Alahuhta, J., Heino, J, & Luoto, M. (2011). Climate change and the future distributions of aquatic macrophytes across boreal catchments. Journal of Biogeography, 38(2), 383-93.
Due to a lack of research on the impacts of climate change on aquatic-terrestrial ecotones in boreal regions, the researchers sought to determine these impacts and include non-climatic factors for a more thorough assessment. Data regarding occurrence and percent cover of aquatic macrophytes across Finland was collected, and the non-climatic variables used were mean elevation, soil type, and shoreline development factor. The climatic model encompassed four different climate scenarios covering the years 2051-2080, and the variables used were growing-degree days, average temperature from the coldest month, and average annual precipitation. The results show that percent cover and occurrence of emergent aquatic macrophytes are likely to expand northward over the course of the modeled time period and this is primarily influenced by growing-degree days, which may negatively affect the ecotone due to overgrowth.
Band, L.E., Mackay, S., Creed, I.F., Semkin, R., & Jeffries, D. (1996) Ecosystem process at the watershed scale: Sensitivity to potential climate change. Limnology and Oceanography, 41 (5), 928-938.
The researchers developed a watershed simulation model, coined the Regional HydroEcological Simulation System (RHESSys), in order to determine potential climate change impacts on forest watersheds. A hydroecological model was used in combination with a topographical model of the Turkey Lakes Watershed in Ontario, Canada, along with terrestrial hydrological and ecological process submodels. These models were run through a variety of simulations, including temperature and precipitation changes, and a doubling of atmospheric carbon dioxide. Although the different scenarios produced a variety of potential adjustments of the watershed ecosystem to climate change, the overall result was that ecosystem processes appear to be resilient to climate change due to offsetting effects (ie forest productivity and watershed outflow).
Boateng, I. (2011). GIS assessment of coastal vulnerability to climate change and coastal adaptation planning in Vietnam. Journal of Coastal Conservation, 16 (1), 25-36.
The low-lying Vietnamese coastline is highly vulnerable to natural phenomena that are exacerbated by human activity and climate change, such as typhoons and erosion. This study sought to determine the impacts that rising sea levels will have on the Vietnamese coastline and to identify potential strategies to mitigate the damage that may result. A combination of a literature review and a GIS analysis using three different flood layers was used to address the research questions. It was found that the two most developed regions in Vietnam, the Red River delta and the Mekong River delta, have the highest risk of flooding, whereas the central coast has a low flood risk. A non-structural approach to adapt the high risk areas to increased flooding was identified as the best option for this region.
Boateng, 2011
Brander, L.M., Brauer, I., Gerdes, H., Ghermandi, A., Kuik, O., Markandya, A., Navrud, S., Nunes, P., Schaafsma, M., Vos, H., & Wagtendonk, A. (2011). Using meta-analysis and GIS for value transfer and scaling up: Valuing climate change induced losses of European wetlands. Environmental and Resource Economics, 52(3), 395-413.
This research paper is focused on the use of meta-analysis in conjunction with GIS to determine how climate change can alter the value of ecosystem services. European wetlands were used to test out the researchers’ methodology, in which a meta-regression model was used to estimate wetland value and a GIS was used to compare current wetland variables (wetland abundance, population, GDP per capita) with that of 2050 (projected to experience an 8% loss). It was predicted from the results that roughly one billion US dollars worth of ecosystem services would be lost by 2050 as a result of the effects of climate change.
Eatherall, A. (1997). Modelling climate change impacts on ecosystems using linked models and a GIS. Climate Change, 35, 17-34.
The researchers here developed what they term a linked model of ecosystem components in order to determine potential climate change effects. The model was applied to the grassland ecosystem and was comprised of soil moisture, grassland productivity, evapotranspiration and soil nitrate sub-models. These linked sub-models were then combined with spatial data in a GIS to incorporate climate change scenarios for 2050. It was found that productivity is likely to decrease in grasslands due to decreased soil moisture as a result of climate change. This could have large implications for water resource planning in response to climate change.
