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/lp/springer-journals/diversity-of-plants-and-mammals-as-indicators-of-the-effects-of-land-hF9alw6FSJ
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- Springer Journals
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- Copyright © The Author(s) 2021
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- 2197-5620
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- 10.1186/s40663-021-00348-2
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Abstract
Background: The ecological indicators are useful tools to determine the effects of human disturbances on woodland biodiversity. Nevertheless, ecological indicators not always responded in the same way to disturbances, and the responses can differ among taxa. In arid and semiarid woodlands, the use of deadwood associated with cattle raising can affect biodiversity and Nature’s contributions to people. Methods: Our study aimed to assess changes in taxonomic and functional diversity of two assemblages, plants and mammals, in Prosopis woodlands under different land management types: grazed woodlands and a protected area. For plants, changes in structural diversity were also analyzed. Prosopis trees under different land management types were selected and their deadwood characteristics were registered. Through live traps and camera traps, we obtained data on the presence-absence of mammals per tree to estimate diversity indices. For plants, we measured the abundance of vegetation by species and by cover type through the Line-Intercept Method to estimated diversity. Finally, we built generalized linear models to assess the responses of diversity of each assemblage to covariables concerning deadwood and different land management types. Results: We found that all diversity indeces for plants were either negatively affected by the presence of deadwood on the ground, or favored by its extraction. For mammals, removal of deadwood increased taxonomic diversity, while functional diversity increased with deadwood on the trees. Both structural diversity of plants and functional diversity of mammals were greater in grazed woodlands. Conclusions: The sustainable use of woodland resources is essential for the activities of rural communities. Our study results indicated that land management of grazed woodlands promoted the structural diversity of plant assemblages and the functional diversity of mammals. The presence of deadwood negatively affected plant diversity but it increased mammal functional diversity. It is advisable to maintain trees that preserve their wooden structure within the managed areas to promote the functional diversity of mammals, while trees with extraction from standing wood will favor the functional diversity of the plant assemblage. Understanding the effects of human disturbances can contribute to management for the conservation of woodlands diversity and Nature’s contributions to people. Keywords: Central Monte, Cattle raising, Deadwood extraction, Taxonomic diversity, Functional traits * Correspondence: cszymanski@mendoza-conicet.gob.ar Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales, CCT CONICET Mendoza, Av. Ruiz Leal s/n, Parque General San Martín, 5000 Mendoza, Argentina Facultad de Ciencias Agrarias, Universidad Nacional de Cuyo, Alte. Brown s/ n, Chacras de Coria, 5505 Mendoza, Argentina Full list of author information is available at the end of the article © The Author(s). 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. Szymañski et al. Forest Ecosystems (2021) 8:74 Page 2 of 15 Background resulting in a high functional redundance (Chillo et al. Land use change, such as land conversion for crops, live- 2017). Understanding the relationship between indica- stock raising, and urban settlements, is the main factor tors of taxonomic and functional diversity allows for affecting terrestrial ecosystems and the vital contribu- comprehending the effects of human use on community tions made by living nature to humanity, referred to as assembly and ecosystem functioning (Janeček et al. Nature’s contributions to people (NCP; Díaz et al. 2019). 2013). Nature’s regulating contributions include functional and In dry woodlands, trees are especially important be- structural features of organisms and ecosystems that cause they ameliorate the microenvironment under their change environmental conditions experienced by people canopy, improving conditions for plant and animal life and regulate the generation of material and non-material (Manning et al. 2006; López-Sánchez et al. 2016). In contributions. Nature’s material contributions to people some cases, they can also cause substantial costs to local are generally transformed and consumed when they are livelihoods and the environment when they are intro- experienced, for example, plants or animals are con- duced species and become invasive, such as the case of verted into materials for ornamental or shelter purposes, species of Prosopis genus (e.g. Rejmánek and Richardson food, or energy (Díaz et al. 2019). 2013; van Wilgen and Richardson 2014; Shackleton et al. In the framework of NCP, deadwood to use as 2015). However, in their natural distribution, Prosopis firewood is the main woodland material used by rural trees are key species from ecological and cultural points communities. Also, deadwood is a major component in of view (e.g. Kingsolver et al. 1977; Mares et al. 1977; maintaining the function and biodiversity of forest Moreno et al. 2018). Prosopis flexuosa is the main tree ecosystems because it decreases soil erosion, stores and conforming open woodlands in the Monte ecoregion, supplies nutrients and water to soil and plants, provides and it plays a key role in providing important NCP to a regeneration substrate for some plants, and offers rural communities, such as forage for livestock and fire- protection and food sites for organisms of several taxa wood (Alvarez and Villagra 2009). (Harmon et al. 1986; Mac Nally et al. 2001; Stoklosa In P. flexuosa woodlands, taxonomic and functional in- et al. 2016). Thus, the use of deadwood, associated with dices of vegetation and animal assemblages seem not to the land-use change produced by cattle raising, can be strongly coupled (Chillo and Ojeda 2014) although a affect some of NCP, such as maintenance of biodiversity decrease in