Adapting to Climatic Extremes through Climate Resilient Industrial Landscapes: Building Capacities in the Southern Indian States of Telangana and Andhra Pradesh

There is now greater confidence and understanding of the consequences of anthropogenic caused climate change. One of the many impacts of climate change, has been the occurrence of extreme climatic events, recent studies indicate that the magnitude, frequency, and intensity of hydro-meteorological events such as heat waves, cyclones, droughts, wildfires, and floods are expected to increase several fold in the coming decades. These climatic extremes are likely to have social, economic, and environmental costs to nations across the globe. There is an urgent need to prepare various stakeholders to these disasters through capacity building and training measures. Here, we present an analysis of the capacity needs assessment of various stakeholders to climate change adaptation in industrial parks in two southern states of India. Adaptation to climate change in industrial areas is an understudied yet highly urgent requirement to build resilience among stakeholders in the Indian subcontinent. The capacity needs assessment was conducted in two stages, participatory rural appraisal (PRA) and focus group discussion (FGD) were conducted among various stakeholders to determine the current capacities for climate change adaptation (CCA) for both, stakeholders and functional groups. Our analysis indicates that in the states of Telangana and Andhra Pradesh, all stakeholder groups require low to high levels of retraining in infrastructure and engineering, planning, and financial aspects related to CCA. Our study broadly supports the need for capacity building and retraining of functionaries at local and state levels in various climate change adaptation measures; likewise industry managers need support to alleviate the impacts of climate change. Specific knowledge, skills, and abilities, with regard to land zoning, storm water management, developing building codes, green financing for CCA, early warning systems for climatic extremes, to name a few are required to enhance and build resilience to climate change in the industrial landscapes of the two states

Interactions between fire and climate in the Western Ghats, India

International audienc

Interactions between fire and climate in the Western Ghats, India

International audienc

Conservation Threat of Increasing Fire Frequencies in the Western Ghats, India

The acceleration of processes such as forest fragmentation and forest fires in landscapes under intense human pressures makes it imperative to quantify and understand the effects of these processes oil the conservation of biodiversity in these landscapes. We combined information from remote-sensing, imagery and ground maps of all fires in the Mudumalai Wildlife Sanctuary (MWLS) in the Western Ghats of India over 14 years (1989-2002). These spatial data on fire occurrence were integrated with maps of vegetation types found in the MWLS to examine fire conditions in each. We calculated the average fire-return interval for. each of the vegetation types individually, and for the MWLS as a whole. Using vegetation data from the larger Nilgiri Biosphere Reserve and the entire Western Ghats region, we conservatively estimated fire frequency information for these larger regions. Because the MWLS does not contain tropical evergreen or montane forests, we were unable to estimate fire conditions in these fire conditions in these forest types, which represent 31% of all Western Ghats vegetation cover. For the MWLS, all vegetation types had average fire-return intervals of < 7 years, and the sanctuary as a whole had a fire-return interval of 3.3 years. Compared with a 13-year MWLS fire data set from 1909-1921, this represents a threefold increase in fire frequency over the last 80 years. We estimated average fire-return intervals of roughly 5 years for both the larger Nilgiri Biosphere Reserve and the entire Western Ghats region. Given other recent reports, the estimated fire frequencies for the Western Ghats forests outside protected reserves are conservative. We conclude that the current fire regime of the Western Ghats poses a severe and persistent conservation threat to forests both within and outside protected reserves

Conservation threat of increasing fire frequencies in the Western Ghats, India

The acceleration of processes such as forest fragmentation and forest fires in landscapes under intense human pressures makes it imperative to quantify and understand the effects of these processes on the conservation of biodiversity in these landscapes. We combined information from remote-sensing imagery and ground maps of all fires in the Mudumalai Wildlife Sanctuary (MWLS) in the Western Ghats of India over 14 years (1989-2002). These spatial data on fire occurrence were integrated with maps of vegetation types found in the MWLS to examine fire conditions in each. We calculated the average fire-return interval for each of the vegetation types individually and for the MWLS as a whole. Using vegetation data from the larger Nilgiri Biosphere Reserve and the entire Western Ghats region, we conservatively estimated fire-frequency information for these larger regions. Because the MWLS does not contain tropical evergreen or montane forests, we were unable to estimate fire conditions in these forest types, which represent 31% of all Western Ghats vegetation cover. For the MWLS, all vegetation types had average fire-return intervals of &#x003C; 7 years, and the sanctuary as a whole had a fire-return interval of 3.3 years. Compared with a 13-year MWLS fire data set from 1909-1921, this represents a threefold increase in fire frequency over the last 80 years. We estimated average fire-return intervals of roughly 5 years for both the larger Nilgiri Biosphere Reserve and the entire Western Ghats region. Given other recent reports, the estimated fire frequencies for the Western Ghats forests outside protected reserves are conservative. We conclude that the current fire regime of the Western Ghats poses a severe and persistent conservation threat to forests both within and outside protected reserves

