, we treated possible pairs and flocks (groups of conspecifics captured at approximately the same time in a single net or group of nets) as single individuals. For species with ≥10 and 13 m (0.5 ha-1)

822 546 274 185 225

136 105 67 118 127 150 128 148 142 176 210 129 217 373 21 39 89 102

Trees (0.5 ha-1)

93 72 75 49 60

17 15 28 17 36 39 30 34 17 22 27 18 13 14 6 4 24 23

Tree spp.

14.1 18.3 14.8 11.6 8.7

3.3 3.0 4.5 2.9 8.5 10.7 4.2 3.3 4.0 7.2 6.2 4.8 6.1 5.8 2.6 2.9 4.8 2.4

Basal area (m2 0.5 ha-1)

25 36 41 45 48

21 20 37 23 39 40 35 35 18 19 22 34 23 17 49 41 33 39

HeightCV (%)

817 545 274 186 217

97 75 61 51 120 133 126 146 74 78 72 79 81 94 21 39 89 103 93 72 75 49 60

17 15 28 16 36 39 28 32 15 16 26 17 12 12 6 4 24 23 14.1 18.3 14.8 11.6 8.7

2.7 2.6 4.4 2.3 8.5 10.6 4.2 3.3 5.7 5.3 5.1 4.2 3.3 3.6 2.6 2.9 4.8 3.2 25 36 41 45 48

30 36 37 37 64 66 36 45 33 30 29 23 38 37 51 31 37 37

Windbreaks excluded Trees Tree Basal Height(0.5 CV spp area ha-1) (%) (m2 0.5 ha-1)

0.0 0.0 0.0 0.0 0.0

1.2 1.3 0.2 0.4 0.0 0.0 0.4 0.2 0.8 0.6 0.0 0.0 0.0 0.0 0.0 0.0 0.8 1.2

Dendroica petechia (birds 5 ha-1)

0.3 1.2 0.0 0.4 0.2

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.6 0.0 0.0 0.0 0.0

Seiurus aurocapilla (birds 5 ha-1)

TABLE 2-4. Habitat at 18 coffee plots and five natural forest plots, and corresponding densities for two bird species.

variables, explained 33% of variation of counts of Ovenbirds (P = 0.004, Table 2-3). The model suggests that Ovenbirds would likely be present in a 5-ha plot only when canopy cover exceeds 37%. The Ovenbird also was the only species for which abundance was related to tree species richness:

D = -0.045 + 0.005 S

where S is tree species per 0.5 ha (r2 = 0.21, P = 0.028). This relationship suggests that >9 tree species per 0.5 ha plot is required for Ovenbirds to be present. The model with transformed variables is only slightly better, explaining 23% of variation in Ovenbird abundance. The Yellow-throated Vireo and Ovenbird were the only species sensitive to density of emergent trees. In both cases the response to emergent tree density was positive, though stronger in the vireo. For the vireo, the model for abundance regressed against emergent tree density is:

D = 0.039 + 0.0046 E

where E is emergent trees per 0.5 ha plot. This model predicts that vireos will be present even if there are no emergent trees, but in that case vireo abundance would be 15% of the natural forest abundance.

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Multiple regression models showed that some species may have more complex relationships with the habitat variables measured (Table 2-5). A multivariate model for Yellow-throated Vireo suggests that the species’ relationship to emergent tree density was intensified at plots where overall disturbance was higher. Rubythroated Hummingbird responded negatively to canopy cover and Wilson’s Warbler responded positively to canopy structure, when modeled with elevation. Magnolia Warbler (Dendroica magnolia) responded negatively to canopy structure when windbreaks were included in variables, and other factors were added to the models. Blue-gray Gnatcatcher appeared to show a preference for emergent trees when date was included in the model. Although including windbreaks in parameter estimations generally had little effect on results, the multivariate model for Ovenbird with windbreaks included explained 56% of variation in that species’ abundance, whereas the model with windbreaks excluded explained only 43% (Table 2-5).

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Pheucticus ludovicianus

Passerina cyanea

Empidonax minimus

D. petechia

Dendroica magnolia

Archilochus colubris

All migrants combined (sum of standardized mean densities)

Dependent variables

date 0.20 –

shade 0.26 –

date 0.38 – elevation 0.28 –

elevation 0.32 +

elevation 0.35 –

height-CV 0.46 – shade 0.53 –

trees 0.54 –

date 0.38 – elevation 0.28 – elevation 0.13 – shade 0.26 – height-CV 0.32 – date 0.12 + date 0.20 –

height-CV 0.57 – shade 0.53 – height-CV 0.28 – elevation 0.35 – shade 0.40 + height-CV 0.29 elevation 0.32 +

date 0.36 +

disturbance 0.49 +

Independent variables, r2, and slope direction Windbreaks excluded Windbreaks included

TABLE 2-5. Multivariate regression models that best explain variation in migratory bird abundances in natural forest and coffee plantations of El Salvador. Independent variables are listed in the order added to each model, with r2 values and slope direction below.

