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Record W7056922231

Influence of the Mexican prairie dog (Cynomys mexicanus) on plant taxonomical and functional diversity and soil properties in semiarid grasslands of Mexico

2024· other· en· W7056922231 on OpenAlexaboutno aff

Bibliographic record

VenueQucosa (Saxon State and University Library Dresden) · 2024
Typeother
Languageen
FieldPhysics and Astronomy
TopicAtomic and Subatomic Physics Research
Canadian institutionsnot available
FundersInstituto Potosino de Investigación Científica y TecnológicaHelmholtz-Zentrum für UmweltforschungConsejo Nacional de Ciencia y TecnologíaDeutscher Akademischer AustauschdienstRufford Foundation
KeywordsBiodiversityThreatened speciesExclosureGrasslandEndangered speciesVegetation (pathology)Habitat
DOInot available

Abstract

fetched live from OpenAlex

Research in grassland ecosystems worldwide has highlighted the crucial role many burrowing herbivore mammals provide as so-called “ecosystem engineers”. Many of these examples come from North America and have mostly been focused on Prairie Dogs (Cynomys sp.), which, due to their burrowing and grazing activities, are considered as a species of high ecological importance. Multiple studies have shown that their loss reduces grassland ecosystem functions and that their activities increase plant, arthropod, bird and mammal biodiversity, grassland heterogeneity, provide benefits to cattle, among many other key ecological roles. However, prairie dog species are distributed throughout multiple landscapes in North America, and most of the studies have been on mixed prairie grasslands. It is therefore not surprising that, when comparing the effects of different prairie dog species across ecoregions, the role of prairie dogs is not as clear and results vary, depending on spatial context, type of grasslands, climate and environmental conditions. Yet, grasslands are considered as some of the most highly threatened ecosystems, having high rates of conversion, desertification and biodiversity loss. Therefore, it is imperative to understand the effects prairie dog species have on the ecosystem. In this thesis, I focus on the Mexican prairie dog (C. mexicanus), a species in drastic decline due to habitat loss, caused by agriculture, overgrazing, human settlement, fragmentation, diseases (e.g. plague) and past eradication programs. C. mexicanus is considered endangered by the IUCN red list of threatened species and The Convention of International Trade in Endangered Species of Wild Fauna and Flora. It is also endemic to the Grassland Priority Conservation Area (GPCA) of El Tokio, located in Northeast Mexico within the Chihuahuan desert ecoregion and designated as a GPCA by the Commission for Environmental Cooperation (a cooperation between Canada, U.S. and Mexico) in 2009. Grasslands within GPCA El Tokio are highly fragmented as a result of many years of intense agricultural practices and other anthropogenic activities and around 90% of the original grasslands have been lost. However, it is considered an area of ecological importance due to its unique vegetation and edaphic associations, as well as being a key habitat for migratory birds. Up until now, very few studies have explored the role C. mexicanus has on plant taxonomical diversity and soil properties. Moreover, no studies focusing on prairie dogs have looked into the effect the species has on plant functional diversity or soil properties. Furthermore, GPCA El Tokio is a data-scarce area. Therefore, at this point, basic information and system understanding are urgently needed in order to identify which conservation efforts are most promising and which specific sites these efforts should focus on. Understanding the influence of prairie dog disturbance on vegetation parameters (taxonomic and functional), soil properties and their interaction with environmental conditions through time, will increase knowledge on the risks and vulnerability of grasslands, promoting solutions that can support grassland management. Furthermore, there is a clear gap in the literature about the varying effects of prairie dogs depending on different grassland types and environmental conditions. To study such conditions, I first classified and controlled for factors that could influence prairie dog ecosystem engineering effects addressing the following two general questions: (1) Which grassland types are present in GPCA El Tokio? (2) Do the different grassland types present in GPCA El Tokio influence prairie dog colony sizes and burrow density? When influencing factors were confirmed, I then assess the effects of prairie dog disturbance on vegetation and soil to answer the following questions: (3) Are there clear distinctions across GPCA El Tokio grassland environmental variables? (4) Do the different grassland types present in GPCA El Tokio influence prairie dog colony sizes and burrow density? To do so I selected a representative sample of sites covering the varying environmental conditions present in GPCA El Tokio grasslands, a data-driven clustering approach was used. Once clusters were defined, average burrow density was estimated from remote sensing imagery. To study vegetation measures I first, sampled plant species (92 species and 28 families and 6 traits) to obtain taxonomical and functional diversity measures, and obtained variables related to nutrient availability, carbon and climate regulation, and water regulation and purification. To study the effects on soil a total of 11 soil properties were obtained (382 