DOI: 10.5061/dryad.hmgqnk9g7
title: Date From: The myriad of complex demographic responses of terrestrial mammals to climate change and gaps of knowledge: A global analysis

description: Approximately 25% of mammals are currently threatened with extinction, a
 risk that is amplified under climate change. Species persistence under
 climate change is determined by the combined effects of climatic factors
 on multiple demographic rates (survival, development, reproduction), and
 hence, population dynamics. Thus, to quantify which species and regions on
 Earth are most vulnerable to climate-driven extinction, a global
 understanding of how different demographic rates respond to climate is
 urgently needed.  Here, we perform a systematic review of
 literature on demographic responses to climate, focusing on terrestrial
 mammals, for which extensive demographic data are available.  To
 assess the full spectrum of responses, we synthesize information from
 studies that quantitatively link climate to multiple demographic rates. We
 find only 106 such studies, corresponding to 87 mammal species. These 87
 species constitute &lt; 1% of all terrestrial mammals. Our synthesis
 reveals a strong mismatch between the locations of demographic studies and
 the regions and taxa currently recognized as most vulnerable to climate
 change. Surprisingly, for most mammals and regions sensitive to climate
 change, holistic demographic responses to climate remain unknown. At the
 same time, we reveal that filling this knowledge gap is critical as the
 effects of climate change will operate via complex demographic mechanisms:
 a vast majority of mammal populations display projected increases in some
 demographic rates but declines in others, often depending on the specific
 environmental context, complicating simple projections of population
 fates.  Assessments of population viability under climate change
 are in critical need to gather data that account for multiple demographic
 responses, and coordinated actions to assess demography holistically
 should be prioritized for mammals and other taxa.
description: For each mammal species
 <i>i</i> with available life-history information, we searched
 SCOPUS for studies (published before 2018) where the title, abstract, or
 keywords contained the following search terms:  <i>Scientific species name<sub>i</sub></i> AND (demograph* OR population OR life-history OR "life history" OR model) AND (climat* OR precipitation OR rain* OR temperature OR weather) AND (surv* OR reprod* OR recruit* OR brood OR breed* OR mass OR weight OR size OR grow* OR offspring OR litter OR lambda OR birth OR mortality OR body OR hatch* OR fledg* OR productiv* OR age OR inherit* OR sex OR nest* OR fecund* OR progression OR pregnan* OR newborn OR longevity). We used the R package <i>taxize </i>(Chamberlain and Szöcs 2013)<i><sup> </sup></i>to resolve discrepancies in scientific names or taxonomic identifiers and, where applicable, searched SCOPUS using all scientific names associated with a species in the Integrated Taxonomic Information System (ITIS; http://www.itis.gov). We did not extract information on demographic-rate-climate relationships if: A study reported on single age or stage-specific demographic rates (e.g., Albon <i>et al</i>. 2002; Rézoiki <i>et al</i>. 2016) A study used an experimental design to link demographic rates to climate variation (e.g., Cain <i>et al</i>. 2008) A study considered the effects of climate only indirectly or qualitatively. In most cases, this occurred when demographic rates differed between seasons (e.g., dry vs. wet season) but were not linked explicitly to climatic factors (e.g., varying precipitation amount between seasons) driving these differences (e.g., de Silva <i>et al</i>. 2013; Gaillard <i>et al</i>. 2013). We included several studies of the same population as different studies assessed different climatic variables or demographic rates or spanned different years (e.g., for <i>Rangifer tarandus platyrhynchus</i>, Albon <i>et al</i>. 2017; Douhard <i>et al</i>. 2016).   We note that we can miss a potentially relevant study if our search terms were not mentioned in the title, abstract, or keywords. To our knowledge, this occurred only once, for <i>Mastomys natalensis</i> (we included the relevant study [Leirs <i>et al</i>. 1997] into our review after we were made aware that it assesses climate-demography relationships in the main text). Lastly, we checked for potential database bias by running the search terms for a subset of nine species in Web of Science. The subset included three species with &gt; three climate-demography studies published and available in SCOPUS (<i>Rangifer tarandus</i>, <i>Cervus elaphus</i>, <i>Myocastor coypus</i>); three species with only one climate-demography study obtained from SCOPUS (<i>Oryx gazella</i>, <i>Macropus rufus</i>, <i>Rhabdomys pumilio</i>); and another three species where SCOPUS did not return any published study (<i>Calcochloris obtusirostris</i>, <i>Cynomops greenhalli</i>, <i>Suncus remyi</i>). Species in the three subcategories were randomly chosen. Web of Science did not return additional studies for the three species where SCOPUS also failed to return a potentially suitable study. For the remaining six species, the total number of studies returned by Web of Science differed, but the same studies used for this review were returned, and we could not find any additional studies that adhered to our extraction criteria. <i>Description of key collected data</i> From all studies quantitatively assessing climate-demography relationships, we extracted the following information: Geographic location - The center of the study area was always used. If coordinates were not provided in a study, we assigned coordinates based on the study descriptions of field sites and data collection. Terrestrial biome - The study population was assigned to one of 14 terrestrial biomes (Olson <i>et al.</i> 2001)<sup> </sup>corresponding to the center of the study area. As this review is focused on general climatic patterns affecting demographic rates, specific microhabitat conditions described for any study population were not considered. Climatic driver - Drivers linked to demographic rates were grouped as either local/regional precipitation & temperature values or derived indices (e.g., ENSO, NAO). The temporal extent (e.g., monthly, seasonal, annual, etc.) and aggregation type (e.g., minimum, maximum, mean, etc.) of drivers was also noted. Demographic rate modeled - To facilitate comparisons, we grouped the demographic rates into either survival, reproductive success (<i>i.e.</i>, whether or not reproduction occurre, reproductive output (<i>i.e.</i>, number or rate of offspring production), growth (including stage transitions), or condition that determines development (<i>i.e., </i>mass or size).  Stage or sex modeled - We retrieved information on responses of demographic rates to climate for each age class, stage, or sex modeled in a given study. Driver effect - We grouped effects of drivers as positive (<i>i.e.,</i> increased demographic rates), negative (<i>i.e.</i>, reduced demographic rate), no effect, or context-dependent (e.g., positive effects at low population densities and now effect at high densities). We initially also considered nonlinear effects (e.g., positive effects at intermediate values and negative at extremes of a driver), but only 4 studies explicitly tested for nonlinear effects, by modelling squared or cubic climatic drivers in combination with driver interactions. We therefore considered nonlinear demographic effects as context dependent.    Driver interactions - We noted any density dependence modeled and any non-climatic covariates included (as additive or interactive effects) in the demographic-rate models assessing climatic effects. Future projections of climatic driver - In studies that indicated projections of drivers under climate change, we noted whether drivers were projected to increase, decrease, or show context-dependent trends. For studies that provided no information on climatic projections, we quantified projections as described in <i>Detailed description of climate-change projections </i>below (see also climate_change_analyses_mammal_review.R).
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