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Wilsonia pusilla

Vireo flavifrons

Vermivora peregrina

Seiurus aurocapilla

Polioptila caerulea

Dependent variables

Table 2-5, continued. Independent variables, r2, and slope direction Windbreaks excluded Windbreaks included date emergents date emergents 0.25 0.42 0.25 0.42 – + – + tree density emergents tree density emergents 0.36 0.43 0.46 0.56 + + + + date elevation date elevation tree density 0.21 0.30 0.21 0.30 0.39 – – – – – emergents disturbance elevation 0.28 0.37 0.44 + + elevation height-CV 0.44 0.57 + +

BIRD ABUNDANCE IN COFFEE VS. NATURAL FOREST

We observed more migrants in coffee plots (mean density 27 ± 6 birds 5 ha-1) than in forest plots (16 ± 7 birds 5 ha-1). Removing possible biases caused by one or a few abundant species, by summing standardized counts, coffee plots still had more migrants than forest (37 vs. 24). A t-test (assuming unequal variances) rejected the null hypothesis of equal abundances in the two habitats (t = 2.4, df = 16, P = 0.031). No single species had significantly higher abundances in coffee when compared with natural forest. Two species, however, were significantly more abundant in natural forest: Ovenbird, a ground feeder, and Yellow-throated Vireo, a canopy feeder (ANOVA, Table 2-6). Five of 23 species showed significant site effects, however, suggesting that for Sharp-shinned Hawk, Ruby-throated Hummingbird, Magnolia Warbler, Yellow Warbler, and Indigo Bunting (Passerina cyanea), plots within sites may not have been independent. Mist nets captured migrants at a higher rate in coffee (9.0 birds 100 net-hrs-1) than in forest (7.1 birds 100 net-hrs-1), but the higher rate in coffee was influenced by more frequent monospecific flocks of Indigo Bunting. When only independent capture events were considered, rates were 6.3 for coffee vs. 5.4 for forest (Table 2-7, G = 1.0, df = 1, P > 0.05). There were no differences between the proportion of immatures and adults or of males and females in the two habitats (Table 2-8). Among individual species, only two of eight migrants were significantly more frequent in coffee netting samples than in forest samples (Table 2-7): Warbling Vireo (Vireo gilvus) and Indigo Bunting. For the vireo, this pattern contradicts the pattern

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suggested by observations (Table 2-6). Three of eight species appeared to prefer natural forest, being captured there more than twice as frequently as in coffee: Ovenbird, Black-and-white Warbler (Mniotilta varia), and Tennessee Warbler, although we could not reject the null hypothesis of equal capture rates for any of these species. Observations suggest that more species of migrants occupied shaded coffee plantations than natural forest. More species were observed in coffee (33 species) than in forest (18 species), and although sampling effort was greater in coffee, the shapes of randomized species accumulation curves in each habitat suggest that more migratory species would have been present in coffee for equivalent sized samples (Fig. 2-4).

35 30

Species

25 20

Coffee Forest

15 10 5 0

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 5-ha plots

FIGURE 2-4. Randomized species accumulation curves for migratory birds suggest that species richness was higher in shaded coffee plantations than in natural forest. 95

TABLE 2-6. Estimated mean wintering densities in coffee and natural forest for 34 migratory species. Species with no statistical results were recorded at just one or two plots. Actual densities were probably higher, as these data are not corrected for detection probabilities, which are likely to vary among species and among habitats. Significant P values are indicated by an asterisk.

Species

Mean density (birds 5 ha-1) in coffee (n = 18) Accipiter striatus 0.06 Archilochus colubris 2.86 Buteo platypterus 0.08 Catharus ustulatus 0.19 Dendroica magnolia 0.72 Dendroica petechia 0.39 Dendroica townsendi 0.33 Dendroica virens 1.41 Empidonax flaviventris 0.01 Empidonax minimus 0.77 Falco sparverius 0.01 Helmitheros vermivorum 0.00 Icteria virens 0.02 Icterus galbula 0.03 Icterus spurius 0.01 Mniotilta varia 0.36 Oporornis tolmiei 0.12 Passerina ciris 0.03 Passerina cyanea 0.40 Pheucticus ludovicianus 0.11 Piranga ludoviciana 0.85 Piranga rubra 0.06 Polioptila caerulea 0.16 Seiurus aurocapilla 0.04 Seiurus motacilla 0.01 Setophaga ruticilla 0.03 Tachycineta thalassina 0.11 Tyrannus verticalis 0.12 Vermivora chrysoptera 0.01 Vermivora peregrina 14.61 Vireo flavifrons 0.07 Vireo gilvus 0.46 Vireo solitarius 0.32 Wilsonia pusilla 1.94 All migrants combined 26.73

SE Mean density (birds 5 ha-1) in forest (n = 5) 0.03 0.00 0.87 0.27 0.03 0.04 0.10 0.44 0.15 0.42 0.11 0.00 0.14 0.10 0.32 0.30 0.01 0.00 0.23 0.64 0.01 0.00 0.00 0.04 0.02 0.00 0.02 0.00 0.01 0.00 0.12 0.35 0.09 0.00 0.03 0.00 0.16 0.12 0.05 0.00 0.25 2.25 0.02 0.00 0.07 0.39 0.04 0.42 0.01 0.00 0.02 0.00 0.11 0.00 0.11 0.00 0.01 0.00 5.40 7.34 0.04 0.24 0.11 0.71 0.10 0.35 0.35 1.67 16.09

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SE

Nested ANOVA Habitat Site F P F P

0.00 0.5 0.493 13.3 0.12 0.9 0.361 4.9 0.04 0.1 0.744 2.3 0.16 0.9 0.354 0.8 0.15 0.7 0.417 2.8 0.00 1.3 0.279 8.0 0.10 0.6 0.448 1.5 0.09 1.4 0.265 2.3 0.00 0.23 0.2 0.710 2.5 0.00 0.04 0.00 0.00 0.6 0.436 0.7 0.00 0.16 0.1 0.726 2.4 0.00 0.3 0.612 2.2 0.00 0.12 0.02 0.897 17.0 0.00 0.7 0.411 2.1 1.00 0.5 0.493 2.1 0.00 0.7 0.414 2.3 0.17 3.5 0.087 1.6 0.20 6.4 0.021 * 0.4 0.00 0.00 0.00 0.00 0.00 4.70 0.4 0.553 1.7 0.15 7.7 0.015 * 0.8 0.32 0.01 0.928 1.5 0.12 0.5 0.492 1.2 0.75 0.01 0.932 2.6

0.05

P

*

0.55

G

TABLE 2-7. Total mist-net captures and capture ratesa for migratory bird species in coffee plantations and natural forest during winter in El Salvador.

