DOI: 10.5061/dryad.66t1g1k4v
title: Decomposing niche components reveals simultaneous effects of opposite deterministic processes structuring alpine small mammal assembly

description: Our knowledge of community assembly dynamics under multiple stressors is
 limited because of opposite niche-based processes, i.e., limiting
 similarity and habitat filtering could simultaneously occur, masking the
 overall patterns. Alpine biomes provide the ideal systems to explore the
 influences of co-occurrence processes as these communities usually face
 multiple stresses such as resources limitation and habitat constraints.
 However, the assembly processes of mammals in alpine areas have hardly
 been exclusively studied. Here, we aimed to address how different
 processes structured small mammal communities at the tree line transition
 zone, which represents one of the most distinct vegetation boundaries
 separating alpine from montane habitats. We compiled a regional dataset
 including species list, phylogeny, and functional traits from field
 collections across 18 mountains of southwest China and complemented them
 with published data sources. The traits were decomposed into different
 niche components to determine the respective effects of specific
 stressors. Phylogenetic and functional diversity indices representing
 evolutionary history, trait space, and pairwise species distance were
 calculated and compared with null expectations. Linear mixed-effect models
 were constructed to assess the increasing or decreasing tendencies of
 diversity values against increasing elevation. The results showed that
 phylogenetic and functional richness were strongly correlated with species
 richness, unlike the distance-based indices which were uncorrelated with
 species richness. There was no evidence found to support non-random
 phylogenetic or overall trait patterns. However, the resource acquisition
 niche tended to be more overdispersed (positive slopes), while the habitat
 affinity niche tended to be more clustered (negative slopes) as habitats
 became less productive and less vegetated. We conclude that limiting
 similarity and habitat filtering simultaneously structure small mammal
 communities in alpine areas. Altogether, the present study provides vital
 insights into the complexity of co-occurring assembly processes by niche
 decomposition, and highlights the importance of considering different
 diversity dimensions when assessing community structure.
description: 2.1 Study area and field
 sampling The study region is located in the southwest
 mountains of China, a global biodiversity hotspot (Mittermeier et al. 2011), and covers the Three Parallel Rivers of Yunnan
 Protected Areas (Fig 1). Four north-south trending mountain ranges
 dominate the region's topography (from west to east, Gaoligong,
 Nushan, Yunling, and Shaluli). Eighteen prominent mountains (or
 sky-islands) were selected as study sites to adequately represent the
 study region's extent (Appendix 1). The tree line in the region
 represents one of the most distinct vegetation boundaries separating
 alpine from montane habitats (Körner 2013; Testolin et al.
 2020). Across the study
 region, the alpine tree line is located between ca. 3 800 – 4200 meters
 above mean sea level (m a.s.l.), and generally rises from south to north
 but varies between sites due to several abiotic or anthropogenic
 influences (Wang et al.
 2013). The alpine habitats
 in the region experience a moderate decline in annual precipitation from
 west to east (Sherman et
 al. 2008), with a 6.7 ℃
 mean annual temperature at the tree line (Wang et al. 2013). The vegetation from below to above the tree
 line rapidly changes from dark coniferous forests to dwarf shrubs,
 meadows, and scree (Fig.
 3; Sherman et al. 2008). The small mammal sampling was conducted from
 2013 to 2018 following a standardized field method (See Song et al. 2020 for
 details). Basically, three
 elevational transects (from 200 m below to 200 m above the tree line at
 200 m intervals) were established on each mountain, representing the
 environmental transition from montane to alpine habitats. We chose this
 elevation range because it covered most small mammal species'
 strongest habitat transition zone before their upper distribution limits.
 The highest transect was missing in seven mountains because their summit merely
 transcended the tree line, and the remaining elevations beyond the tree
 line were not enough for another transect (＜ 200 m). For each captured small mammal,
 measurements of body weight (BW), head-body length (HB), tail length (TL),
 hindfoot length (HF), and ear length (EL) were recorded in the field. From
 each site (mountain), at least one stuffed voucher and skull specimen was
 prepared for each morphologically discriminable group. Liver and muscle
 tissues were collected from each specimen, dehydrated, and preserved in
 2ml vials (81-8204, Biologix Inc., Shandong, China) with 99.7% ethanol for
 DNA extraction. All samples were identified by morphological comparison
 and DNA barcoding based on the mitochondrial Cytochrome b (CYTB) gene
 (Borisenko et al.
 2008). All collections are
 deposited at Kunming Institute of Zoology, Chinese Academy of
 Sciences. 2.2 Reginal species pool
 The regional species pool
 crucially influences conclusions on local communities’ assembly patterns
 and processes (Weiher and
 Keddy 1995). Species from
 the regional pool should have the potential to colonize, establish, or
 inhabit the focal communities depending on different ecological processes
 (Lessard et al.
 2012) and be adequately
 detected in the field. The regional small mammal species pool was
 primarily derived from Wen
 et al. (2016). This data
 set contains county-level species occurrence records covering our study
 sites. To avoid eliminating influences of potential habitat filtering in
 alpine communities a priori (Lessard et al. 2012), we extracted species information from the
 counties where the 18 studied sites were located (Fig. 1), aiming to
 represent all small mammal species along the entire elevational gradient
 (from the lowest to highest elevations) within the region. Further,
 species that were unlikely to be captured by the standardized field
 sampling, such as marmot, flying squirrel, and hare, were removed. The
 final species pool included four Orders (Eulipotyphla, Lagomorpha,
 Rodentia, and Scandentia). Due to outdated taxonomical records for some
 species, we carefully checked the species list and replaced debatable
 names with the most recent taxonomic evaluations. New species records from
 the present study were noted (Song et al. 2021), and those that did not match any known species
 were assigned temporary taxonomic identifications. Species compositions in
 sites were Hellinger-transformed to reduce the effect of zero abundances
 (Legendre and Gallagher
 2001). 2.3 Phylogenetic
 reconstruction The CYTB gene has been found to be more accurate
 at reconstructing mammalian species' phylogenetic associations
 (Tobe et al.