diversity under increasing grazing intensity and habitat creation. has been observed (Chillo et al. 2017). In these wood- In recent years, the development of ecological indica- lands, plant species richness is related to the abundance tors based on functional traits has become a useful tool of adult trees (Campos et al. 2020), showing the import- to determine the effects of human disturbances on bio- ance of trees as fertility islands that contribute to the in- diversity and their implications for the provision of NCP crease in total diversity (Rossi and Villagra 2003). (Feld et al. 2009; Ehlers Smith et al. 2020). Even though Prosopis flexuosa is considered a nurse species because it traditionally ecologists have used species richness indica- facilitates the establishment of other plant species under tors as a measure of changes produced by people’s use its canopy (Rossi and Villagra 2003; Villagra and Alvarez on ecosystems and communities (Leps et al. 2006), there 2019), increases habitat heterogeneity, and sustains high is increasing evidence regarding the importance of func- diversity of small mammals (Tabeni and Ojeda 2003; tional traits of individual species and their interactions, Corbalán and Ojeda 2004; Szymañski et al. 2020). even more than the number of species per se (Díaz and Our study aimed to assess changes in biological diver- Cabido 2001; Villéger et al. 2008). This ‘functional-type’ sity in P. flexuosa woodlands under different land man- approach focuses on the common attributes (Díaz and agement types: grazed woodlands and a protected area. Cabido 2001), considering that communities’ response Changes in taxonomic and functional diversity were to human disturbances mainly depends on the functional evaluated on two assemblages, plants and mammals. For traits of species (Lavorel and Garnier 2002). plants, changes in structural diversity were also analyzed. In general, it has been shown that the increase in We evaluated the effects of variables related to compo- land-use intensity decreases diversity, but the results can nents of deadwood (deadwood on the ground, in the tree vary when taxonomic and functional diversity are ana- and deadwood removed) and land management types in lyzed, and depending on the context and the taxa being plant and mammal diversity. We expected lower diver- studied (Díaz et al. 2007; Carmona et al. 2012; Janeček sity for both assemblages in grazed woodlands than in et al. 2013; Hevia et al. 2016). Besides, in stressful habi- the protected area. In addition to this, when deadwood tats, plant and animal fitness is strongly affected by en- is removed, the availability of habitat and niche for ani- vironmental filters which shape the traits of the species mals can be reduced. Habitat loss drives functional trait (Mouchet et al. 2010; Carmona et al. 2012). Thus, spe- loss (Ehlers Smith et al. 2020), hence we expected that cies taxonomically different tend to present similar traits, deadwood extraction would decrease the availability of Szymañski et al. Forest Ecosystems (2021) 8:74 Page 3 of 15 resources and negatively impact mammal functional di- The BRÑ was created in 1961 to protect the Prosopis versity. Also, we expected that the effects of the dead- woodland that had been cut down at the beginning of wood extraction process, such as trampling, would the nineteenth century to extract wood for the develop- negatively impact plant diversity indices. ment of the irrigated oases, and devoted to livestock use (Abraham and Prieto 1999). In 1972 cattle were ex- Methods cluded, and the BRÑ was incorporated as a Man and Study area Biosphere Reserve in 1986. The native vascular flora has The study site is located in the Monte biogeographic re- been recovered after approximately 50-year of grazing gion (24°35′–44°20′ S; 62°54′–69°05′ W), Argentina. exclusion (Tabeni and Ojeda 2005). We selected two dominant land management types to The climate is semiarid to arid with a wide annual and conduct the research: a protected area, the Biosphere daily temperature range. Mean annual temperatures vary Reserve Nacuñán (BRÑ hereafter) where Prosopis wood- between 13 °C and 18 °C. The mean annual rainfall is lands are destined for conservation, and private sur- 326 mm (Labraga and Villalba 2009). Vegetation is rounding woodlands, where cattle grazing and composed of three main communities: a) shrubland deadwood extraction are the most common activities dominated by Zygophyllaceae species; b) edaphic steppe conducted by rural communities (Fig. 1). of halophytic shrubs (Suaeda divaricata, Atriplex spp., Fig. 1 Location of the study site in the Monte region. Protected area surrounding private grazed woodlands (R1, R2 and R3) are showed. Each thick point corresponds to one sample station around a Prosopis tree Szymañski et al. Forest Ecosystems (2021) 8:74 Page 4 of 15 Alleronfea vaginata); and c) woodland where P. flexuosa tree (Alvarez et al. 2011). Thus, we recorded variables is the dominant tree accompanied by shrubs and grasses related to deadwood for each tree. The amount of dead- − 1 (Larrea divaricata, L. cuneifolia, Condalia microphylla, wood in the tree (DW in trees; kg·tree ) and deadwood − 1 Pappophorum spp., Trichloris crinita and Digitaria cali- removed from the tree (DW removed; kg·tree ) were fornica, among others) (Villagra et al. 2004). estimated from the DAB (diameter at base height), ac- Local assemblages of small and medium-sized mam- cording to the methodology described by Alvarez et al. mals comprise more than 20 species, with different body (2011) for Prosopis forests of Northeast Mendoza. We sizes, activity periods, space use, and diets (e.g. Campos visually estimated the amount of deadwood on the et al. 2001; Ojeda and Tabeni 2009). Four orders are rep- ground (DW on ground) as the percentage of area under resented: a) Didelphimorphia (Thylamys pallidior, Didel- the tree crown covered by deadwood. phis albiventris); b) Cingulata (Chaetophractus villosus, C. vellerosus, Zaedyus pichiy, Chlamyphorus truncatus); c) Plant survey Carnivora (Puma concolor, Herpailurus yagouaroundi, Under each tree, we set four transects of 10 m oriented Leopardus colocolo, L. geoffroyi, Galictis cuja, Lyncodon to the cardinal points. We measured the abundance of patagonicus, Conepatus chinga, Lycalopex gymnocercus); vegetation by species and