Halofsky, J.E., Hemstrom, M.A., Conklin, D.R., Halofsky, J.S., Kerns, B.K., & Bachelet, D. (2013). Assessing potential climate change effects on vegetation using a linked model approach. Ecological Modelling, 266, 131-143.
The researchers here identified a need for predictive modeling of vegetation in response to climate change and so developed a linked model approach using dynamic global vegetation models (DGVMs) and state-and-transition models (STMs) in combination with three different climate change scenarios to make such predictions. A section of central Oregon was used as the template study site in which the linked model approach was applied and compared to the application of the individual models. The prominent finding from this study was that vegetation in this region may be resilient to climate change for a short period of time but will then experience a dramatic alteration as disturbance increases. Species-specific responses to climate change were noted and it was inferred that this could contribute to the short term stability of communities. This information can allow land management to be better prepared for upcoming changes in vegetation due to climate change.
Halofsky et al., 2013
Jantke, K., Muller, J., Trapp, N., & Blanz, B. (2016). Is climate-smart conservation feasible in Europe? Spatial relations of protected areas, soil carbon, and land values. Environmental Science & Policy, 57, 40-49.
Protecting land in attempts to conserve biodiversity can also serve to mitigate climate change via carbon sequestration, a strategy termed climate-smart conservation. The researchers of this study sought to determine any spatial relations existing between biodiversity, soil carbon content and land value in Europe’s Natura 2000 (an expansive network of protected areas across the continent). The Natura 2000, soil organic organic carbon content in topsoils, and agricultural land prices datasets were used in the spatial analysis. The researchers found that regions of high biodiversity are often on land with high carbon content and low land value. The findings provide insight into the opportunity for Europe to participate in cost-effective, climate-smart conservation.
Jeanson, M., Dolique, F., & Anthony, E.J. (2013). A GIS-based coastal monitoring and surveillance observatory on tropical islands exposed to climate change and extreme events: The example of Mayotte Island, Indian Ocean. Journal of Coastal Conservation, 18 (5), 567-580.
Out of concern for the vulnerability of coastal regions to climate change in the form of erosion and extreme weather events, the researchers sought to gain an understanding of how islands like Mayotte Island would change in response. Measurements taken in the field, aerial photographs and meteorological data were used to analyze the dynamic morphology of Mayotte Island over time via interactive maps. The relative stability of the mangrove forest and pocket beaches found over the course of 59 years suggests that these areas are resilient to increases in human activity and to the impacts of climate change. Overall, this study serves as an exemplary methodology to approach the characterization and monitoring of coastal regions in regards to their abilities to withstand climate change impacts.
Keshtkar, H. & Voigt, W. (2016). Potential impacts of climate and landscape fragmentation changes on plant distributions: Coupling multi-temporal satellite imagery with GIS-based cellular automata model. Ecological Informatics, 32, 145-155.
There is a lack of research comparing the effects of climate change to those of landscape fragmentation. In this paper, the researchers attempt to make such a comparison using a GIS-based cellular automata model in which the distribution of three different plant species in central Germany are projected using a number of different dispersal, landscape fragmentation and climate change scenarios for the years 2020, 2040, 2060 and 2080. It was found that fragmentation has a greater impact on plant species distribution compared to climate change, and that realistic dispersal is more reflective of the no-dispersal scenario than the full-dispersal scenario.
Keshtkar and Voigt, 2016
Mahmoud, S.H. & Gan, T.Y. (2018). Impact of anthropogenic climate change and human activities on environment and ecosystem services in arid regions. Science of The Total Environment, 633, 1329-1344.
The researchers sought to determine the extent of the impact created by human activity (via climate change and land use change) on Saudi Arabian ecosystems from 1970 to 2014. Earth observations data were utilized to determine the extent of land use change while temperature, precipitation and greenhouse gas data were used to determine the extent of climate change in the region. A questionnaire was delivered to residents regarding land use and the impacts of human activity on the environment. Additionally, climate and land use change projections were used to predict future environmental impacts. It was found that temperatures have risen, precipitation has decreased, and biodiversity suffered great losses in the forms of degradation and fragmentation in response to human activity in the region.