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4 0 13 1 0 6 98

0.4 0.0 1.2 0.1 0.0 0.6 9.0

4 0 8 1 0 6 68

Coffee plantations Rate Independent (birds 100 capture Captures net-hrs-1) eventsb 37 1 7 2 1 22 324

0.8 0.02 0.2 0.04 0.02 0.5 7.1

24 1 4 2 1 17 248

Natural forest Rate Independent (birds 100 capture -1 eventsb Captures net-hrs )

> 0.05 0.0008 > 0.05 >0.05

* 0.62 1.01

P 0.47

G

Capture effort was 1088 net-hrs in coffee plantations and 4562 net-hrs in natural forest. For “Independent capture events,” pairs or groups of conspecifics captured in the same net or group of nets during the same net run are treated as a singled individual, in order to maintain independence of capture data. These adjusted captures were used for statistical tests. * When sample size was 2 km from major natural forests and placed 5-ha coffee plots within farms >21 ha in size. Historical factors may also contribute to variation in bird abundances in coffee plantations, independent of present-day habitat characteristics. A farm recently converted from natural forest to coffee may not have experienced complete ecosystem decay and may still contain elements of the natural forest bird community that have disappeared at older farms (Lovejoy et al. 1986, Brooks et al. 1999). All of our farmed study sites had been farmed for much longer than several generations of migratory passerine birds, so we doubt this factor was important. The presence of windbreaks in some of the coffee plantations may present an additional source of bias. Windbreaks consisted of dense rows of heavily pruned

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trees, generally 6–8 m tall. Their inclusion in characterization of habitat greatly inflated tree density and tree basal area, and deflated structural diversity within plantations. Biologically, it was not clear whether windbreaks should have been included in habitat calculations or not—on one hand, they were trees, but on the other they did not resemble natural forest elements and were part of the agricultural stratum, as were the coffee bushes themselves (which were not considered in any habitat variable). Analyses with and without windbreaks produced similar results, suggesting that the results are robust to differing assumptions. For comparisons of bird abundances across habitats (natural forest vs. coffee), differences in detectability added an important bias (Thompson 2002). Habitat structure influences capture rates in mist nets: canopy feeding species may be caught in ground-level nets when the canopy is near the ground (as in some coffee plantations), causing relatively higher capture rates even though the species may be most abundant in natural forest with a higher canopy (Remsen and Good 1996). This structural difference between habitats may explain higher captures of Warbling Vireos and other migratory species in coffee plantations. Similarly, easier viewing conditions in the more open coffee plantations may lead to more frequent observations for some species than in the denser forest habitats, especially in the nonbreeding season when few birds vocalize (Chapter 1; Komar, in press). These factors should lead to a general bias in abundance favoring coffee plantations over natural forest, and could explain the weak positive correlation of migrant abundance (all species combined) with the disturbance index.

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A bias that may violate the assumption of independence in analyses of observations and mist-net captures is the tendency for birds to form mixed species flocks during the non-breeding season. Mixed-species flocks could inflate observation rates or capture rates in habitats where the behavior is more prevalent. Mixed-species flocking is more common in natural forest than in coffee plantations in the Dominican Republic (Latta and Wunderle 1996) and in Panama (Roberts et al. 2000a, Pomara et al. 2003). If effects of mixed species flocks could be removed, the relative rates of independent observations or captures in natural forest would probably be reduced more so than in coffee. We observed and captured migratory birds (as a group) more frequently in coffee plantations than in natural forest. For mist-netting results, the difference was not significant when all putatively independent captures were combined. Since biases caused by mixed-species flocks are more likely to inflate abundance estimates for birds in natural forest, we consider our results (higher abundance for migrants in coffee) to be conservative. Assuming that higher abundances of migratory birds in coffee than in forest are real, it is interesting to consider why. Migrants may be more abundant in coffee for a variety of reasons, including ecological adaptation and avoidance of competition with resident birds. Most migrants in this study were generalists that fed on diverse food resources, including insects, fruits, seeds, and nectar. Some of these food resources are abundant in coffee plantations, especially in the dry season, when dominant canopy trees are flowering or fruiting. Migrants may concentrate in coffee plantations in response to abundant food resources (Johnson and Sherry 2001), or in

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response to ecological niches not saturated by resident species (Wunderle and Latta 1998). Higher species richness of migratory birds in coffee may be due to general habitat preferences and higher abundances in coffee, or could also be explained by the overall landscape of the study, in which coffee area (>60,000 ha) is much greater than forest area ( 0.05). The abundances noted herein may be influenced by greater detectability (increased sight lines) in plantations. Habitat characteristics varied widely across the disturbance gradient from natural forest plots to low-shade (“technified” sensu Rice and Ward 1996) coffee plantations. Natural forest plots had much greater tree abundance and basal area, canopy cover, tree richness, and tree height than the coffee plots (Table 3-2). Differences in canopy structure (i.e., variability in tree height) were less striking 120