by cover type (grasses, forbs, and d) Rodentia (Dolichotis patagonum, Microcavia shrubs, subshrubs, and trees) through the Line-Intercept maenas, Galea leucoblephara, Ctenomys mendocinus, Method (Cummings and Smith 2000). We started from Eligmodontia typus, Graomys griseoflavus, Akodon dolores, the trunk of the tree and marked every 0.30 m with a 3- Calomys musculinus). Two exotic species occur in the area, m graduated pole placed vertically. Then, the abundance Sus scrofa and Lepus europaeus. of each plant species and the proportion of cover type were estimated to obtain both an index of taxonomic di- Sampling design and data collection versity (TD) and an index of structural diversity (SD). Prosopis flexuosa trees were selected inside the protected area and in three neighboring grazed fields (Fig. 1). All Mammal survey individuals presented a mean crown diameter of In order to detect mammals of different body sizes, two approximately 5 m. Fifteen trees at least 500 m apart sampling methods were used to obtain presence-absence were chosen at each area (N = 60 trees). The trees were data per tree. The capture method is the most suitable selected in accessible areas to reduce the risk of mortal- way to detect the presence of small rodents (Lettink and ity of captured animals in live capture traps. Armstrong 2003), due to their naturally low abundances Data for the study were collected in the period of and nocturnal habits in drylands. We arranged four tran- highest population abundance of the mammal species sects under each tree following the cardinal points. In (Corbalán 2006), during March and April of 2017, and each transect, we placed five Sherman live traps at 2-m 2018. The total sample effort was 4800 trap-nights and intervals, baited with rolled oats and vegetable oil (20 10,080 h of total camera operation. traps per tree) (Fig. 2). Traps remained open overnight for four consecutive days and they were checked in the Deadwood surveys morning. We identified captured animals by species, and Prosopis flexuosa is a heliophilous tree with low toler- then we released the animals at the place where they ance to shade, whose branches die and remain on the had been captured. Presence-absence data by species of Fig. 2 Experimental design showing sample station in Prosopis flexuosa trees, the location of trapping transects starting from trunk and the location of camera traps under tree canopy Szymañski et al. Forest Ecosystems (2021) 8:74 Page 5 of 15 small mammals at each tree were determined from a a is the number of species found in only one sample and total of 4800 trap-nights. All procedures were performed b is the number of species found in only two samples. according to guidelines of the Purdue Animal Care and Use Committee (PACUC) and the Animal Care and Use Structural diversity Taking into account differences in Committee of the American Society of Mammalogists the structure of vegetation of grazed fields and the BRÑ (Sikes and Gannon 2011) and under certificate for wild- (Tabeni and Ojeda 2005; Campos et al. 2016; Miguel life manipulation (Res. Number 320–2016 and 408– et al. 2018), we estimated an index of vegetation 2018). structure considering the plant cover types. The struc- To survey medium-sized and large mammals, we placed tural diversity was calculated analogously to taxonomic two camera traps (Moultrie, M-900i, Alabaster, AL, USA) diversity, but considering life forms (grasses, forbs, under the cover of each of the 60 trees (Fig. 2). Cameras shrubs, subshrubs, and trees) instead of species (here- were mounted on a 0.50-m high backing and vegetation after SD). A structurally complex site is characterized by surrounding the detection zone was cleared to allow ani- a greater diversity of cover types (Sukma et al. 2019). mals identification. The cameras took three consecutive pictures whenever animal movement was detected, with a Functional traits and functional diversity For plants, 15-s delay between shoots, over an 84-h period (total cam- all traits selected were qualitative and related to disper- era operation = 10,080 h; 120 camera traps per 84 h per sion, establishment and persistence, taking into account camera). Animal species were identified from photos previous studies developed in the Monte region (Chillo based on fur color, tail and body length and other species- et al. 2017) (Table 1). For mammals, we chose two quan- specific physical traits (Ojeda 1989; Braun et al. 2000; titative and seven qualitative traits linked to resource use Giannoni et al. 2001; Tognelli et al. 2001). We recorded and niche dimensions (Table 1) (Sukma et al. 2019). species’ names, and we combined the data from the two Trait values for each species were provided by experts cameras of each tree to generate presence-absence and obtained from literature (e.g. Campos and Ojeda estimates. 1997; Campos et al. 2001; Ojeda and Tabeni 2009; Villa- gra et al. 2011; Campos and Velez 2015). Diversity indices Functional dispersion for both plants and mammals Considering that types of diversity do not always re- was calculated as an indicator of functional diversity spond similarly to disturbances (Carmona et al. 2012; (hereafter FD) with the species records for each sampled Hevia et al. 2016), we analyzed taxonomic and functional tree combined with trait information (Villéger et al. diversity indices for plants and mammals, and also a 2008; Pla et al. 2012; Mason and Mouillot 2013). Func- structural diversity index for plants. tional dispersion (3) is a multivariate index that is calcu- lated as the mean distance of each species to the Taxonomic diversity The Shannon-Weiner index (H′) community centroid, weighted by its abundance (Sukma (Magurran 2004) was estimated for plants and Chao 2 et al. 2019; Salgado-Luarte et al. 2019). This index is index (S )(Chao 1984, 1987) was estimated for mam- closely related to Rao’s quadratic entropy but it can be Chao2 mals, both of them as a proxy of taxonomic diversity used for statistical analysis of unweighted data (pres- (hereafter TD). For plants, abundance per species by tree ence-absence records) (Laliberté and Legendre 2010). was used to estimate Shannon-Weiner index (1) with Bio- For mammals, species presence-absence data were used diversityR package (Kindt and Kindt 2015)inthe Rstatis- jointly with functional traits to compute FD. For plants, tical environment (R Core Team 2018). For mammals, the abundance of species and functional traits were used Chao 2 index (2) was selected because allows estimating to estimate FD. Functional diversity indices were calcu- the richness across assemblages with presence-absence lated with the FD package (Laliberté et al. 2014) in the R data (Chao 1984, 1987). Chao 2 index was calculated with statistical environment (Core Team 2018). EstimateS software (Colwell and Elsensohn 2014). 