Mahmoud and Gan, 2018
Mahmoud and Gan, 2018
McDowell, N.G., Coops, N.C., Beck, P.S.A., Chambers, J.Q., Gangodagamage, C., Hicke, J.A., Huang, C., Kennedy, R., Krofcheck, D.J., Litvak, M., Meddens, A.J.H., Muss, J., Negrón-Juarez, R., Peng, C., Schwantes, A.M., Swenson, J.J., Vernon, L.J., Williams, A.P., Xu, C., Zhao, M., Running, S.W., & Allen, C.D. (2015). Global satellite monitoring of climate-induced vegetation disturbances. Trends in Plant Science, 20(2), 114-123.
The authors of this article make the case that remote sensing can and should be used to monitor terrestrial disturbances across the world, and they developed a framework for others to use when assessing such disturbances. It is argued that our current knowledge of disturbance is not sufficient enough to make accurate predictions as climate change continues to develop. Recent advances in remote sensing offer the potential to vastly improve disturbance analysis by determining the spatiotemporal aspects of disturbance, disturbance classification, and the causes and effects of disturbance. The authors also argue that broader detection methods should be used so that a global disturbance monitoring system may be employed.
Piekielek, N.B., Hansen, A.J., & Chang, T. (2015). Using custom scientific workflow software and GIS to inform protected area climate adaptation planning in the Greater Yellowstone Ecosystem. Ecological Informatics, 30, 40-48.
The goal of this study was to use species distribution models and global climate models to make predictions on how climate change will affect species distributions in the Greater Yellowstone Ecosystem. In doing so, the researchers hoped to use this information to improve upon climate adaptation planning. The dominant vegetation species found in four distinct elevation zones in Yellowstone were used for the species distribution models; water-balance, soil properties and topography were used as predictor data; global climate models and projected temperature, precipitation and habitat data were used for the future climate data. It was found that decreasing spring and summer snowpack and increasing soil moisture deficit are likely to result in deforestation via longer, drier growing season, and that species are likely to alter their distributions to regions of higher elevation. The methodology utilized in this study can serve as a reference for natural resource managers that aim to develop their own climate adaptation strategies.
Piekielek et al., 2015
Sapta, S., Sulistyantara, B., Fatimah, I.S., & Faqih, A. (2015). Geospatial approach for ecosystem change study of Lombok Island under the influence of climate change. Procedia Environmental Sciences, 24, 165-173.
Due to the already shifting ecosystems found on Lombok Island in response to climate change, the researchers in this study sought to determine what changes have taken place since 1975 and which vegetation dominates in each ecosystem identified. Historical climate data was used for comparison, interpolation was used to fill in unknown values, Holdridge Life Zones were used to classify ecosystem types, and ground truthing was used to validate the results. It was found that the number of life zones had decreased from seven in 1975 to five in 2012, with tropical dry forest was the dominant vegetation in the area, and this was confirmed by the ground truthing. This shift in ecosystems was attributed to changes in precipitation and biotemperature on the island.
Sapta et al., 2015
Schmitz, O.J., Post, E., Burns, C.E., & Johnston, K.M. (2003). Ecosystem responses to global climate change: Moving beyond color mapping. BioScience, 53(12), 1199-1205.
The authors of this article argue that most current analyses of ecosystem shifts in response to climate change suffer from a lack of inclusion of animals from higher trophic levels by assuming change is driven by bottom-up ecosystem processes. They also argue that these analyses make the simple, and therefore flawed, assumption that the predicted ecosystem shifts will be viable and intact following relocation when adjusting to climate change. The authors provide examples from a top-down food chain in northern forest, freshwater lake, and pelagic marine ecosystems to drive home these points. More thorough modelling of species interactions are needed to make more accurate predictions about the response of ecosystems to climate change, including drivers from all levels of trophic processes and the strength of different trophic interactions.
