Variations in Surface Urban Heat Island and Urban Cool Island Intensity:A Review Across Major Climate Zones

The climate has an impact on the urban thermal environment,and the magnitude of the surface urban heat island(SUHI)and urban cool island(UCI)vary across the world’s climatic zones.This literature review investigated:1)the variations in the SUHI and UCI intensity under different climatic backgrounds,and 2)the effect of vegetation types,landscape composition,urban configuration,and water bodies on the SUHI.The SUHI had a higher intensity in tropical(Af(tropical rainy climate,Köppen climate classification),Am(tropical monsoon climate),subtropical(Cfa,subtropical humid climate),and humid continental(Dwa,semi-humid and semi-arid monsoon climate)climate zones.The magnitude of the UCI was low compared to the SUHI across the climate zones.The cool and dry Mediterranean(Cfb,temperate marine climate;Csb,temperate mediterranean climate;Cfa)and tropical climate(Af)areas had a higher cooling intensity.For cities with a desert climate(BWh,tropical desert climate),a reverse pattern was found.The difference in the SUHI in the night-time was greater than in the daytime for most cities across the climate zones.The extent of green space cooling was related to city size,the adjacent impervious surface,and the local climate.Additionally,the composition of urban landscape elements was more significant than their configuration for sustaining the urban thermal environment.Finally,we identified future research gaps for possible solutions in the context of sustainable urbanization in different climate zones.

Land tenure and landscape change:a comparison of public-private lands in the southern High Plains

Introduction:Long-term drought in the southern Great Plains increases the vulnerability of coupled human-environment systems at a variety of scales.Developing better understandings of the dynamics at regional scales will become increasingly important as long-established land-use regimes break down in the face of climate change,resource depletion,and evolving governance.To demonstrate differential vulnerability during drought periods,this study hypothesized that observed increases in woody vegetation in grasslands would vary across land-tenure regimes.We argue that differences in State Trust Land governance,in part,lead to differential land management practices that contribute to landscape change.Methods:The study area encompasses adjacent counties,Cimarron County in Oklahoma and Union County in New Mexico,with similar climate variability and agricultural economies.We analyzed National Land Cover Database(NLCD)land-cover maps from 1992 and 2011 to assess changes in landscape composition and structure between 1992 and 2011.Results:During both years under consideration,each county in the study region,across various land-tenure regimes,was dominated by herbaceous vegetation.However,there were changes in both composition and structure across the whole study area,in particular losses of herbaceous vegetation and increases in woody vegetation.The greatest gains in woody vegetation occurred in State Trust Lands of Cimarron County.Overall,the data suggest a fragmentation of herbaceous vegetation and a coalescing of shrubland patches.Conclusions:Research about the influence of land tenure on land management decisions,specifically the role of State Trust Land leases in overgrazing,informs the broader context of drought management in the southern Great Plains.Recommendations include continued research to highlight the specific mechanisms of land-tenure governance that drive landscape change.

Predicting wild boar damages to croplands in a mosaic of agricultural and natural areas

Crop damages by wildlife is a frequent form of human-wildlife conflict. Identifying areas where the risk of crop damages is highest is pivotal to set up preventive measures and reduce conflict. Species distribution models are routinely used to predict species distribution in response of environmental changes. The aim of this paper was assessing whether species distribution models can allow to identify the areas most at risk of crop damages, helping to set up management strategies aimed at the mitigation of human-wildlife conflicts. We obtained data on wild boar Sus scrofa damages to crops in the Alta Murgia National Park, Southern Italy, and related them to landscape features, to identify areas where the risk of wild boar damages is highest. We used MaxEnt to build species distribution models. We identified the spatial scale at which landscape mostly affects the distribution damages, and optimized the regularization parameter of models, through an information-theoretic approach based on AIC. Wild boar damages quickly increased in the period 2007-2011; cereals and legtmaes were the crops more affected. Large areas of the park have a high risk of wild boar damages. The risk of damages was related to low cover of urban areas or olive grows, intermediate values of forest cover, and high values of shrubland cover within a 2-km radius. Temporally independent validation data demonstrated that models can successfully predict damages in the future. Species distribution models can accurately identify the areas most at risk of wildlife damages, as models calibrated on data collected during only a subset of years correctly predicted damages in the subsequent year [Current Zoology 60 （2）： 170-179, 2014].