0 S a z j j H ¼ − ðÞ p log p ð1Þ P FDis ¼ ð3Þ i 2 i i¼1 where S is the number of species, and p is the propor- tion of the total sample that belongs to the i-th species. where a is the abundance of species j and z is the j j distance of species j to the weighted centroid. For S ¼ S þ ð2Þ presence-absence data, functional dispersion is the Chao2 obs 2b unweighted mean distance to the centroid (Laliberté and where S is the actual number of species in the sample, Legendre 2010). obs Szymañski et al. Forest Ecosystems (2021) 8:74 Page 6 of 15 Table 1 Traits of plants and ground-dwelling mammal species Taxa Trait Levels Vegetation Growth form Grass Forb Subshrub Shrub Tree Life cycle Annual Deciduous Perennial Leaf size Small (< 2 cm) Medium (2–5 cm) Big (> 5 cm) Main root system Taproot Lateral Lateral spread Single root Several stems Stolons/rhizomes Leaf texture Tough Intermediate Membranous Leguminosae Legume/non legume Storage organs Yes/no Attractive fruits Yes/no Mammals Activity period Nocturnal Diurnal Body mass Natural log of mean mass in grams (continuous) Ecological role in Prosopis seeds dispersal Seed predator Seed disperser Locomotion habit Scansorial Cursorial Fossorial Semifossorial Nest type Caves Burrows and hollow on ground Hollow on tree Origin Native Exotic and domestic Exotic and wild Main food type Omnivore-folivore Omnivore-insectivorous Omnivore-granivore Omnivore Herbivore Insectivore Carnivore Litter size Continuous variable derived from the mean of reported values Statistical analysis compare the coefficients. We applied GLM with Normal We built generalized linear models (GLM) to assess the distribution to model TD and SD, and GLM with Beta responses of diversity indices of each assemblage to co- distribution to model FD, taking into account the AIC variates concerning deadwood (deadwood in the tree, associated with different distributions for continuous deadwood removed and the amount of deadwood on the variables. We built a set of candidate models with the ground) and different land management types (protected possible combination of additive covariates. The models area and grazed woodlands). All quantitative explanatory were ranked following the AIC and we eliminated from variables were standardized and centered to directly the set those models that did not converge. Because no Szymañski et al. Forest Ecosystems (2021) 8:74 Page 7 of 15 single model was clearly superior to some of the others statistically significant for both assemblages, but model in the set, we used estimates from multiple candidate fit varied from moderate to poor (in example: R for models, hence calculating model-averaged estimates plants’ SD index = 0.58; R for mammals’ FDis = 0.14). In (Burnham et al. 2011). We selected a set of candidate summary, land management of grazed woodlands was models and ranked them starting from the best until associated to higher plants structural diversity and mam- Akaike’s cumulative weight reached 0.95, and then we mal functional diversity. By contrast, deadwood had dif- rejected the rest (Symonds and Moussalli 2011). The ob- ferential effects on the different types of diversity and on jective was to generate a ‘confidence set’ of models that assemblages. are the most likely to be the best approximation model (Burnham and Anderson 2004). The direction and mag- Plants nitude of the effect size of each covariate were based on From fifteen candidate models built to analyze the taxo- model-averaged estimates (Burnham et al. 2011). The nomic diversity of plants, we selected only nine models relative importance of each covariate under consider- according to a 95% confidence set of models (R ranging ation was estimated by summing the Akaike weights for from 0.06 to 0.20) (Table 2). Deadwood on ground and each model in which that covariate appeared (Symonds deadwood removed appeared in all models, and they and Moussalli 2011). Covariates with summed model presented the higher relative importance. Moreover, they weights (SW) > 0.5 were considered the most statistically were the covariates with the greatest effect on the taxo- important (Barbieri and Berger 2004). The R coefficient nomic diversity of plants. Deadwood on ground de- was computed to evaluate the goodness of fit (Schielzeth creased the plant’s taxonomic diversity, while deadwood and Nakagawa 2013), and graphical methods were removed increased it (Fig. 3). employed to confirm that models adjusted to assump- Fifteen models were built for the structural diversity of tions of normality in the residuals and homogeneity of plants, but only six models were selected within a 95% variances. confidence set of models (R ranging from 0.49 to 0.58) Modeling was carried out using betareg (Zeileis et al. (Table 3). The covariates with the highest relative im- 2016) and lme4 (Bates et al. 2018) packages, and model- portance were deadwood removed, deadwood on ground averaging was performed with the MuMIn (Barton 2015) and land management type, but only deadwood removed package, in R 3.4.2 language and environment (Core appeared in all models (Table 3). Besides, deadwood re- Team 2018). moved was the covariate with the greatest effect on the structural diversity of plants (between two and four Results times greater than other variables related to deadwood), Relationships between diversity indices and covariates presenting a positive relationship with the response vari- related to deadwood and land management types were able (Fig. 3). The land management type is the following Table 2 Summary of the model selection procedure for taxonomic diversity index of plants int x x x x df log( ) AIC Δiw R 1 2 3 4 i 1.48 −0.08 0.09 4 9.75 −10.71 0.00 0.47 0.20 1.47 − 0.08 0.10 0.06 5 10.11 −9.03 1.68 0.20 0.21 1.48 0.01 −0.08 0.09 5 9.82 −8.44 2.26 0.15 0.20 1.47 0.01 −0.08 0.10 0.06 6 10.13 −6.55 4.16 0.06 0.21 