Socio-Economic Instability and the Scaling of Energy Use with Population Size

The size of the human population is relevant to the development of a sustainable world, yet the forces setting growth or declines in the human population are poorly understood. Generally, population growth rates depend on whether new individuals compete for the same energy (leading to Malthusian or density-dependent growth) or help to generate new energy (leading to exponential and super-exponential growth). It has been hypothesized that exponential and super-exponential growth in humans has resulted from carrying capacity, which is in part determined by energy availability, keeping pace with or exceeding the rate of population growth. We evaluated the relationship between energy use and population size for countries with long records of both and the world as a whole to assess whether energy yields are consistent with the idea of an increasing carrying capacity. We find that on average energy use has indeed kept pace with population size over long time periods. We also show, however, that the energy-population scaling exponent plummets during, and its temporal variability increases preceding, periods of social, political, technological, and environmental change. We suggest that efforts to increase the reliability of future energy yields may be essential for stabilizing both population growth and the global socio-economic system

Fostering Sustainable Innovation through Creative Destruction Theory

The current information age is modelled on the advancement of innovative mindset of creative thinkers, championed through means associated with transformative technologies embodied on events like, high speed internet and payment system, thereby making it possible for transactions to be dealt with almost instantaneously. Such developments are essentially vital, given its prospect for championing growth rate and dynamism in the world economy and also, the need to ensure living conditions are adequately satisfied, particularly in the direction of the Sustainable Development Goals (SDG) earmarked for full implementation in the year 2030. The concept of innovation is widely used in all walks of life - the effort of Schumpeter’s paradoxical term, “creative destruction” became highly prominent in the 1950s, which many economists in recent time have endeavoured to linked with free market economics (Cozzi and Galli, 2019; Benigno and Fornaro, 2018). Creative destruction as proposed by Schumpeter, and also explained by Alm and Cox (Online) is essentially facts about capitalism, which is thought to be a shorthand description of free market’s messy way of delivering progress

Measuring total factor productivity on Irish dairy farms: a Fisher index approach using farm-level data

peer reviewedThis paper presents a Fisher index measure of the total factor productivity (TFP) performance of Irish dairy farms over the period 2006–2016 using the Teagasc National Farm Survey (NFS) data. The removal of milk quotas in 2015 has led to an increase of over 30% in dairy cow numbers since 2010, and although suckler cow numbers have dropped slightly, the total number of cows in Ireland reached an all-time high of 2.5 million head in 2016. This large increase adds to the environmental pressures attributed to agricultural output and puts the focus firmly on how efficiently the additional agricultural output associated with higher cow numbers is produced. The primary purpose of this paper is to identify a standardised measure of the TFP performance of Irish dairy farms that can be routinely updated using Teagasc NFS data. We found that relative to 2010 the TFP of Irish dairy farms has increased by almost 18%; however, in one production year 2015, when milk quota was removed, the TFP measure increased by 7% and TFP continued to grow by 2.5% in the production year 2016. It would seem therefore that the removal of the European dairy quota system has resulted in a windfall gain for Irish dairy farmers but that productivity gains are continuing. Future data will be required to investigate the longer-term TFP performance of Irish dairy farms in the post-milk quota era

Remote detection of invasive alien species

The spread of invasive alien species (IAS) is recognized as the most severe threat to biodiversity outside of climate change and anthropogenic habitat destruction. IAS negatively impact ecosystems, local economies, and residents. They are especially problematic because once established, they give rise to positive feedbacks, increasing the likelihood of further invasions and spread. The integration of remote sensing (RS) to the study of invasion, in addition to contributing to our understanding of invasion processes and impacts to biodiversity, has enabled managers to monitor invasions and predict the spread of IAS, thus supporting biodiversity conservation and management action. This chapter focuses on RS capabilities to detect and monitor invasive plant species across terrestrial, riparian, aquatic, and human-modified ecosystems. All of these environments have unique species assemblages and their own optimal methodology for effective detection and mapping, which we discuss in detail

GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality

The development of algorithms for remote sensing of water quality (RSWQ) requires a large amount of in situ data to account for the bio-geo-optical diversity of inland and coastal waters. The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement of chlorophyll a, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided. The data were contributed by researchers affiliated with 59 institutions worldwide and come from 450 different water bodies, making GLORIA the de-facto state of knowledge of in situ coastal and inland aquatic optical diversity. Each measurement is documented with comprehensive methodological details, allowing users to evaluate fitness-for-purpose, and providing a reference for practitioners planning similar measurements. We provide open and free access to this dataset with the goal of enabling scientific and technological advancement towards operational regional and global RSWQ monitoring

Estimation of velocity fields at the estuary-coastal interface through statistical analysis of successive airborne remotely sensed images.

The study of surface water velocity fields through in situ sampling is intrinsically difficult because they are highly variable in time and space. With airborne remote sensing, however, it is possible to determine changes in velocity fields because spatially and temporally comprehensive data may be obtained. This letter shows how changes in the statistical properties of successive remotely sensed images may be used to estimate velocity vectors associated with chlorophyll-a and sea surface temperature (SST). The study area is Kirkcudbright Bay, a small estuary in south-west Scotland. Multi-temporal imagery of the study area were acquired by the NERC Daedalus ADDS-1268 Airborne ThematicMapper (ATM) and processed to show chlorophyll and thermal indices as substitutes for chlorophyll- a and SST. Velocity fields were estimated by the Maximum Cross Correlation technique. Complex patterns were found, confirming that the comprehensive coverage provided by airborne remote sensing is required for their analysis. The chlorophyll-a velocity field delivered from the SST velocity field, suggesting that these fields are relevant to the water quality variable in question, and not necessarily the water body itself