Estimating Impacts of Climate Change Policy on Land Use: An Agent-Based Modelling Approach

Agriculture is important to New Zealand’s economy. Like other primary producers, New Zealand strives to increase agricultural output while maintaining environmental integrity. Utilising modelling to explore the economic, environmental and land use impacts of policy is critical to understand the likely effects on the sector. Key deficiencies within existing land use and land cover change models are the lack of heterogeneity in farmers and their behaviour, the role that social networks play in information transfer, and the abstraction of the global and regional economic aspects within local-scale approaches. To resolve these issues we developed the Agent-based Rural Land Use New Zealand model. The model utilises a partial equilibrium economic model and an agent-based decision-making framework to explore how the cumulative effects of individual farmer’s decisions affect farm conversion and the resulting land use at a catchment scale. The model is intended to assist in the development of policy to shape agricultural land use intensification in New Zealand. We illustrate the model, by modelling the impact of a greenhouse gas price on farm-level land use, net revenue, and environmental indicators such as nutrient losses and soil erosion for key enterprises in the Hurunui and Waiau catchments of North Canterbury in New Zealand. Key results from the model show that farm net revenue is estimated to increase over time regardless of the greenhouse gas price. Net greenhouse gas emissions are estimated to decline over time, even under a no GHG price baseline, due to an expansion of forestry on low productivity land. Higher GHG prices provide a greater net reduction of emissions. While social and geographic network effects have minimal impact on net revenue and environmental outputs for the catchment, they do have an effect on the spatial arrangement of land use and in particular the clustering of enterprises.     

Model and Scenario Variations in Predicted Number of Generations of Spodoptera litura Fab. on Peanut during Future Climate Change Scenario

The present study features the estimation of number of generations of tobacco caterpillar, Spodoptera litura. Fab. on peanut crop at six locations in India using MarkSim, which provides General Circulation Model (GCM) of future data on daily maximum (T.max), minimum (T.min) air temperatures from six models viz., BCCR-BCM2.0, CNRM-CM3, CSIRO-Mk3.5, ECHams5, INCM-CM3.0 and MIROC3.2 along with an ensemble of the six from three emission scenarios (A2, A1B and B1). This data was used to predict the future pest scenarios following the growing degree days approach in four different climate periods viz., Baseline-1975, Near future (NF) -2020, Distant future (DF)-2050 and Very Distant future (VDF)—2080. It is predicted that more generations would occur during the three future climate periods with significant variation among scenarios and models. Among the seven models, 1–2 additional generations were predicted during DF and VDF due to higher future temperatures in CNRM-CM3, ECHams5 & CSIRO-Mk3.5 models. The temperature projections of these models indicated that the generation time would decrease by 18–22% over baseline. Analysis of variance (ANOVA) was used to partition the variation in the predicted number of generations and generation time of S. litura on peanut during crop season. Geographical location explained 34% of the total variation in number of generations, followed by time period (26%), model (1.74%) and scenario (0.74%). The remaining 14% of the variation was explained by interactions. Increased number of generations and reduction of generation time across the six peanut growing locations of India suggest that the incidence of S. litura may increase due to projected increase in temperatures in future climate change periods.     

Biotic Interactions in the Face of Climate Change: A Comparison of Three Modelling Approaches

Climate change is expected to alter biotic interactions, and may lead to temporal and spatial mismatches of interacting species. Although the importance of interactions for climate change risk assessments is increasingly acknowledged in observational and experimental studies, biotic interactions are still rarely incorporated in species distribution models. We assessed the potential impacts of climate change on the obligate interaction between Aeshna viridis and its egg-laying plant Stratiotes aloides in Europe, based on an ensemble modelling technique. We compared three different approaches for incorporating biotic interactions in distribution models: (1) We separately modelled each species based on climatic information, and intersected the future range overlap (‘overlap approach’). (2) We modelled the potential future distribution of A. viridis with the projected occurrence probability of S. aloides as further predictor in addition to climate (‘explanatory variable approach’). (3) We calibrated the model of A. viridis in the current range of S. aloides and multiplied the future occurrence probabilities of both species (‘reference area approach’). Subsequently, all approaches were compared to a single species model of A. viridis without interactions. All approaches projected a range expansion for A. viridis. Model performance on test data and amount of range gain differed depending on the biotic interaction approach. All interaction approaches yielded lower range gains (up to 667% lower) than the model without interaction. Regarding the contribution of algorithm and approach to the overall uncertainty, the main part of explained variation stems from the modelling algorithm, and only a small part is attributed to the modelling approach. The comparison of the no-interaction model with the three interaction approaches emphasizes the importance of including obligate biotic interactions in projective species distribution modelling. We recommend the use of the ‘reference area approach’ as this method allows a separation of the effect of climate and occurrence of host plant.     