1.48 0.07 3 6.04 −5.61 5.10 0.04 0.09 1.48 −0.06 3 5.39 −4.33 6.38 0.02 0.06 1.47 0.08 0.05 4 6.28 −3.78 6.93 0.01 0.09 1.48 0.00 0.07 4 6.04 −3.30 7.41 0.01 0.09 1.50 −0.06 −0.05 4 5.72 −2.65 8.06 0.01 0.08 SW 1.00 0.23 1.00 0.96 0.28 β 1.48 0.01 −0.08 0.09 0.06 SE 0.03 0.03 0.03 0.03 0.08 Model averaging was carried out with a 95% confidence subset of models. For each model of the subset, we reported parameter estimates, total number of estimable parameters (k), the log-likelihood log( ), AIC criterion, Δi =AIC – minAIC, Akaike weight (w ), and adjusted R . Models are ordered in terms of Δi for AIC. i i At the bottom of the table, we reported model-averaged estimates β with their standard errors (SE) and their sum of weights (SW), for the four variables (quantitative variables: x - DW in tree, x - DW on ground, x - DW removed; categorical variable: x - land management type (protected 1 2 3 4 area/grazed woodlands-intercept-)) Szymañski et al. Forest Ecosystems (2021) 8:74 Page 8 of 15 Fig. 3 Taxonomic, structural and functional diversity indeces and DW variables for plant assemblages. Covariates with the higher SW and effect were graphed covariate in importance, and it can be observed that the models (R ranging from 0.31 to 0.35) (Table 4). The co- structural diversity is lower in the protected area (Table 3). variates related to deadwood presented the highest rela- Also, deadwood on ground negative affected SD. tive importance, but only deadwood on ground and We built fifteen candidate models to analyze the func- deadwood removed appeared in all models, being their tional diversity of plants, but we only selected four relative importance equal to 1 (Table 4). Also, deadwood models taking into account a 95% confidence set of on ground and deadwood removed were the covariates Szymañski et al. Forest Ecosystems (2021) 8:74 Page 9 of 15 Table 3 Summary of the model selection procedure for structural diversity index of plants int x x x x k log( ) AIC Δiw R 1 2 3 4 i 1.30 −0.04 0.13 −0.09 5 33.92 −56.65 0.00 0.39 0.57 1.30 0.02 −0.05 0.13 −0.11 6 34.54 −55.37 1.28 0.21 0.58 1.27 −0.05 0.15 4 31.97 −55.15 1.50 0.18 0.54 1.30 0.12 −0.10 4 31.10 −53.42 3.22 0.08 0.52 1.27 0.01 −0.05 0.15 5 32.14 −53.09 3.56 0.07 0.54 1.27 0.14 3 29.17 −51.87 4.78 0.04 0.49 SW 1.00 0.30 0.86 1.00 0.71 β 1.29 0.02 −0.05 0.13 −0.10 SE 0.03 0.02 0.02 0.03 0.05 Model averaging was carried out with a 95% confidence subset of models. For each model of the subset, we reported parameter estimates, total number of estimable parameters (k), the log-likelihood log( ), AIC criterion, Δi =AIC – minAIC, Akaike weight (w ), and adjusted R . Models are ordered in terms of Δi for AIC. i i At the bottom of the table, we reported model-averaged estimates β with their standard errors (SE) and their sum of weights (SW), for the four variables (quantitative variables: x - DW in tree, x - DW on ground, x - DW removed; categorical variable: x - land management type (protected 1 2 3 4 area/grazed woodlands-intercept-)) with the greatest effect on the functional diversity of (Table 6). Functional diversity of mammals was mainly plants. Deadwood on ground negatively affected func- affected by land management type (magnitude of land tional diversity, while deadwood removed did positively management type was twice that deadwood in tree and (Fig. 3). deadwood on ground), being lower in protected area (Table 6). Deadwood in the tree was positively related to Mammals functional diversity, while deadwood on ground nega- Fifteen candidate models were built to analyze the mam- tively affected it (Fig. 4). mal taxonomic diversity, but only six were selected (R ranging from 0.44 to 0.50) (Table 5). The covariate dead- Discussion wood removed appeared in all models, being its relative Human-induced changes are usually assumed to cause importance equal to 1. Furthermore, this covariable pre- the loss of species and thus a decrease of the diversity of sented the greatest effect on the taxonomic diversity of functional traits, but the responses of different diversity mammals (three times greater than the variable that fol- indices could follow different patterns (Carmona et al. low in importance), being this effect negative (Fig. 4). 2012; Hevia et al. 2016). Our results showed that wood- Deadwood on ground also presented an importance land management produces changes in biodiversity, but greater than 0.5, showing a negative effect on TD. the effects differed among the assemblages and the ap- Of the fifteen models built to analyze the functional proaches of biodiversity studied. In summary, land man- diversity of mammals, thirteen of them corresponded to agement type of grazed woodlands was associated to a 95% confidence set of models (R ranging from 0.01 to higher plants structural diversity and mammal functional 0.14) (Table 6). In the averaged-model, deadwood in tree diversity. By contrast, deadwood had differential effects and land management type were the covariates with on the different types of diversity and on assemblages. higher SW, but deadwood on ground was also important Presence of deadwood on ground negatively affected Table 4 Summary of the model selection procedure for functional diversity index of plants int x x x x k log( ) AIC Δiw R 1 2 3 4 i −0.61 0.02 −0.04 0.05 5 141.68 −272.17 0.00 0.47 0.35 −0.61 −0.04 0.05 4 140.01 −271.23 0.94 0.29 0.31 −0.61 0.02 −0.04 0.05 0.00 6 141.69 − 269.67 2.50 0.13 0.35 −0.60 − 0.04 0.06 0.01 5 140.06 −268.92 3.25 0.09 0.31 SW 1.00 0.61 1.00 1.00 0.23 β −0.61 0.02 −0.04 0.05 0.00 SE 0.01 0.01 0.01 0.01 0.03 Model averaging was carried out with a 95% confidence subset of models. For each model of the subset, we reported parameter estimates, total number of estimable parameters (k), the log-likelihood log( ), AIC criterion, Δi =AIC – minAIC, Akaike weight (w ), and adjusted R . Models are ordered in terms of Δi for AIC. i i At the bottom of the table, we reported model-averaged estimates β with their standard errors (SE) and their sum of weights (SW), for the four variables (quantitative variables: x - DW in tree, x - DW on ground, x - DW Removed; categorical variable: x - land management type (protected 1 2 3 4 area/grazed woodlands-intercept-)) Szymañski et al. Forest Ecosystems (2021) 8:74 Page 10 of 15 Table 5 Summary of the model selection procedure for taxonomic diversity index of mammals int x x x x k log( ) AIC Δiw R 1 2 3 4 i 15.98 0.39 −0.58 −1.60 5 −113.07 237.35 0.00 0.30 0.50 15.98 −0.51 −1.60 4 − 114.29 236.36 0.01 0.29 0.48 15.98 −1.72 3 − 116.15 238.76 1.42 0.15 0.44 16.17 −0.51 −1.54 −0.25 5 −114.21 239.62 2.28 0.09 0.48 15.98 0.29 − 1.74 4 − 115.50 239.79 2.45 0.09 0.45 15.99 0.39 −0.58 −1.59 −0.02 6 −113.07 239.86 2.51 0.08 0.50 SW 1.00 0. 