ORCID Profile
0000-0003-3362-2976
Current Organisation
Colorado State University
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Publisher: Wiley
Date: 2006
DOI: 10.1890/05-0355
Abstract: A central challenge in ecology is to understand the interplay of internal and external controls on the growth of populations. We examined the effects of temporal variation in weather and spatial variation in vegetation on the strength of density dependence in populations of large herbivores. We fit three subsets of the model ln(Nt) = a + (1 + b) x ln(N(t-1)) + c x ln(N(t-2)) to five time series of estimates (Nt) of abundance of ungulates in the Rocky Mountains, USA. The strength of density dependence was estimated by the magnitude of the coefficient b. We regressed the estimates of b on indices of temporal heterogeneity in weather and spatial heterogeneity in resources. The 95% posterior intervals of the slopes of these regressions showed that temporal heterogeneity strengthened density-dependent feedbacks to population growth, whereas spatial heterogeneity weakened them. This finding offers the first empirical evidence that density dependence responds in different ways to spatial heterogeneity and temporal heterogeneity.
Publisher: Elsevier BV
Date: 10-2008
Publisher: Elsevier BV
Date: 02-2010
Publisher: IOP Publishing
Date: 04-2020
Abstract: Rangelands are one of the Earth’s major ice-free land cover types. They provide food and support livelihoods for millions of people in addition to delivering important ecosystems services. However, rangelands are at threat from climate change, although the extent and magnitude of the potential impacts are poorly understood. Any declines in vegetation biomass and fluctuations in grazing availability would be of concern for food production and ecosystem integrity and functionality. In this study, we use a global rangeland model in combination with livestock and socio-economic datasets to identify where and to what extent rangeland systems may be at climatic risk. Overall, mean herbaceous biomass is projected to decrease across global rangelands between 2000 and 2050 under RCP 8.5 (−4.7%), while inter- (year-to-year) and intra- (month-to-month) annual variabilities are projected to increase (+21.3% and +8.2%, respectively). These averaged global estimates mask large spatial heterogeneities, with 74% of global rangeland area projected to experience a decline in mean biomass, 64% an increase in inter-annual variability and 54% an increase in intra-annual variability. Half of global rangeland areas are projected to experience simultaneously a decrease in mean biomass and an increase in inter-annual variability—vegetation trends both potentially harmful for livestock production. These regions include notably the Sahel, Australia, Mongolia, China, Uzbekistan and Turkmenistan and support 376 million people and 174 million ruminant Tropical Livestock Units. Additionally, the rangeland communities currently the most vulnerable (here, with the lowest livestock productivities and economic development levels and with the highest projected increases in human population densities) are projected to also experience the most damaging vegetation trends for livestock production. Although the capacity of rangeland systems to adapt is highly complex, analyses such as these generate some of the information required to inform options to facilitate pastoral system mitigation and adaptation strategies under climate change.
Publisher: Wiley
Date: 09-05-2022
DOI: 10.1111/GEB.13523
Abstract: Macroecological studies that require habitat suitability data for many species often derive this information from expert opinion. However, expert‐based information is inherently subjective and thus prone to errors. The increasing availability of GPS tracking data offers opportunities to evaluate and supplement expert‐based information with detailed empirical evidence. Here, we compared expert‐based habitat suitability information from the International Union for Conservation of Nature (IUCN) with habitat suitability information derived from GPS‐tracking data of 1,498 in iduals from 49 mammal species. Worldwide. 1998–2021. Forty‐nine terrestrial mammal species. Using GPS data, we estimated two measures of habitat suitability for each in idual animal: proportional habitat use (proportion of GPS locations within a habitat type), and selection ratio (habitat use relative to its availability). For each in idual we then evaluated whether the GPS‐based habitat suitability measures were in agreement with the IUCN data. To that end, we calculated the probability that the ranking of empirical habitat suitability measures was in agreement with IUCN's classification into suitable, marginal and unsuitable habitat types. IUCN habitat suitability data were in accordance with the GPS data ( 95% probability of agreement) for 33 out of 49 species based on proportional habitat use estimates and for 25 out of 49 species based on selection ratios. In addition, 37 and 34 species had a 50% probability of agreement based on proportional habitat use and selection ratios, respectively. We show how GPS‐tracking data can be used to evaluate IUCN habitat suitability data. Our findings indicate that for the majority of species included in this study, it is appropriate to use IUCN habitat suitability data in macroecological studies. Furthermore, we show that GPS‐tracking data can be used to identify and prioritize species and habitat types for re‐evaluation of IUCN habitat suitability data.
No related grants have been discovered for Randall Boone.