between the two habitat types, and not significantly different (t = -1.62, df = 27, P = 0.103). Some coffee plots included rows or grids of tightly pruned trees that served as windbreaks. Including these trees as part of the shade tree community led to higher mean tree basal area and tree density (Table 3-2). Natural forest sites scored at one end of the first PCA axis while the most intervened (technified) coffee sites scored at the opposite end (Fig. 3-1); I thus considered the scores on PC1 as an index of forest disturbance. Of 63 bird species analyzed, 16 were forest birds with mean abundances significantly negatively correlated to the habitat disturbance index (Table 3-3). This group of “disturbancesensitive” species included a toucan, a trogon, a woodcreeper, flycatchers, a manakin, wrens, a warbler, and a ground-sparrow. All are at least occasionally found in coffee plantations far from natural forest. The remaining 47 species analyzed either had insignificant regression slopes (36 species, classified as generalists, insensitive to disturbance) or significantly positive regression slopes (11 species, favoring disturbance). The species that favored disturbance were relatively rare or absent in natural forests, and included a woodpecker, a magpie-jay, wrens, a robin, a tanager, a goldfinch, a seedeater, an oriole, and a blackbird. Of the 35 species not analyzed (mostly too rare), 10 were found exclusively in natural forest plots. The 16 disturbance-sensitive forest bird species can be used as an indicator of conservation value of habitat characteristics of differing coffee production systems. The summed standardized mean abundances and richness of these species were highly sensitive to habitat disturbance (Fig. 3-2). For this analysis, I used the habitat

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Second Component

5 4 3 2 1 0 -1 -2 -3 -4 0

1

2

3

4

5

6

7

8

9

First Component (Index)

FIGURE 3-1. Score plots of principal components analysis of habitat variables measured in coffee and natural forest sites. The first component describes variation in disturbance level across the study sites. Natural forest (relatively undisturbed) plots scored towards the left end of the axis (solid dots), while highly altered coffee plantations scored towards the right end of the axis (open circles). The axis is reversed for ease of interpretation. The plot reflects treating windbreak trees as canopy trees; a plot with windbreaks ignored is similar.

disturbance index calculated without windbreaks, since most sensitive species were more highly correlated to this index than that including windbreaks (Table 3-3). The habitat disturbance index explained 71% of the variance in the summed abundances from the 29 study plots (F1,27 = 67.22, P < 0.001), and 65% of the variance in richness of habitat-sensitive species (F1,27 = 51.10, P < 0.001). The latter relationship is the more useful of the two relationships, because predicted species richness is more easily related to data collected in the field. Summed standardized mean abundance would be difficult to translate into a predicted abundance or density of birds, because of differing scales of abundance for different species. 122

TABLE 3-3. ANOVA tests (df = 1, 27) of regression slopes for abundances of birds regressed against the habitat disturbance index (with and without windbreaks treated as shade trees) across a disturbance gradient in natural forest and coffee plantations. The results of these tests (and directions of their slopes) dictated the classification of species as disturbance-sensitive, generalist, or favoring disturbance. Response variable (Species) 16 Disturbance-sensitive species Aulacorhynchus prasinus Catharus aurantiirostris Chiroxiphia linearis Cyanocompsa parellina Euthlypis lachrymosa Hylophilus decurtatus Melozone leucotis Mionectes oleagineus Myiarchus tuberculifer Myiopagis viridicata Oncostoma cinereigulare Thryothorus maculipectus T. rufalbus Tolmomyias sulphurescens Trogon elegans Xiphorynchus flavigaster 36 Generalist (non-sensitive) species Amazilia beryllina A. rutila Asturina nitida Basileuterus rufifrons Brotogeris jugularis Chlorostilbon canivetii Crypturellus cinnamomeus Cyanerpes cyaneus Cyanocorax melanocyaneus Cyclarhis gujanensis Dactylortyx thoracicus Dendrortyx leucophrys Dryocopus lineatus Eumomota superciliosa Euphonia affinis E. hirundinacea Glaucidium brasilianum Icterus gularis I. maculialatus I. pectoralis

Sites Reported Windbreaks included Windbreaks excluded (n) sensitivity* r2 F P r2 F P 10 7 7 5 10 8 5 3 20 3 3 13 11 11 12 7

M L M M M M M M L M L M M M M M

0.21 0.39 0.54 0.67 0.41 0.50 0.22 0.19 0.19 0.12 0.30 0.58 0.70 0.44 0.43 0.30

7.19 17.36 31.92 53.75 18.47 27.37 7.62 6.50 6.15 3.54 11.57 37.87 63.89 21.45 20.58 11.80

0.012 0.000 0.000 0.000 0.000 0.000 0.010 0.017 0.020 0.071 0.002 0.000 0.000 0.000 0.000 0.002

0.23 0.34 0.57 0.69 0.43 0.50 0.20 0.16 0.17 0.10 0.33 0.53 0.71 0.43 0.45 0.30

8.02 13.97 35.23 59.33 20.11 26.45 6.74 5.20 5.34 3.15 13.34 30.75 65.58 20.20 22.29 11.39

0.009 0.001 0.000 0.000 0.000 0.000 0.015 0.031 0.029 0.087 0.001 0.000 0.000 0.000 0.000 0.002

26 8 3 28 4 7 5 8 9 6 6 5 6 15 14 13 12 9 4 4

M L M L L? L M L M L H M L L L L L M M M

0.03 0.00 0.00 0.01 0.04 0.07 0.01 0.00 0.05 0.08 0.02 0.00 0.09 0.04 0.07 0.08 0.05 0.05 0.00 0.07

0.82 0.00 0.01 0.18 1.00 1.89 0.28 0.03 1.40 2.28 0.47 0.01 2.53 1.21 2.00 2.20 1.47 1.40 0.07 2.00

0.374 0.945 0.906 0.678 0.327 0.180 0.604 0.859 0.247 0.142 0.501 0.904 0.124 0.281 0.169 0.149 0.236 0.248 0.800 0.168

0.02 0.00 0.00 0.01 0.03 0.07 0.01 0.00 0.04 0.07 0.01 0.00 0.08 0.05 0.08 0.07 0.05 0.04 0.00 0.08