Tolerance to Copper and to Salinity in Daphnia longispina: Implications within a Climate Change Scenario

Considering IPPC climate change scenarios, it is pertinent to predict situations where coastal ecosystems already impacted with chemical contamination became exposed to an additional stressor under a future scenario of seawater intrusion. Accordingly, the present study aimed at evaluating if a negative association between tolerance to a metal and to saltwater exists among genotypes of a freshwater organism. For this, five clonal lineages of the cladoceran Daphnia longispina O.F. Müller, exhibiting a differential tolerance to lethal levels of copper, were selected. Each clonal lineage was exposed to lethal and sublethal concentrations of sodium chloride (assumed as a protective surrogate to evaluate the toxicity of increased salinity to freshwater organisms). Mortality, time to release the first brood and total number of neonates per female were monitored and the somatic growth rate and intrinsic rate of natural increase were computed for each clonal lineage. Data here obtained were compared with their lethal responses to copper and significant negative correlations were found. These results suggest that genetically eroded populations of D. longispina, due to copper or salinity, may be particularly susceptible to a later exposure to the other contaminant supporting the multiple stressors differential tolerance.     

Incorporating Field Studies into Species Distribution and Climate Change Modelling: A Case Study of the Koomal Trichosurus vulpecula hypoleucus (Phalangeridae)

Species distribution models (SDMs) are an effective way of predicting the potential distribution of species and their response to environmental change. Most SDMs apply presence data to a relatively generic set of predictive variables such as climate. However, this weakens the modelling process by overlooking the responses to more cryptic predictive variables. In this paper we demonstrate a means by which data gathered from an intensive animal trapping study can be used to enhance SDMs by combining field data with bioclimatic modelling techniques to determine the future potential distribution for the koomal (Trichosurus vulpecula hypoleucus). The koomal is a geographically isolated subspecies of the common brushtail possum, endemic to south-western Australia. Since European settlement this taxon has undergone a significant reduction in distribution due to its vulnerability to habitat fragmentation, introduced predators and tree/shrub dieback caused by a virulent group of plant pathogens of the genus Phytophthora. An intensive field study found: 1) the home range for the koomal rarely exceeded 1 km in in length at its widest point; 2) areas heavily infested with dieback were not occupied; 3) gap crossing between patches (>400 m) was common behaviour; 4) koomal presence was linked to the extent of suitable vegetation; and 5) where the needs of koomal were met, populations in fragments were demographically similar to those found in contiguous landscapes. We used this information to resolve a more accurate SDM for the koomal than that created from bioclimatic data alone. Specifically, we refined spatial coverages of remnant vegetation and dieback, to develop a set of variables that we combined with selected bioclimatic variables to construct models. We conclude that the utility value of an SDM can be enhanced and given greater resolution by identifying variables that reflect observed, species-specific responses to landscape parameters and incorporating these responses into the model.     

The Relative Impacts of Climate and Land-Use Change on Conterminous United States Bird Species from 2001 to 2075

Species distribution models often use climate data to assess contemporary and/or future ranges for animal or plant species. Land use and land cover (LULC) data are important predictor variables for determining species range, yet are rarely used when modeling future distributions. In this study, maximum entropy modeling was used to construct species distribution maps for 50 North American bird species to determine relative contributions of climate and LULC for contemporary (2001) and future (2075) time periods. Species presence data were used as a dependent variable, while climate, LULC, and topographic data were used as predictor variables. Results varied by species, but in general, measures of model fit for 2001 indicated significantly poorer fit when either climate or LULC data were excluded from model simulations. Climate covariates provided a higher contribution to 2001 model results than did LULC variables, although both categories of variables strongly contributed. The area deemed to be “suitable” for 2001 species presence was strongly affected by the choice of model covariates, with significantly larger ranges predicted when LULC was excluded as a covariate. Changes in species ranges for 2075 indicate much larger overall range changes due to projected climate change than due to projected LULC change. However, the choice of study area impacted results for both current and projected model applications, with truncation of actual species ranges resulting in lower model fit scores and increased difficulty in interpreting covariate impacts on species range. Results indicate species-specific response to climate and LULC variables; however, both climate and LULC variables clearly are important for modeling both contemporary and potential future species ranges.     