samples were analyzed). Field work was done during the wet season and repeated during the dry season to obtain season variations of all measures. Soil measures were further obtained at depths of 0-10cm and 10 to 20cm. Results from the study classify GPCA El Tokio into 8 different grassland types with 4 clusters being the most dominant, named Agriculture, Arid, Calcareous, Mountain. I found agricultural grasslands had significantly lower colony sizes compared to calcareous grasslands when outliers were considered, but no differences when outliers were removed and burrow density varied depending on the grassland type, with mountain grasslands having a significantly lower burrow density compared to agricultural and calcareous grasslands. Regarding the effects of prairie dogs on vegetation and soil my findings suggest that functional metrics and community weighted mean (CWM) analyses responded to interactions between prairie dog disturbance, grassland type and season, whilst species diversity and cover measures were less sensitive to the role of prairie dog disturbance. I found weak evidence that prairie dog disturbance has a negative effect on vegetation structure, except for minimal effects on C4 and graminoid cover, but which depended mainly on season. Grassland type and season explained most of the effects on plant functional and taxonomic diversity as well as CWM traits. In the case of soil properties WOP grasslands tended to have higher nutrient availability than WP grasslands. However, mounds played a key role within WP grasslands. Mounds reduce compaction and increase nutrient levels of soil organic carbon, nitrogen, potassium, magnesium, and phosphorus. Such an effect was particularly present in calcareous and arid grasslands, and in many cases the effect was enhanced under wet conditions. In general, the effect of disturbance on soil property changes was dependent on environmental conditions. Overall, my study shows evidence that grassland type and season have a stronger effect than prairie dog disturbance on the vegetation of this short-grass, water-restricted grassland ecosystem.:3 TABLE OF CONTENTS Declaration of conformity 2 1 Acknowledgments 3 2 Extended Summary 5 4 List of Figures 11 5 List of Tables 13 1 Introduction 1 1.1 Importance of grasslands 1 1.2 Grassland conservation and ecosystem engineers 2 1.3 Prairie dogs: ecosystem engineers of grasslands in North America 3 1.4 Distribution of prairie dogs across North American grasslands 6 1.5 Current threats and conservation of the Mexican prairie dog C. mexicanus 7 1.6 Research questions, aims and objectives 9 2 Scientific background 13 2.1 Differences in grassland definitions and classifications 13 2.2 Dryland biases in grassland research 13 2.3 Research gaps on C. mexicanus 15 2.4 Functional diversity and disturbance 16 2.5 Soil complexity and limited research 17 3 Study Area: Grassland Priority Conservation Area of El Tokio 19 3.1 General overview 19 3.2 Bioregions, geology, topography and soils 20 3.3 Climate 23 3.4 Ecoregions, Land cover and Biodiversity 24 3.5 Anthropogenic activities and environmental issues 28 4 Assessing and classifying factors that could influence prairie dog ecosystem engineering effects 31 4.1 Data-driven identification of grassland types 33 4.1.1 Introduction 33 4.1.2 Methods 33 4.1.3 Results 36 4.1.4 Discussion and conclusion 39 4.2 C. mexicanus colony trends and differences across grassland types 41 4.2.1 Introduction 41 4.2.2 Methods 42 4.2.3 Results 48 4.2.4 Discussion and conclusion 52 5 Prairie dog disturbance effects on vegetation and soil across different grassland types and seasons 55 5.1 General methodology 57 5.1.1 Selection of grassland locations 57 5.1.2 Defining study sites and plots 58 5.1.3 Vegetation and soil sampling design 59 5.2 The effect of C. mexicanus on taxonomical and functional diversity across different seasons and grassland types 61 5.2.1 Introduction 61 5.2.2 Methods 63 5.2.3 Results 65 5.2.4 Discussion and conclusion 72 5.3 Soil property responses to the presence of C. mexicanus and its mounds across different grassland types, seasons and depths 77 5.3.1 Introduction 77 5.3.2 Methods 78 5.3.3 Results 81 5.3.4 Discussion and conclusion 88 6 Synthesis 95 6.1 Key findings 95 6.2 Management and Conservation opportunities 97 6.2.1 Designing management plans to suit existing environmental conditions 97 6.2.2 Functional diversity: an opportunity to identify patterns of vegetation across environmental conditions and scales. 98 6.3 Future research 99 6.3.1 Exploration of spatial and temporal effects 99 6.3.2 Mechanistic understanding of disturbance dynamics 100 6.3.3 A need for plant and soil ecological data 101 7 References 103 8 Appendix 131 8.1 Appendix 1. Prairie dog research reference list 132 8.2 Appendix 2. List of individual colonies with areas and other relevant information 140 8.3 Appendix 3. Historical and present colony data. 142 8.4 Appendix 4. Correlation results 144 8.5 Appendix 5. Top 3 models 146 8.6 Appendix 6. Species list per grassland type. 151 8.7 Appendix 7. Correspondence analysis (CA) for each grassland 154 8.8 Appendix 8. Post-hoc results 155 8.9 Appendix 9. Top 3 dominant species. 157 8.10 Appendix 10. HPD credible interval and ROPE. 159

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.453
Threshold uncertainty score0.728

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.202
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2024
Admission routes1
Has abstractyes

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