0.47 0.01 0.02 0.31 0.94 1.97 0.16 0.03 1.20 2.10 0.28 0.11 2.37 1.45 2.40 1.99 1.53 1.25 0.07 2.37

0.497 0.910 0.893 0.580 0.340 0.171 0.694 0.855 0.283 0.159 0.598 0.742 0.135 0.239 0.133 0.170 0.227 0.274 0.789 0.135

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Table 3-3, continued. Response variable (Species) Leptotila verreauxi Megarynchus pitangua Molothrus aeneus Momotus momota Myiodynastes luteiventris Myiozetetes similis Patagioenas flavirostris Piaya cayana Piculus rubiginosus Pteroglossus torquatus Quiscalus mexicanus Thryothorus modestus Tityra semifasciata Trogon violaceus Vireo flavoviridis Zenaida asiatica 11 Species favoring disturbance Calocitta formosa Campylorhynchus rufinucha Carduelis psaltria Dives dives Icterus pustulatus Melanerpes aurifrons Saltator atriceps Thraupis abbas Tiaris olivacea Troglodytes aedon Turdus grayi

Sites Reported Windbreaks included (n) sensitivity* r2 F P 25 L 0.07 1.90 0.179 20 L 0.02 0.59 0.448 7 L 0.07 2.11 0.158 27 M 0.03 0.93 0.344 8 L 0.06 1.84 0.186 3 L 0.00 0.00 0.927 21 M 0.01 0.39 0.536 28 L 0.01 0.28 0.603 28 L 0.06 1.62 0.213 3 M 0.04 1.05 0.314 4 L 0.02 0.55 0.466 16 L 0.01 0.28 0.600 20 M 0.04 1.02 0.322 3 M 0.03 0.69 0.412 14 L 0.00 0.00 0.969 12 L 0.06 1.72 0.201

22 22 3 21 26 23 25 18 3 19 27

M L L L L L M L L L L

0.24 0.18 0.11 0.15 0.25 0.29 0.14 0.20 0.12 0.35 0.30

8.32 5.94 3.35 4.90 9.05 11.08 4.45 6.91 3.56 14.32 11.74

0.008 0.022 0.078 0.036 0.006 0.003 0.044 0.014 0.070 0.001 0.002

Windbreaks excluded r2 F P 0.06 1.67 0.207 0.03 0.83 0.371 0.06 1.79 0.192 0.04 1.21 0.282 0.07 1.88 0.181 0.00 0.02 0.895 0.01 0.35 0.557 0.01 0.23 0.634 0.07 2.05 0.164 0.04 1.16 0.292 0.02 0.42 0.522 0.01 0.35 0.559 0.03 0.93 0.344 0.03 0.75 0.395 0.00 0.00 0.970 0.05 1.55 0.223

0.23 0.21 0.14 0.17 0.29 0.29 0.15 0.22 0.14 0.38 0.29

8.12 7.16 4.37 5.45 10.82 11.17 4.68 7.52 4.48 16.60 10.97

0.008 0.013 0.046 0.027 0.003 0.002 0.040 0.011 0.044 0.000 0.003

* Reported sensitivity to habitat disturbance was subjectively determined by Stotz et al. (1996): H = High, M = Medium, L = Low.

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Combined Abundance

100

R2 = 0.71

50

0 95% CI 95% PI

0

1

2

3

4

5

6

7

8

9

10

Habitat Disturbance Index

Species Richness

20

R2 = 0.65

10

0 95% CI 95% PI

0

1

2

3

4

5

6

7

8

9

10

Habitat Disturbance Index

FIGURE 3-2. A group of 16 bird species individually sensitive to habitat disturbance in the coffee growing region of El Salvador can be combined to function as an indicator representing forest species of conservation concern. The top graph shows the response of summed standardized mean abundances to habitat disturbance, the bottom graph species richness within the indicator group. Solid dots represent forest plots; open circles represent coffee plots.

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When the richness of disturbance-sensitive species was regressed against canopy cover alone, the resulting linear model explained 66% of variation in bird species richness. A quadratic regression model provided a better fit, explaining 72% of variation (r2 =0.715, F2,26 = 32.64, P < 0.001): S = 1.666 - 0.1018 C + 0.00241 C2 where C is percent canopy cover. This model predicts richness of these 16 species at a typical natural forest site (93% canopy cover) to be 13 species. Figure 3-3a presents this model with species richness converted to a scale of “% forest birds conserved” where 100% represents 13 indicator species found in a 5-ha plot. This conversion permits application of the equation to other areas where the disturbance-sensitive forest-bird communities may differ in richness. The linear model for bird species richness regressed on tree species richness explained 65% of bird species richness variation (F1,27 = 49.47, P < 0.001). The equation is: S = -0.3054 + 0.1754 T where T is tree species richness. Although a polynomial regression model provided a better fit, explaining 71% of bird richness variation, it was less practical because it predicted >1 forest bird species even when tree species richness was zero. As with the previous model, I converted the response variable (species richness) into a proportion of forest birds conserved, for broad applicability (Fig. 3-3b).

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% Forest Birds Conserved

(a)

100 50

0 95% CI 95% PI

20

30

40

50

60

70

80

90

100

(b)

% Forest Birds Conserved

% Canopy Cover

100 50 0 95% CI 95% PI

0

10 20 30 40 50 60 70 80 90 100

(c)

% Forest Birds Conserved

Tree Richness (Spp. in 0.5 ha)

100 50

0

95% CI 95% PI

0

10 20 30 40 50 60 70 80 90 100 Emergent Trees (per 0.5 ha)

FIGURE 3-3. Prediction models for the conservation of disturbance-sensitive forest birds in coffee plantations, based on (a) canopy cover, (b) tree species richness, and (c) emergent trees. The response variable, richness of forest birds, has been converted to a proportion of forest bird species conserved, to generalize the scale for any coffee bird community.

