DroughtA drought is a period of drier-than-normal conditions. A drought can last for days, months or years. Drought often has large impacts on the ecosystems and agriculture of affected regions, and causes harm to the local economy. Annual dry seasons in the tropics significantly increase the chances of a drought developing and subsequent wildfires. Periods of heat can significantly worsen drought conditions by hastening evaporation of water vapour.
AgricultureAgriculture encompasses crop and livestock production, aquaculture, fisheries and forestry for food and non-food products. Agriculture was the key development in the rise of sedentary human civilization, whereby farming of domesticated species created food surpluses that enabled people to live in cities. While humans started gathering grains at least 105,000 years ago, nascent farmers only began planting them around 11,500 years ago. Sheep, goats, pigs and cattle were domesticated around 10,000 years ago.
Climate resilienceClimate resilience is defined as the "capacity of social, economic and ecosystems to cope with a hazardous event or trend or disturbance". This is done by "responding or reorganising in ways that maintain their essential function, identity and structure (as well as biodiversity in case of ecosystems) while also maintaining the capacity for adaptation, learning and transformation". The key focus of increasing climate resilience is to reduce the climate vulnerability that communities, states, and countries currently have with regards to the many effects of climate change.
Drought in AustraliaDrought in Australia is defined by the Australian Bureau of Meteorology as rainfall over period greater than three-months being in the lowest decile of what has been recorded for that region in the past. This definition takes into account that drought is a relative term and rainfall deficiencies need to be compared to typical rainfall patterns including seasonal variations. Specifically, drought in Australia is defined in relation to a rainfall deficiency of pastoral leases and is determined by decile analysis applied to a certain area.
Agricultural scienceAgricultural science (or agriscience for short) is a broad multidisciplinary field of biology that encompasses the parts of exact, natural, economic and social sciences that are used in the practice and understanding of agriculture. Professionals of the agricultural science are called agricultural scientists or agriculturists. History of agricultural science In the 18th century, Johann Friedrich Mayer conducted experiments on the use of gypsum (hydrated calcium sulphate) as a fertilizer.
Crop rotationCrop rotation is the practice of growing a series of different types of crops in the same area across a sequence of growing seasons. This practice reduces the reliance of crops on one set of nutrients, pest and weed pressure, along with the probability of developing resistant pests and weeds. Growing the same crop in the same place for many years in a row, known as monocropping, gradually depletes the soil of certain nutrients and selects for both a highly competitive pest and weed community.
Multinomial logistic regressionIn statistics, multinomial logistic regression is a classification method that generalizes logistic regression to multiclass problems, i.e. with more than two possible discrete outcomes. That is, it is a model that is used to predict the probabilities of the different possible outcomes of a categorically distributed dependent variable, given a set of independent variables (which may be real-valued, binary-valued, categorical-valued, etc.).
Generalized linear modelIn statistics, a generalized linear model (GLM) is a flexible generalization of ordinary linear regression. The GLM generalizes linear regression by allowing the linear model to be related to the response variable via a link function and by allowing the magnitude of the variance of each measurement to be a function of its predicted value. Generalized linear models were formulated by John Nelder and Robert Wedderburn as a way of unifying various other statistical models, including linear regression, logistic regression and Poisson regression.
Climate classificationClimate classifications are systems that categorize the world's climates. A climate classification may correlate closely with a biome classification, as climate is a major influence on life in a region. One of the most used is the Köppen climate classification scheme first developed in 1884. There are several ways to classify climates into similar regimes. Originally, climes were defined in Ancient Greece to describe the weather depending upon a location's latitude.
Ecological resilienceIn ecology, resilience is the capacity of an ecosystem to respond to a perturbation or disturbance by resisting damage and recovering quickly. Such perturbations and disturbances can include stochastic events such as fires, flooding, windstorms, insect population explosions, and human activities such as deforestation, fracking of the ground for oil extraction, pesticide sprayed in soil, and the introduction of exotic plant or animal species.