Sentinel Nematodes of Land-Use Change and Restoration in Tallgrass Prairie

Changes in land use and the associated changes in land cover are recognized as the most important component of human-induced global change. Much attention has been focused on deforestation, but grasslands are among the most endangered ecosystems on Earth. The North American tallgrass prairie is a dramatic example, exhibiting a greater than 95% decline in historical area. Renewed interest in prairie conservation and restoration has highlighted the need for ecological indicators of disturbance and recovery in native systems, including the belowground component. The tallgrass prairie differs from the agricultural systems that have replaced it in having greater diversity and heterogeneity of resources, less physical soil disturbance (although other disturbances, such as fire and grazing, are prominent), and greater nitrogen limitation. Understanding the responses of nematode taxa to these characteristic differences is crucial to the development and improvement of community indices, but while knowledge of disturbance responses by individual taxa is accumulating, the level of necessary taxonomic resolution remains in question. Although nematode communities generally are better described for temperate grasslands than for other natural ecosystems, identification of sentinel taxa is further confounded by high levels of diversity, and both spatial and temporal heterogeneity.     

气候变化对鸟类影响：长期研究的意义

过去一个多世纪全球气候发生了明显变化,地球表面温度正在逐渐变暖。已有大量研究结果表明,鸟类已经在种群动态变化、生活史特性以及地理分布范围等方面对全球气候变化作出了相应的反应。根据全球范围内气候变化对鸟类影响的研究资料,尤其是北美和欧洲的一些长期研究项目的成果,综述了气候变化对鸟类分布范围、物候、繁殖和种群动态变化等方面的可能影响。这些长期研究项目为探讨气候变化在个体和种群的水平上如何长时间地影响鸟类提供了独特的机会,对未来中国鸟类学研究也会有所裨益。     

A Statistical Model for Regional Tornado Climate Studies

Tornado reports are locally rare, often clustered, and of variable quality making it difficult to use them directly to describe regional tornado climatology. Here a statistical model is demonstrated that overcomes some of these difficulties and produces a smoothed regional-scale climatology of tornado occurrences. The model is applied to data aggregated at the level of counties. These data include annual population, annual tornado counts and an index of terrain roughness. The model has a term to capture the smoothed frequency relative to the state average. The model is used to examine whether terrain roughness is related to tornado frequency and whether there are differences in tornado activity by County Warning Area (CWA). A key finding is that tornado reports increase by 13% for a two-fold increase in population across Kansas after accounting for improvements in rating procedures. Independent of this relationship, tornadoes have been increasing at an annual rate of 1.9%. Another finding is the pattern of correlated residuals showing more Kansas tornadoes in a corridor of counties running roughly north to south across the west central part of the state consistent with the dryline climatology. The model is significantly improved by adding terrain roughness. The effect amounts to an 18% reduction in the number of tornadoes for every ten meter increase in elevation standard deviation. The model indicates that tornadoes are 51% more likely to occur in counties served by the CWAs of DDC and GID than elsewhere in the state. Flexibility of the model is illustrated by fitting it to data from Illinois, Mississippi, South Dakota, and Ohio.     

A Global and Spatially Explicit Assessment of Climate Change Impacts on Crop Production and Consumptive Water Use

Food security and water scarcity have become two major concerns for future human''s sustainable development, particularly in the context of climate change. Here we present a comprehensive assessment of climate change impacts on the production and water use of major cereal crops on a global scale with a spatial resolution of 30 arc-minutes for the 2030s (short term) and the 2090s (long term), respectively. Our findings show that impact uncertainties are higher on larger spatial scales (e.g., global and continental) but lower on smaller spatial scales (e.g., national and grid cell). Such patterns allow decision makers and investors to take adaptive measures without being puzzled by a highly uncertain future at the global level. Short-term gains in crop production from climate change are projected for many regions, particularly in African countries, but the gains will mostly vanish and turn to losses in the long run. Irrigation dependence in crop production is projected to increase in general. However, several water poor regions will rely less heavily on irrigation, conducive to alleviating regional water scarcity. The heterogeneity of spatial patterns and the non-linearity of temporal changes of the impacts call for site-specific adaptive measures with perspectives of reducing short- and long-term risks of future food and water security.     

Local Variability Mediates Vulnerability of Trout Populations to Land Use and Climate Change

Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007–2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change.     