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The linear relationship between species richness and abundances of emergent trees was weak (43% of variation explained). A quadratic regression model (Fig. 33c), was: S = 2.026 + 0.3619 E - 0.00266 E2 where E is abundance of emergent trees. This model explains 55% of variation in the response variable, and was highly significant (F2,26 = 16.14, P < 0.001). Are the regression equations presented above useful for predicting species richness of disturbance-sensitive birds in coffee plantations? The F-ratios for each of the three equations are >4 times the F-ratios required for a P-value of 0.05, and therefore meet the Box–Wetz criterion for identifying a useful prediction model (Draper and Smith 1998). The F-ratios are larger by factors of 9.7, 11.8, and 4.8, respectively. The third equation (for emergent trees) barely meets the criterion. No multiple linear regression model explained bird species richness better than the polynomial regression equation for canopy cover presented above. The only model selected by stepwise regression combined canopy cover and tree species richness to explain 68% of variation in bird species richness. Adding emergent tree abundance to the model did not increase its explanatory power and reduced the Fratio.

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DISCUSSION This study confirms that at least 16 species of disturbance-sensitive forest birds are found in shaded coffee plantations of southwestern El Salvador. They tend to be relatively rare in plantations, and many plantations meeting certification criteria may not be attractive to these species. It remains to be investigated whether these species are maintaining sustainable populations in coffee farms, or whether their use of farms (potentially only as movement corridors or occasional feeding areas) enhances the sustainability of populations in nearby local forest habitats. Additional disturbancesensitive species may use the plantations rarely, seasonally, or as movement corridors, but were not detected during the present study. Previous studies of resident birds in coffee plantations have tended to look at overall bird communities, comparing bird species richness in plantations to natural forest, or among plantation types (e.g., Aguilar-Ortiz 1982, Calvo and Blake 1998). The present study demonstrates the importance of discerning which species in a community are of conservation concern and/or sensitive to changes in habitat variables. Management practices within coffee plantations attract some species while repelling others, so overall species richness hides finer scale changes in communities. Generalist species present, not sensitive to the factors evaluated, simply serve to add noise to the analysis, and can mask loss of sensitive species (Canaday 1996). To measure effects of a habitat variable on bird diversity (and its conservation), only species sensitive in one direction should be used as indicators. This concept is illustrated in Figure 3-4.

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Combined Abundance

90 80

16 species decrease

70

r = 0.75

2

60 36 species not sensitive

50

2

r = 0.03

40 30

11 species increase

20

r = 0.54

2

10 0 -10 0

2

Natural Forest

4

6

Shaded Coffee

8

10

Technified Coffee

Forest Disturbance Index FIGURE 3-4. Trend lines for summed standardized mean abundances of three classes of avian communities coexisting in the coffee growing region of the Sierra de Apaneca, El Salvador. The solid black line represents 16 disturbance sensitive species (most common in natural forest); the dotted line represents 36 generalist species insensitive to habitat disturbance; the dashed line represents 11 species that increased with disturbance, being most common in low-shade coffee plantations.

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Determination of which species are habitat sensitive should be carried out locally and objectively. Previous studies of birds in coffee (Petit and Petit 2003, Tejeda-Cruz and Sutherland 2004) used a classification for habitat sensitivity generated by Stotz et al. (1996), expert ornithologists with experience in a variety of Neotropical locations who subjectively assigned sensitivity values to all Neotropical breeding bird species. However, that source classified several species differently than I have found in my study area. Thirteen of 16 disturbance-sensitive species identified by the present study were classified as moderately sensitive by Stotz et al. (1996), but the remaining three (Oncostoma cinereigulare, Myiarchus tuberculifer, Catharus aurantiirostris) were listed as only of low sensitivity by those authors. In contrast, Stotz et al. (1996) listed 16 species as moderately or highly disturbance-sensitive that I found to be either insensitive to habitat variation (14 species) or favoring disturbance (2 species). These species are indicated in Table 3-3. None of the disturbance-sensitive species in my study area was listed as highly sensitive by Stotz et al. (1996), which perhaps is not surprising, given that most field sites were disturbed plantations, and the natural forest sites have also been disturbed by fragmentation. It would be unrealistic to expect any kind of coffee plantation to be adequate habitat for a highly-sensitive forest species.

IMPLICATIONS FOR CERTIFICATION OF SHADE COFFEE FARMS

The relationships estimated herein, for effects of canopy cover and tree species richness on a group of disturbance-sensitive indicator bird species, imply that coffee

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plantations that just met ecological certification criteria (40% canopy cover, 12 tree species ha-1) likely had 25% of the production area, in which case canopy characteristics need not be evaluated for certification, and (3) habitat external to the farm conserved as mitigation. In the last case, the farmer would conserve a larger area, suggested to be equivalent to 50% or more of the farm’s production area, in a nature reserve within the same geographic region.