47 0.77 1.00 0.18 β 15.99 0.37 −0.54 −1.62 −0.14 SE 0.35 0.27 0.27 0.29 0.71 Model averaging was carried out with a 95% confidence subset of models. For each model of the subset, we reported parameter estimates, total number of estimable parameters (k), the log-likelihood log( ), AIC criterion, Δi =AIC – minAIC, Akaike weight (w ), and adjusted R . Models are ordered in terms of Δi for AIC. i i At the bottom of the table, we reported model-averaged estimates β with their standard errors (SE) and their sum of weights (SW), for the four variables (quantitative variables: x - DW in tree, x - DW on ground, x - DW Removed; categorical variable: x - land management type (protected 1 2 3 4 area/grazed woodlands-intercept-)) diversity for plants while deadwood removed increased convergent and plant adaptations that enhance living in them. For mammals, deadwood on ground clearly de- drylands also promote tolerance or avoidance of grazing creased the both types of diversity analyzed, while the (Sala 1988). Carmona et al. (2012) have reported a con- removal of deadwood decreased TD and presence of vergence in traits under the combined effect of grazing deadwood in tree increased FD. We found that taxo- and drought conditions. Other factors also could be nomic and functional diversity for both, plant and mam- driving the diversity of vegetation. In P. flexuosa wood- mal assemblages did not vary consistently with the land lands of the hyper-arid portion of the Monte Desert, management type. This could be showing differential re- Campos et al. (2020) reported that the vegetation rich- sponses of the diversity indices for both assemblages ness is enhanced by the abundance of adult trees and (Carmona et al. 2012; Chillo and Ojeda 2014), and it the effect of facilitation provided by them seems to be highlights the importance of considering functional and very important in ecosystems under high abiotic stress. taxonomic diversity in evaluating the responses of wood- Prosopis trees increase local soil fertility through the ac- land ecosystems to disturbances (Carmona et al. 2012). cumulation of carbon and nitrogen, and modify the de- For the plant assembly, taxonomic and functional di- composition rate by increasing infiltration rate and versity indices did not significantly change under differ- protecting against high temperatures and radiation ent land management types. In stressful ecosystems, (Rossi and Villagra 2003). However, we observed that environmental filters are among the main factors struc- grazing and deadwood management promoted an incre- turing plant communities (Chillo et al. 2017). Particu- ment in the structural diversity of plants, as previous larly in drylands, the fitness of the individuals is strongly studies have proposed (Tabeni and Ojeda 2005; Campos affected by the availability of water, which could make et al. 2016; Miguel et al. 2018). the relative importance of the disturbance less evident Functional similarities are also expected for the assem- (Carmona et al. 2012). Also, in drylands that had coe- bly of animals living in stressful environments (Mouchet volved with large herbivores, selection pressures are et al. 2010). We found that the taxonomic diversity of Fig. 4 Taxonomic and functional diversity indeces and DW variables for mammal assemblages. Covariates with the higher SW and effect were graphed Szymañski et al. Forest Ecosystems (2021) 8:74 Page 11 of 15 Table 6 Summary of the model selection procedure for functional diversity index of mammals int x x x x k log( ) AIC Δiw R 1 2 3 4 i −0.66 0.05 − 0.04 −0.11 5 107.05 −202.90 0.00 0.19 0.14 −0.67 0.04 −0.10 4 105.46 −202.13 0.76 0.13 0.09 −0.67 − 0.08 3 103.99 −201.51 1.39 0.09 0.04 −0.69 0.03 3 103.80 −201.13 1.77 0.08 0.03 −0.67 − 0.03 −0.08 4 104.89 −200.99 1.91 0.07 0.07 −0.69 0.04 −0.03 4 104.85 −200.91 1.99 0.07 0.07 −0.69 − 0.03 3 103.52 −200.57 2.33 0.06 0.03 −0.66 0.05 −0.04 0.01 −0.10 6 107.09 −200.46 2.44 0.06 0.14 −0.69 0.04 −0.04 0.03 5 105.71 −200.22 2.68 0.05 0.10 −0.69 0.02 3 103.26 −200.06 2.84 0.05 0.01 −0.69 − 0.03 0.03 4 104.30 −199.83 3.07 0.04 0.05 −0.66 0.04 0.00 −0.10 5 105.46 −199.73 3.17 0.04 0.09 −0.69 0.03 0.02 4 104.19 −199.59 3.31 0.04 0.05 SW 1.00 0.67 0.56 0.28 0.60 β −0.67 0.04 −0.04 0.02 −0.10 SE 0.03 0.02 0.02 0.03 0.05 Model averaging was carried out with a 95% confidence subset of models. For each model of the subset, we reported parameter estimates, total number of estimable parameters (k), the log-likelihood log( ), AIC criterion, Δi =AIC – minAIC, Akaike weight (w ), and adjusted R . Models are ordered in terms of Δi for AIC. i i At the bottom of the table, we reported model-averaged estimates β with their standard errors (SE) and their sum of weights (SW), for the four variables (quantitative variables: x - DW in tree, x - DW on ground, x - DW Removed; categorical variable: x - land management type (protected 1 2 3 4 area/grazed woodlands-intercept-)) mammals did not change by land management type, but functional diversity can increase without a change in functional diversity increased in grazed woodlands. This species diversity under land-use change (Mayfield et al. may be showing that the management of grazed wood- 2010). In grazed woodlands, the heterogeneous spaces lands is leading to a decrease of functional redundancy characterized by vegetation patches in a matrix of bare for mammals. In the protected area, the exclusion of soil allow for the presence of mammals species needing grazing and extractive activities for almost 50 years has open spaces to develop (Tabeni and Ojeda 2005). Previ- driven the recovery of vegetation, but in turn causing ous studies have reported the presence of species such homogenization in the habitat structure (Rossi 2004; as Dolichotis patagonum or Eligmodontia typus only in Campos et al. 2016). Although more productive areas grazed woodlands (Tabeni and Ojeda 2005), were traits promote positive responses in functional diversity