Improving the Use of Species Distribution Models in Conservation Planning and Management under Climate Change

Choice of variables, climate models and emissions scenarios all influence the results of species distribution models under future climatic conditions. However, an overview of applied studies suggests that the uncertainty associated with these factors is not always appropriately incorporated or even considered. We examine the effects of choice of variables, climate models and emissions scenarios can have on future species distribution models using two endangered species: one a short-lived invertebrate species (Ptunarra Brown Butterfly), and the other a long-lived paleo-endemic tree species (King Billy Pine). We show the range in projected distributions that result from different variable selection, climate models and emissions scenarios. The extent to which results are affected by these choices depends on the characteristics of the species modelled, but they all have the potential to substantially alter conclusions about the impacts of climate change. We discuss implications for conservation planning and management, and provide recommendations to conservation practitioners on variable selection and accommodating uncertainty when using future climate projections in species distribution models.     

Use of the 82Sr/82Rb Generator in Clinical PET Studies

The use of the ⁸²Sr/⁸²Rb generator in clinical positron emission tomography (PET) studies of myocardial perfusion has been described. An infusion pump is used to deliver the short-lived ⁸²Rb from the generator to the patient. Various characteristics of the generator and the infusion system are described. The ⁸²Rb yield was 69.8 ± 13.3% and the ⁸²Sr breakthrough was always less than the limit of 0.02 μCi/mCi ⁸²Rb. The yield of ⁸²Rb increased with the flow rate and the potency of the generator. Patients with coronary artery disease were studied for myocardial perfusion abnormalities by the ⁸²Rb PET technique and images of excellent diagnostic quality were obtained.     

Economic and Societal Changes in China and their Effects onWater Use A Scenario Analysis

China's development over the last few decades has been characterized by high rates of economic growth, large-scale migration from rural areas to the fast-growing cities accompanied by changes in lifestyles, and steady population growth. These developments have left deep marks on resource availability and quality. In this article we conduct a scenario analysis of how lifestyle changes and other major developments might affect water resources.
China has the longest tradition in river and water resource management in the world. Its civilization has sought to control the effects of floods and drought for thousands of years and has utilized water flows for irrigation and navigation. In the last century, competing uses such as domestic, municipal, and industrial water consumption have also become reasons for the regulation of and large-scale abstraction of water.
To investigate the major changes in economy and society and their effects on the water situation in China, a set of scenarios is developed and analyzed within a structural economics framework. A hydrological model that represents water flows in the major watersheds is linked to a regional input-output model that represents socioeconomic activities in the major economic-administrative regions of China. The regional analysis shows that the North and Northwest regions are water-scarce and that lifestyle changes and technical shifts are the most important factors driving future water consumption.     

Climate Change and Health in Sub-Saharan Africa: A Case-Based Perspective

Over the coming decades, sub-Saharan Africa will face profound stresses and challenges from global climate change. Many of these will manifest as adverse health outcomes. This article uses a series of five hypothetical cases to review the climate impacts on the health and well-being of individuals and populations in sub-Saharan Africa. This approach fosters insights into the human dimensions of the risks to health, their interaction with local human ecology, and awareness of the diverse health ramifications of external environmental changes. Each case illustrates the health impact resulting from a specific environmental or social consequence of climate change, including impacts on agriculture and food security, droughts, floods, malaria, and population displacement. Whereas the article focuses on discrete manifestations of climate change, individuals will, in practice, face multiple stresses from climate change (i.e., floods and malaria) concomitant with other non-climate stressors (i.e., HIV/AIDS, globalization, etc.). These multiple sources of vulnerability must be considered when designing climate change and socioeconomic development interventions.     

Land Use Compounds Habitat Losses under Projected Climate Change in a Threatened California Ecosystem

Given the rapidly growing human population in mediterranean-climate systems, land use may pose a more immediate threat to biodiversity than climate change this century, yet few studies address the relative future impacts of both drivers. We assess spatial and temporal patterns of projected 21^st century land use and climate change on California sage scrub (CSS), a plant association of considerable diversity and threatened status in the mediterranean-climate California Floristic Province. Using a species distribution modeling approach combined with spatially-explicit land use projections, we model habitat loss for 20 dominant shrub species under unlimited and no dispersal scenarios at two time intervals (early and late century) in two ecoregions in California (Central Coast and South Coast). Overall, projected climate change impacts were highly variable across CSS species and heavily dependent on dispersal assumptions. Projected anthropogenic land use drove greater relative habitat losses compared to projected climate change in many species. This pattern was only significant under assumptions of unlimited dispersal, however, where considerable climate-driven habitat gains offset some concurrent climate-driven habitat losses. Additionally, some of the habitat gained with projected climate change overlapped with projected land use. Most species showed potential northern habitat expansion and southern habitat contraction due to projected climate change, resulting in sharply contrasting patterns of impact between Central and South Coast Ecoregions. In the Central Coast, dispersal could play an important role moderating losses from both climate change and land use. In contrast, high geographic overlap in habitat losses driven by projected climate change and projected land use in the South Coast underscores the potential for compounding negative impacts of both drivers. Limiting habitat conversion may be a broadly beneficial strategy under climate change. We emphasize the importance of addressing both drivers in conservation and resource management planning.     