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INTRODUCTION Ecological certification systems for coffee plantations were developed in the 1990s, initially as an effort to improve habitat for migratory and resident birds in highly deforested Neotropical mountain ranges. The focus of this dissertation (Chapters 1–3) was to investigate the role of shaded coffee plantations, especially those that qualify for ecological certification, in bird conservation. As was shown in Chapter 1 (Komar, in press), such a role was assumed by the organizations that developed certification systems. Although numerous field studies in coffee plantations since the early 1990s have shed much light on ecology of birds and other wildlife, they have nonetheless shed little light on the bird conservation role of coffee plantations. The assumption that shaded coffee plantations were beneficial for conservation of migratory birds has yet to be strongly supported by field studies. I have shown that most migratory birds are generalists that were not sensitive to habitat characteristics traditionally used for certification, such as canopy cover and tree species richness (Chapter 2). Some research has even suggested that migratory bird abundance and diversity is high in sun coffee plantations with no shade (Wunderle and Latta 1996). A few migratory bird species are considered of global or continental conservation concern (Rich et al. 2004), but those species are mostly habitat specialists rarely found in coffee plantations. Overall, coffee plantations appear to play little role, if any, in migratory bird conservation. In Chapter 3, I examined abundance and richness of resident birds in coffee plantations. By focusing on just species that were sensitive to disturbance, I

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characterized relationships between disturbance-sensitive bird species richness and levels of canopy cover, tree richness, and emergent tree density in coffee plantations. These relationships demonstrated that plantations that meet current certification criteria benefit only very few disturbance-sensitive bird species, far fewer than equivalent-sized plots of natural forests. Furthermore, adjustments to criteria required to markedly improve bird conservation are likely to be economically impractical. In this chapter, I review ecological certification standards related to canopy cover and ecosystem conservation within coffee plantations. I identify problems in application of those standards, and discuss possible solutions. As a result, I propose a new system for evaluating wildlife habitat in the plantations, taking into account the potential value of even small forest fragments or reserves that could play a direct role in conservation of biodiversity, as gene banks, stepping stones in biological corridors, and habitat for maintenance of disturbance-sensitive wildlife populations.

METHODS Data on canopy cover and tree species richness were collected at 10 coffee plantations in El Salvador, in conjunction with the studies presented in Chapters 2 and 3; detailed methods for the collection of those data are presented in Chapter 2. The plantations were selected for variation in canopy cover, such that they spanned the gradient of canopy characteristics, from low to high shade. I critically reviewed five sets of existing coffee certification criteria used for ecological coffee certification (Table 4-1). The recommendations developed herein

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and evaluations of some of the difficulties with coffee certification were discussed with persons (listed in the Acknowledgments) actively involved in coffee certification in several Latin American countries, through the Sustainable Agriculture Network (SAN).

TABLE 4-1. Existing ecological certification systems for Latin American coffee plantations in 2005. Certification system and document title Normas para la Producción de Café Sustentable en México (Consejo Civil de Café Sostenible en México) Normas e Indicadoras para la Certificación del Cultivo de Café (Rainforest Alliance / Sustainable Agriculture Network) Norma con Indicadores para Agricultura Sostenible – Red de Agricultura Sostenible. Criterios e Indicadores Adicionales para la Producción de Café (Rainforest Alliance / Sustainable Agriculture Network)

Document date No date, recd. June 2003 May 2002

November 2005

Líneas Guías de Conservación para la Producción Cafetera en Colombia (Federación Nacional de Cafeteros de Colombia and Conservation International)

March 2003

Shade Management Criteria for “Bird Friendly®” Coffee (Smithsonian Migratory Bird Center, Washington, D.C.) [http://natzoo.si.edu/ConservationAndScience/MigratoryBirds/ Coffee/Certification/criteria.cfm]

Downloaded 16 September 2003 and again 2 January 2006.

NKG Sustainability Index: 100 Points for the Assessment of Sustainability in Coffee Production (Neumann Kaffee Gruppe)

Undated draft, recd. 14 June 2003

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DIFFICULTIES WITH EXISTING CERTIFICATION CRITERIA The certification systems reviewed were generally complex (Table 4-2) and all presented difficulties with their interpretation or application. For example, standards set for Mexico by the Consejo Civil de Café Sostenible en México (CCCSM, undated) required ≥50% native tree species in the shade canopy, but did not specify if ≥50% of trees must be of native species or if ≥50% of species must be native. Guidelines for Colombia (CI 2003) suggested that farms located within landscapes that are extensively forested and/or have adequate regional conservation plans could qualify as ecologically sustainable, even when the farmers themselves had no role in improving such landscapes. In fact, such farms may have contributed to landscape degradation. The Smithsonian Migratory Bird Center (SMBC) guidelines (Greenberg and Rice undated), which required that a farm also be certified organic, failed to specify an area requirement for their standard of 10 tree species, and recommended that tree pruning be carried out during the avian breeding season, apparently to improve benefits for migratory birds, but to the possible detriment of resident birds. The SMBC guidelines recommended that ≥40% of shade be provided by trees above and below the mid-canopy. Unfortunately, calculating proportions of shade by trees from different strata is extremely difficult, if not impossible. The NKG standards (Neumann Kaffee Gruppe undated) proposed that tree species richness be an indicator for biodiversity on a farm, but failed to indicate a standard measurement area useful for comparison.

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TABLE 4-2. Standards used for ecological certification of coffee plantations. Standard Canopy characteristics Canopy cover after tree pruning Density of shade trees (ha-1) Native tree species Density of native tree species (ha-1) Tree species other than Inga spp. on the farm

México/ CCCSM

Rainforest Alliance/ SAN2

Colombia/ CI

SMBC Bird Friendly

NKG

≥40%

≥40%

Determined locally

≥40%

≥40%

1

≥70

≥40

≥50% ≥10

Ambigu ous ≥12

Determined locally

Evergreen (nondeciduous) tree abundance Congeneric trees Conspecific trees

≥70% ≤60% ≤35%

Canopy layers among shade trees Emergent tree abundance

≥2

Emergent tree height Canopy height average Cutting emergent trees restricted No pruning of trees flowering or seeding No clearing epiphytes or hemi-epiphytes from shade trees

