An Unlikely Movable Feast in a Desert Hydrological System: Why Do Life Cycles Matter

Rodríguez‐Sánchez, Mariana; Pisanty, Irene; Mandujano, María C.; Flores‐Olvera, Hilda; Almaguer, Ana Karen

doi:10.1007/978-3-030-44963-6_17

Cited by 6 publications

(4 citation statements)

References 27 publications

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“…Underestimation of survival probabilities due to imperfect detection of individuals during field surveys could lead to wrong conclusions about the population status (Alexander et al, 2009; Kéry & Gregg, 2003; Shefferson et al, 2001) or evolutionary trends of plant species (e.g., in studies that aim to quantify the strength of natural selection; Waller & Svensson, 2016). The consequences can be serious, especially if the research is focused on rare or endangered species (such as M. hernandezii , N. macrocephala , and G. lagenophora ; Esparza‐Olguín et al, 2005; Ureta & Martorell, 2009), species that act as indicators of environmental change (such as F. chlorifolia ; Pisanty et al, 2020; Rodríguez‐Sánchez et al, 2020), or species that support biotic interactions (such as C. tenuiflora which is a hemiparasitic plant; Granados‐Hernández et al, 2021).…”

Section: Discussionmentioning

confidence: 99%

“…Unexpectedly, most of the significant differences between demographic estimates (obtained without considering detection probabilities) and true parameter values, along with substantially large biases, occurred in two species of intermediate size ( F. chlorifolia : 0.3–3 m tall, G. lagenophora : 0.6–0.9 m tall). Their large biases were caused by substantially low detectability that in turn resulted from limited access to individuals (both species grow in deep cracks and sinkholes; Rodríguez‐Sánchez et al, 2020; Salazar, 2009). In summary, the magnitude of bias in demographic estimates caused by ignoring detection probabilities does not depend on the size of the different plant species, but is instead related to particular ecological characteristics of their habitats, such as topography and density of the surrounding vegetation.…”

Section: Discussionmentioning

confidence: 99%

“…Based on previous knowledge about the life cycle and reproductive phenology of each species (Esparza‐Olguín et al, 2005; Granados‐Hernández et al, 2021; Pisanty et al, 2020; Rodríguez‐Sánchez et al, 2020; Ureta & Martorell, 2009), as well as on field observations, we constructed life cycle graphs for the five species (a general life cycle graph is depicted in Figure 1a and species‐specific life cycle graphs for all five species are shown in Figures S1–S5). From one sampling occasion to the next, individuals can survive with state‐specific probability S , and if they survive, they can make a transition to a different state or size class (i.e., transitions in strict sense: ψ AB , ψ BA , ψ BC , ψ CB , ψ CA , and ψ AC in Figure 1a) or, alternatively, they can remain in the same state or size class (i.e., stasis: ψ AA , ψ BB , and ψ CC in Figure 1a).…”

Section: Methodsmentioning

confidence: 99%

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Estimation of demographic parameters of some plant species accounting for imperfect detection probabilities

et al. 2023

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Detection probability (p) in plants is imperfect in natural conditions due to several factors. This imperfect detectability is rarely accounted for in the estimation of demographic parameters, such as survival probabilities (S) or transition rates between different life states or size classes (ψ), which may result in inaccurate quantitative information about plant populations. In this study, we used previously collected data of five plant species belonging to different families with contrasting life forms and habitats (Flaveria chlorifolia, Mammillaria hernandezii, Neobuxbaumia macrocephala, Govenia lagenophora, and Castilleja tenuiflora), data simulations, multi‐state models (a demographic tool that explicitly accounts for p), and direct estimation of survival and transition rates (i.e., assuming perfect detection) to identify in which species, states, or demographic parameters the bias caused by ignoring our imperfect detectability is more severe. Detection was imperfect (p < 1) for all our study species. In general, ignoring detection probabilities yielded underestimated survival and transition rates in all five species. Biases caused by assuming perfect detection were also large and significant, mainly in inconspicuous life states and size classes, such as seedlings and dry individuals. In contrast, considering detection probabilities resulted in fewer underestimated survival and transition rates, with smaller and mostly nonsignificant biases. Intriguingly, some transitions were overestimated even when accounting for detection probabilities. Our findings highlight the importance of considering that detection of most plant species is imperfect in the field, even in species that are apparently conspicuous, to avoid incorrect inferences about plant populations.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Estimation of demographic parameters of some plant species accounting for imperfect detection probabilities

