DOI: 10.5061/dryad.f7m0cfz41
title: Bird and vegetation diversity in Chaco forests under different cattle management practices

description: Birds play key roles in forest dynamics, favoring the resilience of
 forests to cattle ranching. Generalist species may benefit from changes in
 the vegetation structure caused by cattle grazing while specialist species
 are usually negatively affected. Therefore, studying changes in taxonomic
 and functional bird diversity can provide valuable information in order to
 propose sustainable cattle management practices. Here, we study the
 influence of different cattle management practices (Cattle Exclusion: FCE;
 Continuous grazing: FCG; Rotational grazing: FRG; Seasonal grazing: FSG)
 on the understory vegetation structure, and the bird taxonomic and
 functional diversity in humid Chaco forests of Argentina. Forests under
 grazing had an open (FCG) or semi-open (FRG and FSG) understory, whereas
 FCE presented a closed understory with higher plant richness. Generalized
 linear models revealed a decrease in bird richness and abundance under
 most cattle management practices compared to FCE. However, FRG was most
 similar to FCE in terms of vegetation structure and showed no differences
 in bird richness. FCE presented the lowest values of functional diversity
 while FCG and FRG showed the highest values. A fourth-corner analysis
 showed that FCE was associated with insectivorous species which forage and
 nest in the shrub layer, reflecting a possible loss of ecosystem services
 in forests with cattle grazing.  We propose FRG as the most
 appropriate cattle management option and the least detrimental to bird
 assemblages. However, maintaining protected areas that exclude cattle
 ranching activities will be key to striking a balance between the
 conservation of most specialist species and beef production.
description: <strong>Experimental design and surveys of birds and
 vegetation</strong> We conducted surveys on
 ranches and at the INTA Experimental Station located in the Departamento
 Presidencia Plaza, Chaco province, Argentina (Figure 1). Crops and
 livestock, as well as livestock raising in a traditional continuous
 grazing regime, are the main activities in an extensive agricultural
 landscape composed of forest fragments. Sampling was conducted in forest
 patches under different cattle management practices:<strong>
 </strong> (1) a control forest with cattle exclusion 
 (<strong>FCE</strong>) which consisted of a forest with
 81-year old permanent exclosures located in four large paddocks (in total
 200 ha) at the Estación Experimental INTA (26° 56′ S, 59° 45′ W); (2)
 forest with continuous grazing (<strong>FCG</strong>): cattle
 are left in five large paddocks, foraging in grassland and forest areas
 (in total 220 ha), which is the most widespread cattle management practice
 especially among small ranchers (Borrás et al. 2017); (3)<strong>
 </strong> forest with annual rotational grazing
 (<strong>FRG</strong>): it has 60 paddocks of two to three ha
 each,  where one to two days of intense grazing are carried out in each
 paddock followed by 45 to 60 days of rest for the vegetation to recover
 (in total 220 ha); and (4) forest with seasonal grazing
 (<strong>FSG</strong>), with cattle grazing in the forest only
 in winter, since it is the only season in which cattle have access to
 water, whereas the rest of the year cattle graze in grassland paddocks
 (Cattle are moved to the forest in winter to allow the grassland to
 recover; in total 100 ha). Twenty sampling sites were randomly selected
 for each cattle management practice. All cattle management practices were
 embedded in a similar matrix of forest alternating with grasslands and
 pastures thus any confounding effects related to matrix composition were
 minimized. In order to study the effects of these
 cattle management practices on the vegetation structure, a visual
 estimation of the cover percentage within each management practice was
 carried out at stations with a fixed radius of 20 m (Matteucci &
 Colma, 1982). At each station, the cover of “caraguatá” (dominant species
 of the herbaceous stratum: <em>Pseudananas macrodontes, Bromelia
 serra, </em>and <em>Aechmea distichantha</em>), shrub
 cover and tree cover were estimated, grouping the estimates in 10%
 intervals (0-10%, 11-20%, 21-30%, etc.). We used the classification guide
 of Ledesma et al. (2017) to identify the dominant species within each
 stratum. The understory plant species richness was calculated for each
 cattle management practice from presence and absence data of these
 species. Bird sampling points were separated from each
 other by at least 150 m in order to ensure independence of records and
 avoid double counting (Bibby et al., 2000). We used a handheld GPS (error
 ±5 m) to measure distances. Bird sampling was conducted during the
 breeding season, covering September to December, in 2017. The same
 observer (MC) sampled each point count and recorded all birds seen or
 heard within a 25 m radius of the survey point during a 10-min period
 (following Bibby et al., 2000) except for individuals flying over 20
 meters in height (Codesido & Bilenca, 2000; Codesido &
 Bilenca, 2004). The number of counts of individuals of each species was
 used as a proxy for abundance estimates.  Point counts were conducted
 during the four hours following sunrise, registering all birds from the
 moment of reaching the point. Birds flying away from the point count when
 the observer arrived were considered present at the count point (Hutto et
 al., 1986). Bird taxonomy followed Remsen et al. (2022).