such as locomotion habit allows them to avoid predation (Sukma et al. 2019), the homogenization of habitat in open spaces (Taraborelli et al. 2003). At local scale, structures leads to a decrease in niche availability, and trees with a well-conserved structure of deadwood and consequently it diminishes the representation of traits grasses under their canopy produce a cascade effect in capable of occupying that functional space. Usually, ho- these grazed woodlands because they promote a web of mogenized habitats do not contain a wide spectrum of plant and animal interactions which are especially bene- functional traits (Carmona et al. 2012; Ehlers Smith ficial for species needing more complex habitats (Szy- et al. 2020). What is more, the homogenization involves mañski et al. 2020). Species associated with closed and the biotic impoverishment, decreasing the resilience of homogeneous habitats, such as G. griseoflavus and A. do- the system against disturbances (Salgado-Luarte et al. lores, can be found both in the protected area and in 2019). In the protected area, we observed that the grazed woodlands (Tabeni and Ojeda 2005; Campos homogenization of the habitat did not modify the taxo- et al. 2016; Miguel et al. 2018). Thus, spatial heterogen- nomic diversity of mammals but it influenced the func- eity of resource availability in grazed woodlands in- tional diversity of mammals, presenting smaller values. creases the functional trait dissimilarity, and the By contrast, grazed woodlands did not present changes functional diversity of mammals. Opposite results have in taxonomic diversity in comparison to the protected been reported for drylands in North-Central Chile, area, but functional diversity was higher in grazed wood- showing a homogenization of vegetation community lands. When species with novel functional traits replace under grazing pressure by goats (Salgado-Luarte et al. functionally redundant species within a community, 2019). This stresses the fact that livestock grazing is a Szymañski et al. Forest Ecosystems (2021) 8:74 Page 12 of 15 complex disturbance, and highlights the importance of process, a possible explanation is that the trampling ef- considering several factors that determine its effects, fect is not significant because the extraction level is low. such as grazer identity and stocking rates, among many The evidence for the effects of deadwood removal in for- others (Chillo et al. 2017). ests around the world is not conclusive, and studies Our results disagree with those reported in other stud- show negative, nil, or even positive effects on ecosystem ies (Chillo et al. 2017; Salgado-Luarte et al. 2019), where functioning. In arid lands, the information is scarce, but increasing grazing intensity was linked to a decrease in there is evidence that deadwood extraction does not taxonomic diversity and functional diversity of all plant have significant effects on the cover, richness and com- and animal assemblages. Probably, the main difference is position of understory plants (Vázquez et al. 2011). because our findings relate to moderate livestock loads Deadwood seems to have a main role in the conserva- in grazed woodlands and do not consider a grazing gra- tion of mammal diversity. In other forest ecosystems, dient, as did Chillo et al. (2017). In the study area, the such as boreal forests, deadwood represents an import- carrying capacity for livestock production depends on ant forest component that furnishes habitats for inverte- precipitation but the recommended sustainable stocking brates, in turn providing feeding sites for vertebrate − 1 rate is between 15 and 26 ha·AU (hectares per animal species (Sullivan et al. 2017). In P. flexuosa woodlands, unit, one animal unit (AU) is defined as a 450-kg beef there is evidence that deadwood availability is positively cow) (Guevara et al. 2009). For mammal assemblages, associated with the presence of small rodents (Szy- human disturbances, such as logging, fire, agriculture ex- mañski et al. 2020). Our findings indicated that at local pansion and livestock grazing, have been reported to scale, deadwood in the tree is relevant for the conserva- present negative effects on functional diversity in arid tion of mammal diversity. Deadwood in the tree is used and semi-arid biomes, but herbivory is the disturbance by scansorial species, such as G. griseoflavus, a small ro- that least affects the mammal functional diversity, prob- dent predator of P. flexuosa seeds (Giannoni et al. 2013). ably because levels of grazing reported did not generate The arched branching pattern, with branches reaching changes in resources and the initial state properties of the ground, defines the structure used by M. maenas in ecosystems (Chillo and Ojeda 2012). Furthermore, the locating their colonies (Tognelli et al. 1995); this species evolutionary history of the plant-herbivore interaction is is a seed disperser of P. flexuosa (Campos et al. 2017). one of the main factors that determines the effect of Deadwood in the tree could be used as a resting site by grazing on the plant community in arid ecosystems climbing carnivores, such as Leopardus geoffroyi. Besides, (Cingolani et al. 2005). Thus, maintaining appropriate deadwood provides feeding and nesting sites to small levels of grazing could promote the heterogeneity of rodents, which in turn constitutes a source of food habitats which positively influences the structure, com- resources for carnivores. Thus, the vertical structure of position and functional diversity of mammal assem- deadwood on trees favors the presence of mammal blages. Taking into account the results of the present species with different functional traits. By contrast, we study, management strategies of livestock production in found that the presence of deadwood on the ground de- grazed woodlands are compatible with the conservation creased mammal diversity at tree scale. This may indi- of functional diversity of the analyzed assemblages. It cate an indirect effect because deadwood on ground has been reported for other arid lands that intermediate decreased all plant diversity indices, which negatively af- levels of grazing are desirable for the preservation of a fects species that do not use the vertical space, but pre- threatened plant species (Martorell and Peters 2005). fer the complex