Smith, A.M.S., Kolden, C.A., Tinkham, W.T., Talhelm, A.F., Marshall, J.D., Hudak, A.T., Boschetti, L., Falkowski, M.J., Greenberg, J.A., Anderson, J.W., Kliskey, A., Alessa, L., Keefe, R.F., & Gosz, J.R. (2013). Remote sensing the vulnerability of vegetation in natural terrestrial ecosystems. Remote Sensing of Environment, 154, 322-337.
This article is a review of studies that have utilized remote sensing to assess the vulnerability of ecosystem goods and services to disturbance driven by climate change. Research on this subject uses historical data, recent observations, experimental approach, or modelling to assess likely changes to ecosystems due to climate change. The article highlights the use of remote sensing of vulnerability in a variety of ecosystems, including temperate and tropical forests, Savannahs, wetlands, and tundra. Early warning systems can be developed via remote sensing for use in mitigation and adaptation in which spatial layers are used to produce ecological models that could pinpoint causes and tipping points of ecosystem change. In order to be effective, these systems must include a specific set of characteristics outlined by the authors, including metrics that are transferable to similar ecosystems, data that land managers and stakeholders can understand, and temporal series data.
Smith et al., 2013
Srivastava, P., Mehta, A., Gupta, M., Singh, S.K., & Islam, T. (2015). Assessing impact of climate change on Mundra mangrove forest ecosystem, Gulf of Kutch, western coast of India: A synergistic evaluation using remote sensing. Theoretical and Applied Climatology, 120 (3-4), 685-700.
This study examined how mangrove forest density has changed over time in relation to climate change factors (rising sea levels, altered precipitation and temperature, etc.) and human activity (increased population and density, urbanization, industrialization) in the Gulf of Kutch. Satellite images were rectified via RMSE evaluation and classified using both supervised and unsupervised methods, and SRSM was used to check for accuracy. It was found that both sparse and potential mangrove forests decreased between 1994 and 2010, while dense forests increased (attributed to preservation initiatives), with a total forest loss of 4.8%. A thematic map of land use change suggests that forests were cut back by rising sea levels and growing waste land and mudflats, while the increase in dense forests was likely due to the land use change to water. Rising sea levels and temperature as well as increasing human activity heavily limited the growth of the forests.
Taylor, G.T., Muller-Karger, F.E., Thunell, R.C., Scranton, M.I., Astor, Y., Varela, R., Ghinaglia, L.T., Lorenzoni, L., Fanning, K.A., Hameed, S. & Doherty, O. (2012). Ecosystem responses in the southern Caribbean Sea to global climate change. Proceedings of the National Academy of Sciences of the United States of America, 109 (47), 19315-19320.
Due to the sensitivity of marginal seas to climate change and the discrepancies in research regarding ocean productivity, the researchers here sought to identify trends in ocean productivity, hydrography and meteorology, specifically in the southern Caribbean Sea. Monthly data from the CARIACO Ocean Time-Series over the past 14 years was used to compare climate change indices with observed ecological change. Phytoplankton populations were found to have decreased over time as well as shifted in taxon dominance from larger to smaller taxa. These changes are attributed to climatic changes, specifically the northern shift of the Azores High pressure center and the northeastern shift of the ITCZ Atlantic centroid, which have weakened the Trade Winds and thus decreased upwelling of nutrients.
Taylor, S. & Kumar, L. (2013). Potential distribution of an invasive species under climate change scenarios using CLIMEX and soil drainage: A case study of Lantana camara L. in Queensland, Australia. Journal of Environmental Management, 114, 414-422.
This article explores the effects of climate change and soil drainage on the distribution of Lantana, an invasive species in Australia. The researchers projected Lantana distribution using a niche model and two different climate models, incorporating the non-climatic variable of soil drainage. They found that Lantana is likely to experience a distribution increase by 2030, although it will reduce overall by 2100.
Taylor et al., 2013