 <strong>Selection of functional
 traits</strong> We selected 11 functional traits
 (see Table S1) related to the life history of the species and based on
 previous studies of functional diversity or responses to natural habitat
 replacement (Cofre et al., 2007; Corbelli et al., 2015; Feeley et al.,
 2007; Luck et al., 2013; Petchey & Gaston, 2006). The selected
 traits are relevant to understand how bird species may respond to
 environmental changes (Luck et al., 2013). We considered the following
 four groups of traits: <strong>1)</strong>
 <strong>Feeding traits:</strong> body weight, which is
 associated with metabolic rate, foraging behavior, longevity and territory
 size; foraging substrate, meaning where the species carry out their
 feeding activities and provides information on the sensitivity of species
 to the loss of different types of habitats that affect food availability;
 diet, which  indicates the place of the species in the food chain and the
 ecosystem services it provides;<strong> 2) Breeding
 traits:</strong> migratory status, which can influence large-scale
 nutrient cycling and the provision of services over large regions; nesting
 habitat, which provides information about the sensitivity of species to
 the loss of different types of habitats that affect the availability of
 nesting sites; clutch size, species with low reproductive rates tend to be
 less resilient to habitat changes than those species with higher rates;
 <strong>3) Habitat traits:</strong> number of habitats used,
 generalist species tend to be more resilient to habitat changes than
 specialist species as they can use different types of habitats; main
 habitat, primary habitat where the species can be found, including
 anthropic habitats; <strong>4) Vulnerability traits:</strong>
 abundance, population size is strongly related to the risk of extinction
 of the species; distribution, the species with a restricted distribution
 are at greater risk of extinction than those with wider distributions; 
 sensitivity to human disturbance, meaning how species respond to habitat
 modification, replacement and contamination by anthropogenic processes.