Logistic regressionIn statistics, the logistic model (or logit model) is a statistical model that models the probability of an event taking place by having the log-odds for the event be a linear combination of one or more independent variables. In regression analysis, logistic regression (or logit regression) is estimating the parameters of a logistic model (the coefficients in the linear combination).
Animal husbandryAnimal husbandry is the branch of agriculture concerned with animals that are raised for meat, fibre, milk, or other products. It includes day-to-day care, selective breeding, and the raising of livestock. Husbandry has a long history, starting with the Neolithic Revolution when animals were first domesticated, from around 13,000 BC onwards, predating farming of the first crops. By the time of early civilisations such as ancient Egypt, cattle, sheep, goats, and pigs were being raised on farms.
Agricultural extensionAgricultural extension is the application of scientific research and new knowledge to agricultural practices through farmer education. The field of 'extension' now encompasses a wider range of communication and learning activities organized for rural people by educators from different disciplines, including agriculture, agricultural marketing, health, and business studies. Extension practitioners can be found throughout the world, usually working for government agencies.
Cash cropA cash crop, also called profit crop, is an agricultural crop which is grown to sell for profit. It is typically purchased by parties separate from a farm. The term is used to differentiate marketed crops from staple crop ("subsistence crop") in subsistence agriculture, which are those fed to the producer's own livestock or grown as food for the producer's family. In earlier times, cash crops were usually only a small (but vital) part of a farm's total yield, while today, especially in developed countries and among smallholders almost all crops are mainly grown for revenue.
Intensive farmingIntensive agriculture, also known as intensive farming (as opposed to extensive farming), conventional, or industrial agriculture, is a type of agriculture, both of crop plants and of animals, with higher levels of input and output per unit of agricultural land area. It is characterized by a low fallow ratio, higher use of inputs such as capital, labour, agrochemicals and water, and higher crop yields per unit land area. Most commercial agriculture is intensive in one or more ways.
Remote sensingRemote sensing is the acquisition of information about an object or phenomenon without making physical contact with the object, in contrast to in situ or on-site observation. The term is applied especially to acquiring information about Earth and other planets. Remote sensing is used in numerous fields, including geophysics, geography, land surveying and most Earth science disciplines (e.g. exploration geophysics, hydrology, ecology, meteorology, oceanography, glaciology, geology); it also has military, intelligence, commercial, economic, planning, and humanitarian applications, among others.
Crop diversityCrop diversity or crop biodiversity is the variety and variability of crops, plants used in agriculture, including their genetic and phenotypic characteristics. It is a subset of and a specific element of agricultural biodiversity. Over the past 50 years, there has been a major decline in two components of crop diversity; genetic diversity within each crop and the number of species commonly grown. Crop diversity loss threatens global food security, as the world's human population depends on a diminishing number of varieties of a diminishing number of crop species.
Agricultural engineeringAgricultural engineering, also known as agricultural and biosystems engineering, is the field of study and application of engineering science and designs principles for agriculture purposes, combining the various disciplines of mechanical, civil, electrical, food science, environmental, software, and chemical engineering to improve the efficiency of farms and agribusiness enterprises as well as to ensure sustainability of natural and renewable resources. An agricultural engineer is an engineer with an agriculture background.
LivestockLivestock are the domesticated animals raised in an agricultural setting to provide labor and produce diversified products for consumption such as meat, eggs, milk, fur, leather, and wool. The term is sometimes used to refer solely to animals who are raised for consumption, and sometimes used to refer solely to farmed ruminants, such as cattle, sheep, goats, and pigs. Horses are considered livestock in the United States. The USDA classifies pork, veal, beef, and lamb (mutton) as livestock, and all livestock as red meat.
Linear regressionIn statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). The case of one explanatory variable is called simple linear regression; for more than one, the process is called multiple linear regression. This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable.