Land-Use Change and Stream Water Fluxes: Decadal Dynamics in Watershed Nitrate Exports

Stream water exports of nutrients and pollutants to water bodies integrate internal and external watershed processes that vary in both space and time. In this paper, we explore nitrate (NO₃) fluxes for the 326 km² mixed-land use Fall Creek watershed in central New York for 1972–2005, and consider internal factors such as changes in land use/land cover, dynamics in agricultural production and fertilizer use, and external factors such as atmospheric deposition. Segmented regression analysis was applied independently to dormant and growing seasons for three portions of the period of record, which indicated that stream water NO₃ concentrations increased in both dormant and growing seasons from the 1970s to the early 1990s at all volumes of streamflow discharge. Dormant season NO₃ concentrations then decreased at all flow conditions between the periods 1987–1993 and 1994–2005. Results from a regression-based stream water loading model (LOADEST) normalized to mean annual concentrations showed annual modeled NO₃ concentration in stream water increased by 34% during the 1970s and 1980s (from 1.15 to 1.54 mg l⁻¹), peaked in about 1989, and then decreased by 29% through 2005 (to 1.09 mg l⁻¹). Annual precipitation had the strongest correlation with stream water NO₃ concentrations (r = −0.62, P = 0.01). Among land use factors, corn production for grain was the variable most highly correlated to stream water NO₃ concentrations (r = 0.53, P = 0.01). The strongest associative trend determined using Chi-squared Automatic Interaction Detection (CHAID) was found between stream water NO₃ concentrations and N-equivalence of dairy production (Bonferroni adjusted P value = 0.0003). Large increases in dairy production were coincident with declining nitrate concentrations over the past decade, which suggest that dairy management practices may have improved in the watershed. However, because dairy production in the Fall Creek watershed has been fueled by large increases in feed imports, the environmental costs of feed production have likely been externalized to other watersheds.     

Land-Use Change and Biogeochemical Controls of Methane Fluxes in Soils of Eastern Amazonia

Tropical soils account for 10%–20% of the 15–35 Tg of atmospheric methane (CH₄) consumed annually by soils, although tropical deforestation could be changing the soil sink. The objectives of this study were (a) to quantify differences in soil CH₄ fluxes among primary forest, secondary forest, active pasture, and degraded pasture in eastern Amazonia; and (b) to investigate controlling mechanisms of CH₄ fluxes, including N availability, gas-phase transport, and soil respiration. At one ranch, Fazenda Vitória, annual uptake estimates (kg CH₄ha⁻¹ y⁻¹) based on monthly measurements were: primary forest, 2.1; secondary forest, 1.0; active pasture, 1.3; degraded pasture, 3.1. The lower annual uptake in the active pasture compared with the primary forest was due to CH₄ production during the wet season in the pasture soils, which is consistent with findings from other studies. In contrast, the degraded pasture was never a CH₄ source. Expressing uptake as a negative flux and emission as a positive flux, CH₄ fluxes were positively correlated with CO₂ fluxes, indicating that root and microbial respiration in the productive pastures, and to a lesser extent in the primary forest, contributed to the formation of anaerobic microsites where CH₄ was produced, whereas this productivity was absent in the degraded pasture. In all land uses, uptake rates of atmospheric CH₄ were greater in the dry season than in the wet season, indicating the importance of soil water content and gas transport on CH₄ fluxes. These clay soils had low annual uptake rates relative to reported rates on sandy soils, which also is consistent with gas transport within the soil being a limiting factor. Nitrogen availability indices did not correlate with CH₄ fluxes, indicating that inhibition of CH₄ oxidation was not an important mechanism explaining differences among land uses. At another ranch, Fazenda Agua Parada, no significant effect of pasture age was observed along a chronosequence of pasture ages. We conclude that land-use change can either increase or decrease the soil sink of CH₄, depending on the duration of wet and dry seasons, the effects of seasonal precipitation on gas-phase transport, and the phenology and relative productivity of the vegetation in each land use.