 All traits were categorical variables, and each category was binary
 (present or absent for each species). Traits with multiple states were
 subdivided, and each state was treated as a single binary trait. For
 example, if a species feeds primarily on fruits and seeds, we assigned 1
 to both "insectivore" and "frugivore", and 0 to all
 other feeding categories. All trait categories were mutually exclusive
 except "diet," "feeding substrate," and "nesting
 habitat." Table S1 lists the references from which trait information
 was taken for each species. <strong>Statistical
 analysis </strong> All analyses were performed
 using the R statistical software (R Core Team, 2022). The influence of the
 cattle management practices on understory vegetation species richness
 (response variable) was studied by testing a generalized linear model
 (GLM) with a one-factor Poisson distribution (management type factor with
 four levels). The "glmmTMB" function was used to generate the
 models and the "DHARMa" package (Hartig, 2021) was used to test
 the assumptions of these models.  To study the ordination of the sites
 based on the set of forest and understory species recorded and the
 coverage of the different strata we carried out a redundancy analysis
 (RDA). RDA is a direct ordination method that arranges the sites in
 relation to one or more continuous variables (axes), which are linear
 combinations of the original variables, to optimize the visualization of
 the data (Leps and Smilauer 2003). This analysis provides a plot showing
 how strongly and in which direction the vegetation variables are
 associated with each axis, and the location of the sites on the axes
 indicates how they are characterized in terms of these variables (Leps and
 Smilauer 2003). To study differences in bird taxonomic
 diversity among cattle management practices, we fit General Linear Models
 with Poisson distribution to species richness and abundance per site as
 response variables, and cattle management practice as the explanatory
 variable. The "glmmTMB" function was used to generate the models
 and the "DHARMa" package (Hartig, 2021) was used to test the
 assumptions of these models. <em>A posteriori</em> comparisons
 were performed using Tukey's test with the "glht" function
 in the multcomp package (Hothorn et al., 2008). An indicator species
 analysis (De Cáceres & Legendre, 2009) was used to identify the
 characteristic bird species for each cattle management practice. This
 analysis estimates an indicator value for each species based on its
 frequency and relative abundance. This value ranges from 0 (no
 association) to 100 (perfect association, i.e., the species was observed
 at all sites for a determined cattle management practice and absent from
 all sites of the different management conditions). We used the multipatt
 function of the "indicspecies" package and only those species
 with indicator values greater than 35 and significant (P ≤ 0.01) were
 taken into account (Codesido et al., 2013). This function also allows the
 evaluation of indicator species for combinations of cattle management
 practices as described in De Cáceres (2013). To
 estimate functional diversity, we used the multidimensional functional
 dispersion index (FDis) developed by Laliberté & Legendre (2010).
 FDis is the mean distance of individual species to the centroid of all
 species in a multidimensional trait space, this index takes into account
 both species relative abundances and their functional traits. FDis is not
 affected by species richness, it is not strongly influenced by outliers,
 it can include any number and type of traits, and it can be calculated
 with any measure of distance or dissimilarity (Anderson et al., 2006).
 Higher values for this index correspond to higher functional trait
 diversity (Anderson et al., 2006). To estimate FDis for each site, we
 first calculated the distance matrix between species from the original
 species-trait matrix, using the Jaccard index (vegdist function in the R
 package "VEGAN") since it is suitable for categorical data and
 omits double zeros (Legendre & Legendre, 1998). The calculation of
 the FDis index for each site was performed with the "FD" package
 using the distance matrix between species and the matrix of sites by
 species (Laliberté & Legendre, 2010). To study the differences in
 functional diversity between the management practices, a linear model was
 generated with the FDis value per site as the response variable and cattle
 management practice as the explanatory variable. After testing the
 assumptions of homoscedasticity and normality, an analysis of variance
 (Anova) and <em>a posteriori</em> comparisons were performed
 with the "emmeans" function. Finally, we
 analyzed associations between functional traits and management practices
 using a fourth-corner analysis (Brown et al., 2014), which tested for
 relationships between species traits and cattle management by comparing
 three matrices: sites-by-species, species-by-traits and sites-by-traits
 matrices. The significance is tested by a permutation procedure using
 model 6 (Brown et al., 2014). We performed separate analyses for each of
 the four trait groups. The sign of the correlation coefficients obtained
 with this analysis indicates whether the association between a site and a
 trait is positive or negative, and their value indicates the strength of
 the association. Differences were considered
 significant at P&lt;0.05 with the exception of the indicator species
 analysis (P&lt;0.01).