et al. 2023

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“…F. chloraefolia is a Type I C 3 –C 4 species that has been grown and studied under controlled conditions for decades (e.g., Powell 1978 ; Holaday et al 1984 ; Holaday and Chollet 1984 ; Reed and Chollet 1985 ; Bauwe and Chollet 1986 ; Edwards and Ku 1987 ; Chastain and Chollet 1989 ; Ku et al 1991 ; Dai et al 1996 ; Kopriva et al 1996 ; Pfündel and Pfeffer 1997 ; Leonardos and Grodzinski 2000 , 2003 ; Engelmann et al 2003 ; Huxman and Monson 2003 ; Westhoff and Gowik 2004 ; McKown et al 2005 ; McKown and Dengler 2007 ; Kocacinar et al 2008 ; Vogan and Sage 2011 ; Schulze et al 2013 ; Aldous et al 2014 ; Mallmann et al 2014 ; Way et al 2014 ; Stata et al 2016 ; Lyu et al 2021 ). However, there are very few studies of this species under field conditions (e.g., Van Auken et al 2007 ; Peralta-García et al 2016 ; Ochoterena et al 2020 ; Peralta-García et al 2020 ; Pisanty et al 2020 ; Rodríguez-Sánchez et al 2020 ). We compared the photosynthetic performance of a greenhouse-grown research population at the Carnegie Institution in Stanford, CA to that of naturally-occurring populations at the Blue Hole Ciénega in Guadalupe County, NM (34° 56ʹ 8ʺ N, 104° 40ʹ 30ʺ W), and the Diamond Y Spring Preserve in Pecos County, TX (31° 0ʹ 36ʺ N, 102° 55ʹ 5ʺ W).…”

Section: Model Applicationsmentioning

confidence: 99%

The limiting factors and regulatory processes that control the environmental responses of C3, C3–C4 intermediate, and C4 photosynthesis

Johnson

Field

2021

Oecologia

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Here, we describe a model of C3, C3–C4 intermediate, and C4 photosynthesis that is designed to facilitate quantitative analysis of physiological measurements. The model relates the factors limiting electron transport and carbon metabolism, the regulatory processes that coordinate these metabolic domains, and the responses to light, carbon dioxide, and temperature. It has three unique features. First, mechanistic expressions describe how the cytochrome b6f complex controls electron transport in mesophyll and bundle sheath chloroplasts. Second, the coupling between the mesophyll and bundle sheath expressions represents how feedback regulation of Cyt b6f coordinates electron transport and carbon metabolism. Third, the temperature sensitivity of Cyt b6f is differentiated from that of the coupling between NADPH, Fd, and ATP production. Using this model, we present simulations demonstrating that the light dependence of the carbon dioxide compensation point in C3–C4 leaves can be explained by co-occurrence of light saturation in the mesophyll and light limitation in the bundle sheath. We also present inversions demonstrating that population-level variation in the carbon dioxide compensation point in a Type I C3–C4 plant, Flaveriachloraefolia, can be explained by variable allocation of photosynthetic capacity to the bundle sheath. These results suggest that Type I C3–C4 intermediate plants adjust pigment and protein distributions to optimize the glycine shuttle under different light and temperature regimes, and that the malate and aspartate shuttles may have originally functioned to smooth out the energy supply and demand associated with the glycine shuttle. This model has a wide range of potential applications to physiological, ecological, and evolutionary questions.

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Morphological and Phenological Variation in Samolus ebracteatus var. coahuilensis in Different Environments in the Churince System, Cuatro Ciénegas Basin (Coahuila)

Cervantes-Campero.

Pisanty

Mandujano

2020

Plant Diversity and Ecology in the Chihuahuan Desert

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An Unlikely Movable Feast in a Desert Hydrological System: Why Do Life Cycles Matter

Cited by 6 publications

References 27 publications

Estimation of demographic parameters of some plant species accounting for imperfect detection probabilities

Estimation of demographic parameters of some plant species accounting for imperfect detection probabilities

The limiting factors and regulatory processes that control the environmental responses of C3, C3–C4 intermediate, and C4 photosynthesis

Morphological and Phenological Variation in Samolus ebracteatus var. coahuilensis in Different Environments in the Churince System, Cuatro Ciénegas Basin (Coahuila)

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