≥15 m ≥12 m Yes

NA (just “mixed tree canopy”) ≥2

≤30% ≥3 ≥20% of shade cover

≥20%

Yes

≥2 10 (each >1% of trees present) ≥3, max. 50% of one species Not explicit, but high3 ≤60%

Number of species of Inga used to provide majority of shade

≥12 m Only up to 50%

Ambiguous Yes

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≥50%

Table 4-2, continued. Standard

México/ CCCSM 1

Rainforest Alliance/ SAN2

Colombia/ CI

SMBC Bird Friendly

NKG

20% of shade cover

Abundance of trees, lowest stratum (below mid-stratum) Other vegetation characteristics Protection of river and stream borders

≥10 m each side (5 m for streams)

Reforest roadsides

Dead trunks maintained Farmworker behavior No hunting in general No hunting globally threatened species

Yes

≥5 m on each side

Connect natural patches with corridors of natural vegetation Remnants of existing ecosystems marked and conserved Natural vegetation barriers protect human use areas Proportion of property with natural vegetation Herbaceous cover height in production area

≥10 m each side (50 m where slope is >30%)

≥10 m each side (5 m for streams) Yes

Yes (corrid ors ≥10 m wide)

Yes

Yes

≥5 m each side

Yes

Yes

Yes Yes ≥20%

≥5 cm

Cover promoted, no minimum.

Yes

Yes

Yes Implicit

Yes

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Implicit

Table 4-2, continued. Standard No hunting nationally threatened species No hunting CITESlisted species No extraction of plants General farm administration Natural vegetation age protected from farming expansion Transition period Límit on annual cleaning Establish strategies for protecting threatened species Plan for forest fire control Reforest or recover areas not fit for agriculture

México/ CCCSM

Rainforest Alliance/ SAN2

Colombia/ CI

Yes

Ambiguous

Yes

Implicit

Yes

1

SMBC Bird Friendly

NKG

Yes

20 years

15 years

Up to 36 months 3 Yes Yes

Yes Yes

Yes

Sources listed in Table 4-1. 1 Includes standards for natural resources conservation (including wildlife), but not for agroecosystem management, which do not deal with shade canopy. 2 Based on Rainforest Alliance (2002). 3 The SMBC standards do not specify the percentage of evergreen (nondeciduous) trees but mention that the majority of trees should be non-deciduous, even though deciduous trees (three genera are mentioned) are acceptable if they do not form >5% of shade cover.

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One of the most complex systems and also most widely applied is the SAN system for Rainforest Alliance Certified coffee. I present in greater detail below an analysis of this system and related difficulties. Ecological standards applied in coffee certification through 2005 by the SAN include canopy cover of ≥40% (after pruning), ≥70 shade trees ha-1, ≥12 native tree species ha-1, and ≥20% abundance of emergent trees (Rainforest Alliance 2002). Some of the difficulties associated with these criteria for achieving wildlife conservation on coffee farms involve the practicality for farm auditors to evaluate the indicators (canopy cover, tree density and richness) during relatively brief farm visits. The standards were focused on characteristics of the shade canopy, and did not reflect characteristics of natural habitat preservation (under the farmer’s control) that may occur within farms. At the end of 2005, the SAN revised its standards and shifted focus from shade towards natural ecosystems (Rainforest Alliance 2005), but maintained the criteria discussed in this paper, with the exception of presence of 20% emergent trees. Presence of emergent trees is still included as an indicator for the criterion of providing a two-layered canopy over the coffee plants, but a minimum quantity of emergent trees is no longer stated. Difficulties in the logistics of determining a farm’s minimum average canopy cover after tree pruning (usually an annual practice) have led to auditors’ practice of simply estimating canopy cover without actually taking any measurements. The problem lies in the impracticality of auditors visiting all certified farms (and farms requesting certification) just after pruning to measure shade. Lack of actual measurements permits room for large errors. Taking enough measurements at a single

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farm to avoid large errors is a process that requires several hours, which frequently are not available to the farm auditor on regularly scheduled farm visits. An appropriate method for calculating canopy cover would be to take densiometer readings at ≥150 points randomly distributed throughout the farm (Lemmon 1956, Fig. 4-1). If coffee plants are very high (on some farms they reach 3 or even 4 m), obtaining densiometer readings can be difficult since the densiometer should be held 90 80 70

90 80 70

60 50

60 50 40

40 30

30

20 10 0

20 10 0 1

51

101

151

1

51

101

151

1

51

101

151

90 80 70

90 80 70 60

60 50

50

40 30

40 30 20

20 10 0

10 0 1

51

101

151

FIGURE 4-1. Examples of evaluations of canopy cover (Y axis) using cumulative estimates derived from 180 densiometer measurements (X axis), for shaded coffee plantations in El Salvador with 45%, 29%, 60%, and 25% canopy cover. These graphs suggest that 150 measurements would have been sufficient.

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level with tops of coffee shrubs. Partly because of the practical problems of measuring canopy cover, the SAN requires a density of ≥70 trees ha-1 on farms it certifies. Although counting trees in a 1-ha plot (or more appropriately, in smaller plots randomly distributed throughout the farm) is not complicated, the standard of 70 trees ha-1 is problematic because of the great variation among tree sizes used in different coffee production systems. Nonetheless, in a sample of shaded plantations of El Salvador, 70 trees ha-1 corresponded almost exactly with 40% canopy cover (95% CI, 32–48%), based on 24 study plots selected to include a range of shaded coffee management systems (Fig. 42). Important to note, however, is the relatively low correlation between tree density and canopy cover, as variation in tree density (log-transformed) only explained 43%

Canopy Cover (%)

of variation in canopy cover. The F-ratio for this relationship (F1,22 = 16.7) was