description: # Biotropica OpenData Haene et al. 2024
 This database contains
 information on bird diversity and vegetation structure in humid forests of
 the Chaco of Argentina. These data were used to study the influence of
 different cattle management practices (Cattle Exclusion: FCE; Continuous
 Grazing: FCG; Rotational Grazing: FRG; Seasonal Grazing: FSG) on
 understory vegetation structure and the taxonomic and functional diversity
 of birds. Sampling was conducted in forest patches under different cattle
 management practices: (1) a control forest with cattle exclusion 
 (**FCE**) which consisted of a forest with 81-year old permanent
 exclosures located in four large paddocks (in total 200 ha) at the
 Estación Experimental INTA (26° 56′ S, 59° 45′ W); (2) forest with
 continuous grazing (**FCG**): cattle are left in five large paddocks,
 foraging in grassland and forest areas (in total 220 ha), which is the
 most widespread cattle management practice especially among small ranchers
 (Borrás et al. 2017); (3)forest with annual rotational grazing (**FRG**):
 it has 60 paddocks of two to three ha each,  where one to two days of
 intense grazing are carried out in each paddock followed by 45 to 60 days
 of rest for the vegetation to recover (in total 220 ha); and (4) forest
 with seasonal grazing (**FSG**), with cattle grazing in the forest only in
 winter, since it is the only season in which cattle have access to water,
 whereas the rest of the year cattle graze in grassland paddocks (Cattle
 are moved to the forest in winter to allow the grassland to recover; in
 total 100 ha). Twenty sampling sites were randomly selected for each
 cattle management practice. All cattle management practices were embedded
 in a similar matrix of forest alternating with grasslands and pastures
 thus any confounding effects related to matrix composition were minimized.
 In order to study the effects of these cattle management practices on the
 vegetation structure, a visual estimation of the cover percentage within
 each management practice was carried out at stations with a fixed radius
 of 20 m. At each station, the cover of “caraguatá” (dominant species of
 the herbaceous stratum: Pseudananas macrodontes, Bromelia serra and
 *Aechmea distichantha*), shrub cover and tree cover were estimated,
 grouping the estimates in 10% intervals (0-10%, 11-20%, 21-30%, etc.). The
 understory plant species richness was calculated for each cattle
 management practice from presence and absence data of these species. Bird
 sampling points were separated from each other by at least 150 m in order
 to ensure independence of records and avoid double counting. We used a
 handheld GPS (error ±5 m) to measure distances. Bird sampling was
 conducted during the breeding season, covering September to December, in
 2017. The same observer (MC) sampled each point count and recorded all
 birds seen or heard within a 25 m radius of the survey point during a
 10-min period (following Bibby et al., 2000) except for individuals flying
 over 20 meters in height. The number of counts of individuals of each
 species was used as a proxy for abundance estimates.  Point counts were
 conducted during the four hours following sunrise, registering all birds
 from the moment of reaching the point. Birds flying away from the point
 count when the observer arrived were considered present at the count
 point. Forests under grazing had an open (FCG) or semi-open (FRG and FSG)
 understory, whereas FCE presented a closed understory with higher plant
 richness. Generalized linear models revealed a decrease in bird richness
 and abundance under most cattle management practices compared to FCE.
 However, FRG was most similar to FCE in terms of vegetation structure and
 showed no differences in bird richness. FCE presented the lowest values of
 functional diversity while FCG and FRG showed the highest values. A
 fourth-corner analysis showed that FCE was associated with insectivorous
 species which forage and nest in the shrub layer, reflecting a possible
 loss of ecosystem services in forests with cattle grazing.  We propose FRG
 as the most appropriate cattle management option and the least detrimental
 to bird assemblages. However, maintaining protected areas that exclude
 cattle ranching activities will be key to strike a balance between the
 conservation of most specialist species and beef production. ##
 Description of the data and file structure \ The first tab of the database
 contains information about bird species (columns) and their abundances by
 site (rows). It is indicated to which treatment each site belongs (FCE,
 FCG, FRG, and FSG). Species are abbreviated using the first letter of the
 genus and the first two letters of the specific name (see Supplementary
 Material). Empty cells indicate that no individuals were recorded. The
 second tab contains information on the incidence of plant species
 (columns), indicated by their common names, for each site (rows). To
 search for common names of the species mentioned search at
 The third
 tab contains information about the percentage of coverage of different
 plant strata (columns) for each site (rows). ##