 2010) and is frequently
 used for small mammals’ phylogenetic studies (e.g. Bannikova et al. 2018; Koju et al. 2017;
 Liu et al. 2018). Total
 DNA was extracted from newly collected samples, and the CYTB gene was
 amplified and sequenced to rebuild the phylogeny. The DNA was extracted
 from 1-2 individuals of each morphologically distinct species from each
 site using the SQ Tissue DNA Kit (D6032, Omega Bio-tek Inc., Norcross,
 USA) following the manufacturer’s protocol. The CYTB gene was amplified
 and sequenced following Koju et al. (2017). The PCR primers for the genus Ochotona were
 L14724 and H15913 (Koju et
 al. 2017) and L14725_hsw1
 (ATG ACA TGA AAA ATC ATC GTT GT) and H15915_hsw1 (TCY CCA TTT CTG GTT TAC
 AAG ACC) for other species. The sequenced CYTB products were assembled in
 Geneious R11.1 (https://www.geneious.com/) then aligned in MEGA X
 (Kumar et al.
 2018) using MUSCLE
 (Edgar
 2004). The resulting
 alignment was verified in BLAST (https://blast.ncbi.nlm.nih.gov/Blast.cgi)
 to handle sequencing errors and misidentifications. The alignment for
 further phylogenetic analysis comprised of one complete CYTB sequence of
 each newly captured species and the CYTB sequences of species not captured
 but downloaded from GenBank. The field numbers and GenBank accession
 numbers are provided in Appendix 2. The phylogenetic tree of the total
 species pool was reconstructed in the IQ-TREE web server
 (http://iqtree.cibiv.univie.ac.at/;
 Trifinopoulos et al. 2016)
 using Maximum Likelihood (ML) with 10 000 bootstrap
 replicates. 2.4 Traits used to quantify functional
 diversity Traits were classified into morphology, resource
 acquisition, and habitat affinity combinations. Morphological
 characteristics, including body size and extremities (e.g., ears, limbs,
 and tail), are important to cold adaption (Alhajeri et al. 2020; Blackburn and Hawkins
 2004), a prominent
 constraint in alpine areas. The morphological traits, represented by BW,
 HB, TL, HF, and EL, were measured in the field as numerical variables; BW
 and HB were represented by the mean values of recorded individuals, while
 TL, HF, and EL were transformed as proportions of HB (Du et al. 2017). Resource acquisition traits included activity
 cycle, trophic level, diet breadth, and diet composition extracted from
 the COMBINE dataset (Soria
 et al. 2021). Habitat
 affinity traits were represented by habitat breadth, habitat occupations,
 fossoriality, and foraging stratum obtained from Ding et al. (2022). Habitat breadth determines the number of
 available habitat types, and habitat occupation refers to the availability
 of specific habitat types for the species. Fossoriality and foraging
 stratum represented spatial separation in a given habitat, i.e.,
 underground, above ground, or arboreal. Among all traits, diet composition
 and habitat occupation comprised 3 (vertebrate, invertebrate, and plants)
 and 6 (forest, shrublands, grassland, wetlands, rocky areas, and
 artificial) subdivisions, respectively. Diet composition included the
 percentage proportion of different food types (Soria et al. 2021), and habitat occupation included binary levels
 of availability (available =1 and unavailable = 0) of a particular habitat
 type for the species (Ding
 et al. 2022). Traits were
 classified into nominal, circular, or quantitative types
 (Magneville et al.
 2021).
description: All statistical analyses and
 result illustrations were processed in the R 4.1.0
 environment. Initial data and R code were
 provided. The uploaded files
 include: 1. overall_trait.R: R code to calculate observed
 phylogenetic and overall trait functional diversity indices, null models,
 and plots. 2. morpho_trait.R: R code to
 calculate observed morphological trait functional diversity indices, null
 models, and plots. 3. die_trait.R: R code to calculate observed
 resource acquisition trait functional diversity indices, null models, and
 plots. 4. habit_trait.R: R code to calculate
 observed habitat affinity trait functional diversity indices, null models,
 and plots. 5. lme.R: R code to calculate correlation
 coefficients between diversity metrics and generating linear mixed-effects
 models. 6. pool.sp.csv: species by site matrix of the
 regional species pool 7. pooltree: netwick file of the
 phylogenetic tree used to calculate phylogenetic diversity and tests
 phylogenetic signals. 8. reduced_traits.csv: trait data
 of the regional species pool used to calculate functional diversity
 metrics. 9. tr_cat.csv: sheet used to classify the
 traits into nominal, circular, or quantitative types, which was required
 in the ‘funct.dist’ and ‘quality.fspaces’ in ‘mFD’ package. 
 10. meta-redueced.csv: elevational gradients used to
 generate linear mixed-effects models.
 11. README_file.txt: description for the variable in each data
 set.