Using species distributions models for designing conservation strategies of Tropical Andean biodiversity under climate change

Ramírez-Villegas, Julián; Cuesta, Francisco; Devenish, Christian; Peralvo, Manuel; Jarvis, Andy; Arnillas, Carlos Alberto

doi:10.1016/j.jnc.2014.03.007

Cited by 146 publications

(94 citation statements)

References 89 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…However, conservation programs are not considered important by the government and have therefore not received economic support, resulting in the low representation of wild crop relatives in germplasm banks (Castañeda‐Álvarez et al., 2016; Maxted et al., 2016). In addition, it is necessary to know the conditions of in situ conservation to conduct long‐term monitoring because of the advantages of low maintenance costs and the dynamic evolution of populations that this type of conservation offers (Acosta‐Díaz et al., 2015; Ramírez‐Villegas et al., 2014; Smýkal et al., 2015). Furthermore, we must consider the threats to wild germplasm caused by agriculture, urbanization, invasive species, contamination, mining, and climate change.…”

Section: Discussionmentioning

confidence: 99%

Climatic adaptation and ecological descriptors of wild beans from Mexico

Cerda-Hurtado

Máyek-Pérez

Muruaga‐Martínez

et al. 2018

Ecology and Evolution

View full text Add to dashboard Cite

Despite its economic, social, biological, and cultural importance, wild forms of the genus Phaseolus are not well represented in germplasm banks, and they are at great risk due to changes in land use as well as climate change. To improve our understanding of the potential geographical distribution of wild beans (Phaseolus spp.) from Mexico and support in situ and ex situ conservation programs, we determined the climatic adaptation ranges of 29 species and two subspecies of Phaseolus collected throughout Mexico. Based on five biotic and 117 abiotic variables obtained from different databases—WorldClim, Global‐Aridity, and Global‐PET—we performed principal component and cluster analyses. Germplasm was distributed among 12 climatic types from a possible 28. The general climatic ranges were as follows: 8–3,083 m above sea level; 12.07–26.96°C annual mean temperature; 10.33–202.68 mm annual precipitation; 9.33–16.56 W/m2 of net radiation; 11.68–14.23 hr photoperiod; 0.06–1.57 aridity index; and 10–1,728 mm/month of annual potential evapotranspiration. Most descriptive variables (25) clustered species into two groups: One included germplasm from semihot climates, and the other included germplasm from temperate climates. Species clustering showed 45% to 54% coincidence with species previously grouped using molecular data. The species P. filiformis, P. purpusii, and P. maculatus were found at low‐humidity locations; these species could be used to improve our understanding of the extreme aridity adaptation mechanisms used by wild beans to avoid or tolerate climate change as well as to introgress favorable alleles into new cultivars adapted to hot, dry environments.

show abstract

Section: Discussionmentioning

confidence: 99%

Climatic adaptation and ecological descriptors of wild beans from Mexico

Cerda-Hurtado

Máyek-Pérez

Muruaga‐Martínez

et al. 2018

Ecology and Evolution

View full text Add to dashboard Cite

show abstract

“…We estimated species diversity using the Shannon‐Weaver index (H`), and species turnover rate as a measure of community change, with the formula: (Species gain + species lost)/(initial richness + species gain) × 100 (in 11 years), following Ramirez‐Villegas et al (). Plant cover, Shannon diversity index, and species turnover were only calculated at plot scale, where species abundance data was more accurate (Zimmer, Meneses, Rabatel, Soruco, & Anthelme, ).…”

Section: Methodsmentioning

confidence: 99%

Vegetation trends over eleven years on mountain summits in NW Argentina

Carilla

Halloy

Cuello

et al. 2018

Ecology and Evolution

Self Cite

View full text Add to dashboard Cite

As global climate change leads to warmer and dryer conditions in the central Andes, alpine plant communities are forced to upward displacements following their climatic niche. Species range shifts are predicted to have major impacts on alpine communities by reshuffling species composition and abundances. Using a standardized protocol, we surveyed alpine plant communities in permanent plots on four high Andean summits in NW Argentina, which range from 4,040 to 4,740 m a.s.l. After a baseline survey in 2006–2008, we resurvey the same plots in 2012, and again in 2017. We found a significant decrease in plant cover, species richness, and diversity across the elevation gradient in the three censuses and a strong decrease in soil temperature along the elevation gradient. We found a high plant community turnover (37%–49%) among censuses, differentiating according to summits and aspects; major changes of community turnover were observed in the lowest summit (49%) and on the northern (47%) and western (46%) aspects. Temporal patterns in community changes were represented by increases in plant cover in the highest summit, in species richness in the lower summit, and in diversity (Shannon index) in the four summits, over time, together with increase in small herbs and non‐tussock grasses. We suggest that the observed trend in plant community dynamics responds to short‐term temperature and precipitation variability, which is influenced by El Niño Southern Oscillation (ENSO), and due to time lags in plant community response, it may take much longer than one decade for the observed trends to become stables and statistically significant. Our study provides an important foundation for documenting more profound changes in these subtropical alpine plant communities as global climate change continues.

show abstract

“…For example, Johnson et al (2005) modeled the potential distribution for three arctic species and evaluated the effect of mineral exploration on habitat suitability in an effort to inform management. Species distribution modeling is also an important tool for evaluating the effect of environmental and climatic changes on habitat use (Alamgir, Mukul, & Turton, 2015; Ramirez-Villegas et al, 2014). Additionally, predicting the spatial distribution of a species has also played a role in understanding the distribution of important animal diseases (Brook & McLachlan, 2009; Dugal, Beest, Wal, & Brook, 2013; Morris, Proffitt, Asher, & Blackburn, 2015; Proffitt et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Mapping resource selection functions in wildlife studies: Concerns and recommendations

2016

View full text Add to dashboard Cite

Predicting the spatial distribution of animals is an important and widely used tool with applications in wildlife management, conservation, and population health. Wildlife telemetry technology coupled with the availability of spatial data and GIS software have facilitated advancements in species distribution modeling. There are also challenges related to these advancements including the accurate and appropriate implementation of species distribution modeling methodology. Resource Selection Function (RSF) modeling is a commonly used approach for understanding species distributions and habitat usage, and mapping the RSF results can enhance study findings and make them more accessible to researchers and wildlife managers. Currently, there is no consensus in the literature on the most appropriate method for mapping RSF results, methods are frequently not described, and mapping approaches are not always related to accuracy metrics. We conducted a systematic review of the RSF literature to summarize the methods used to map RSF outputs, discuss the relationship between mapping approaches and accuracy metrics, performed a case study on the implications of employing different mapping methods, and provide recommendations as to appropriate mapping techniques for RSF studies. We found extensive variability in methodology for mapping RSF results. Our case study revealed that the most commonly used approaches for mapping RSF results led to notable differences in the visual interpretation of RSF results, and there is a concerning disconnect between accuracy metrics and mapping methods. We make 5 recommendations for researchers mapping the results of RSF studies, which are focused on carefully selecting and describing the method used to map RSF studies, and relating mapping approaches to accuracy metrics.

show abstract

Using species distributions models for designing conservation strategies of Tropical Andean biodiversity under climate change

Cited by 146 publications

References 89 publications

Climatic adaptation and ecological descriptors of wild beans from Mexico

Climatic adaptation and ecological descriptors of wild beans from Mexico

Vegetation trends over eleven years on mountain summits in NW Argentina

Mapping resource selection functions in wildlife studies: Concerns and recommendations

Contact Info

Product

Resources

About