habitat formed by plants. Contrary to what we expected, the results showed that The role of deadwood needs to be assessed in different deadwood removal positively affected both taxonomic forest ecosystems because management of this forest and functional diversity of plants, and the presence of component should be included in management pro- deadwood on the ground negatively affected plant func- grams (Lassauce et al. 2011; Vázquez et al. 2011). This tional diversity. Prosopis flexuosa conserves the internal study is the first considering the role of deadwood in re- dry branches, occupying the space under the tree can- lation to the functional diversity of plant and mammal opy. Thus, the presence of deadwood in the trees may assemblages of drylands. Although the results are not be reducing the available space with good moisture and conclusive, they are relevant because they fill an import- nutrient conditions for the regeneration and establish- ant knowledge gap in arid ecosystems. Also, taking into ment of plants, affecting diversity indices. This fact be- account the low variability explained by some of our comes more relevant in arid environments, such as models, futures studies should consider other drives of Prosopis woodlands, where trees act as nurse species, diversity, such as productivity, soil heterogeneity, wood- permitting the development of a network of interactions land structure, multiple human disturbances and even under their canopy (Rossi and Villagra 2003). Regarding climate change in order to achieve a better comprehen- the damage to plants resulting from the extraction sion of biodiversity dimensions (Campos et al. 2020). Szymañski et al. Forest Ecosystems (2021) 8:74 Page 13 of 15 Conclusions population structure and tree-growth habit. J Arid Environ 7(1):7–13. https:// doi.org/10.1016/j.jaridenv.2010.09.003 Livestock loads of the studied sites promote the struc- Barbieri MM, Berger JO (2004) Optimal predictive model selection. Ann Stat 32(3): tural diversity of plant assemblages and the functional 870–897. https://doi.org/10.1214/009053604000000238 diversity of mammals. Regarding deadwood, opposite re- Barton K (2015) Package ‘MuMin’. Version 1(18):439. https://cran.r-project.org/ web/packages/MuMIn/MuMIn.pdf. Accessed 15 June 2021 sults were found in terms of diversity conservation of Bates D, Maechler M, Bolker B, Walker S, Christensen RHB, Singmann H, Green P mammals and plants. At tree scale, it is advisable to (2018) Package ‘lme4’. Version 1(17):437 https://cran.r-project.org/web/packa maintain trees that preserve their wooden structure ges/lme4/index.html. Accessed 15 June 2021 Botta-Dukát Z (2005) Rao’s quadratic entropy as a measure of functional diversity within the managed areas to promote the functional di- based on multiple traits. J Veg Sci 16(5):533–540. https://doi.org/10.1111/j.1 versity of mammals, while trees with extraction from 654-1103.2005.tb02393.x standing wood will favor the functional diversity of the Braun JK, Mares MA, Ojeda RA (2000) A new species of grass mouse, genus Akodon (Muridae: Sigmodontinae), from Mendoza province, Argentina. Z plant assemblage. Säugetierkd 65(4):216–225 Burnham KP, Anderson DR (2004) Multimodel inference: understanding AIC and Abbreviations BIC in model selection. Sociol Methods Res 33(2):261–304. https://doi.org/1 NCP: Nature’s contributions to people; BRÑ: Biosphere Reserve Nacuñán; 0.1177/0049124104268644 DAB: Diameter at base height; DW: Deadwood; TD: Taxonomic diversity; Burnham KP, Anderson DR, Huyvaert KP (2011) AIC model election and SD: Structural diversity; FDis: Functional dispersion; FD: Functional diversity; multimodel inference in behavioral ecology: some background, observations, GLM: Generalized linear models; AIC: Akaike Information Criterion; and comparisons. Behav Ecol Sociobiol 65(1):23–35. https://doi.org/10.1007/ SE: Standard errors; SW: Sum of weights s00265-010-1029-6 Campos CM, Campos VE, Giannoni SM, Rodríguez D, Albanese S, Cona MI (2017) Acknowledgments Role of small rodents in the seed dispersal process: Microcavia australis We thank the staff of BÑR and the owners and families in charge of the consuming Prosopis flexuosa fruits. Austral Ecol 42(1):113–119. https://doi. private fields for allowing us to work there. We thank C. Moreno, S. Mendoza, org/10.1111/aec.12406 N. Carlos, F. Lozano, L. Ramos and L. Sosa for help with data collection in the Campos CM, Campos VE, Miguel F, Cona MI (2016) Management of protected field. C. Pissolito assisted us in drafting the English version. areas and its effect on an ecosystem function: removal of Prosopis flexuosa seeds by mammals in Argentinian drylands. PLoS One 11(9):e0162551. Authors’ contributions https://doi.org/10.1371/journal.pone.0162551 All authors conceived the study, collected the data, performed statistical Campos CM, Ojeda RA (1997) Dispersal and germination of Prosopis flexuosa analysis and helped to draft manuscript. All authors read and approved the (Fabaceae) seeds by desert mammals in Argentina. J Arid Environ 35(4):707– final manuscript. 714. https://doi.org/10.1006/jare.1996.0196 Campos CM, Ojeda RA, Monge S, Dacar M (2001) Utilization of food resources by Funding small and medium-sized mammals in the Monte Desert biome, Argentina. This work was supported by National Council for Scientific and Technical Austral Ecol 26(2):142–149. https://doi.org/10.1046/j.1442-9993.2001.01098.x Research (CONICET, Proyecto de Unidad Ejecutora 0042 IADIZA), National Campos CM, Velez S (2015) Almacenadores y frugívoros oportunistas: el papel de Agency for Scientific and Technological Promotion of Argentina (PICT 2017– los mamíferos en la dispersión del Algarrobo (Prosopis flexuosa DC) en el 2154), Secretary of Science, Technology and Postgraduate - U.N. Cuyo desierto del Monte, Argentina. Ecosistemas 24(3):28–34. https://doi.org/10. (Program 2016 and 2018) and a graduate fellowship from CONICET to CS. 7818/ECOS.2015.24-3.05 Campos VE, Cappa FM, Gatica G, Campos CM (2020) Drivers of plant species richness Availability of data and materials and structure in dry woodland of Prosopis flexuosa. 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Journal
"Forest Ecosystems" – Springer Journals
Published: Nov 23, 2021
Keywords: Central Monte; Cattle raising; Deadwood extraction; Taxonomic diversity; Functional traits