Environmental susceptibility model for predicting forest fire occurrence in the Western Ghats of India

International audienc

A comparative analysis of spatial, temporal, and ecological characteristics of forest fires in seasonally dry tropical ecosystems in the Western Ghats, India

The Western Ghats in India is one of the 25 global hotspots of biodiversity, and it is the hotspot with the highest human density. This study considers variations in the regional fire regime that are related to vegetation type and past human disturbances in a landscape. Using a combination of remote sensing data and GIS techniques, burnt areas were delineated in three different vegetation types and various metrics of fire size were estimated. Belt transects were enumerated to assess the vegetation characteristics and fire effects in the landscape. Temporal trends suggest increasingly short fire-return intervals in the landscape. In the tropical dry deciduous forest, the mean fire-return interval is 6 years, in the tropical dry thorn forest mean fire-return interval is 10 years, and in the tropical moist deciduous forest mean fire-return interval is 20 years. Tropical dry deciduous forests burned more frequently and had the largest number of fires in any given year as well as the single largest fire (9900 ha). Seventy percent, 56%, and 30% of the tropical moist deciduous forests, tropical dry thorn forests, and tropical dry deciduous forests, respectively have not burned during the 7-year period of study. The model of fire-return interval as a function of distance from park boundary explained 63% of the spatial variation of fire-return interval in the landscape. Forest fires had significant impacts on species diversity and regeneration in the tropical dry deciduous forests. Species diversity declined by 50% and 60% in the moderate and high frequency classes, respectively compared to the low fire frequency class. Sapling density declined by ca. 30% in both moderate and high frequency classes compared to low frequency class. In tropical moist deciduous ecosystems, there were substantial declines in species diversity, tree density, seedling and sapling densities in burned forests compared to the unburned forests. In contrast forest fires in tropical dry thorn forests had a marginal positive effect on ecosystem diversity, structure, and regeneration

A comparative analysis of spatial, temporal, and ecological characteristics of forest fires in seasonally dry tropical ecosystems in the Western Ghats, India

The Western Ghats in India is one of the 25 global hotspots of biodiversity, and it is the hotspot with the highest human density. This study considers variations in the regional fire regime that are related to vegetation type and past human disturbances in a landscape. Using a combination of remote sensing data and GIS techniques, burnt areas were delineated in three different vegetation types and various metrics of fire size were estimated. Belt transects were enumerated to assess the vegetation characteristics and fire effects in the landscape. Temporal trends suggest increasingly short fire-return intervals in the landscape. In the tropical dry deciduous forest, the mean fire-return interval is 6 years, in the tropical dry thorn forest mean fire-return interval is 10 years, and in the tropical moist deciduous forest mean fire-return interval is 20 years. Tropical dry deciduous forests burned more frequently and had the largest number of fires in any given year as well as the single largest fire (9900 ha). Seventy percent, 56%, and 30% of the tropical moist deciduous forests, tropical dry thorn forests, and tropical dry deciduous forests, respectively have not burned during the 7-year period of study. The model of fire-return interval as a function of distance from park boundary explained 63% of the spatial variation of fire-return interval in the landscape. Forest fires had significant impacts on species diversity and regeneration in the tropical dry deciduous forests. Species diversity declined by 50% and 60% in the moderate and high frequency classes, respectively compared to the low fire frequency class. Sapling density declined by ca. 30% in both moderate and high frequency classes compared to low frequency class. In tropical moist deciduous ecosystems, there were substantial declines in species diversity, tree density, seedling and sapling densities in burned forests compared to the unburned forests. In contrast forest fires in tropical dry thorn forests had a marginal positive effect on ecosystem diversity, structure, and regeneration

Where there's Smoke, there's Fire: Wildfire Risk Predictive Modeling via Historical Climate Data

Wildfire is a growing global crisis with devastating consequences. Uncontrolled wildfires take away human lives, destroy millions of animals and trees, degrade the air quality, impact the biodiversity of the planet and cause substantial economic costs. It is incredibly challenging to predict the spatio-temporal likelihood of wildfires based on historical data, due to their stochastic nature. Crucially though, the accurate and reliable prediction of wildfires can help the stakeholders and decision-makers take timely, strategic and effective actions to prevent, detect and suppress the wildfires before they become unmanageable. Unfortunately, most previous studies developed predictive models that suffer from some shortcomings: (i) they do not take the temporal aspects into account precisely and they assume the independent and identically distributed random variables in the evaluation phase; (ii) they do not evaluate their approaches comprehensively, thus it is not clear if their proposed predictions and selected models are reliable across different locations and time steps for practical deployment; and (iii) for the supervised learning models, they use predictor features and fire observations from the same time step in the training phase, which makes the inference task infeasible for future fire prediction. In this paper, we revisit the wildfire predictive modeling, explore the inherent challenges from a practical perspective and evaluate our modeling approach comprehensively via historical burned areas, climate and geospatial data from three vast landscapes in India