This layer shows the population counts in Tucson by neighborhood, aggregated from block level data, between 2010-2019. Population density is expressed as persons per square mile. For questions, contact GIS_IT@tucsonaz.gov. The data shown is from Esri's 2019 Updated Demographic estimates.Esri's U.S. Updated Demographic (2019/2024) Data - Population, age, income, sex, race, home value, and marital status are among the variables included in the database. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies.Additional Esri Resources:Esri DemographicsU.S. 2019/2024 Esri Updated DemographicsEssential demographic vocabularyPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

Species interactions such as facilitation and competition play a crucial role in driving species range shifts. However, density-dependence as a key feature of these processes has received little attention in both empirical and modelling studies. Herein, we used a novel, individual-based treeline model informed by rich in-situ observations to quantify the contribution of density-dependent species interactions to alpine treeline dynamics, an iconic biome boundary recognized as an indicator of global warming. We found that competition and facilitation dominate in dense versus sparse vegetation scenarios, respectively. The optimal balance between these two effects was identified at an intermediate vegetation thickness where the treeline elevation was the highest. Further, treeline shift rates decreased sharply with vegetation thickness and the associated transition from positive to negative species interactions. We thus postulate that vegetation density must be considered when modeling spec..., This dataset includes the code of the Sygera Treeline Model and the raw data for model results for validation and model experiments. The Sygera Treeline Model is a new individual-based treeline model, which shares some key features and processes with the polar treeline simulator LAVESI (v. 1.01) (Kruse et al. 2016), and two classical forest gap models, FORCLIM (Bugmann 1994) and JABOWA (Botkin 1993). It is designed to explore how alpine treeline formation and dynamics under different vegetation scenarios with the background of climate change. In this model, trees were placed on a hypothetical mountain slope where the temperature gradually decreased with elevation, and had been impacted by alpine vegetation. All trees experience three physiological processes of establishment, growth, and mortality, and these processes were influenced by abiotic (temperature, drought) and biotic (intra- and interspecific interaction) environmental factors. The another file includes the the raw data file..., , # Density-dependent species interactions modulate alpine treeline shifts

Xiangyu Zheng1,2, Flurin Babst3,4, J. Julio Camarero5, Xiaoxia Li1, Xiaoming Lu1, Shan Gao1, Shalik Ram Sigdel1, Yafeng Wang6, Haifeng Zhu1, Eryuan Liang1*

1State Key Laboratory of Tibetan Plateau Earth System, Environment and Resources (TPESER), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China

2University of Chinese Academy of Sciences, Beijing 100049, China;

3School of Natural Resources and the Environment, University of Arizona, Tucson, AZ 85721;

4Laboratory of Tree-Ring Research, University of Arizona, Tucson, AZ 85721

5Instituto Pirenaico de EcologÃa (IPE-CSIC), 50059 Zaragoza, Spain

6College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China

The file of “model code†is the code of the Sygera Treeline Model v1.0.

Containing files:

1. Source code and header files: "....cpp" and "....h" and the makefile "Makefile"

2. Parame...