not sure if this helps but I hope it does
sorry its so long
To date erosion scientists have failed to address — or have addressed inadequately — some of the ‘big questions’ of our discipline. For example, where is erosion occurring? Why is it happening, and who is to blame? How serious is it? Who does it affect? What should be the response? Can we prevent it? What are the costs of erosion? Our inability or reluctance to answer such questions damages our credibility and is based on weaknesses in commonly-used approaches and the spatial and temporal scales at which much research is carried out. We have difficulty in the recognition, description and quantification of erosion, and limited information on the magnitude and frequency of events that cause erosion. In particular there has been a neglect of extreme events which are known to contribute substantially to total erosion. The inadequacy and frequent misuse of existing data leaves us open to the charge of exaggeration of the erosion problem (a la Lomborg).
Models need to be developed for many purposes and at many scales. Existing models have proved to be of limited value, in the real as opposed to the academic world, both because of problems with the reliability of their results, and difficulties (with associated costs) of acquiring suitable data. However, there are some positive signs: models are now being developed for purposes including addressing questions of off-site impacts and land-use policy. Cheap, reliable and technically simple methods of erosion assessment at the field scale are needed. At the global scale, an up-date of GLASOD based on a scientific approach is urgent so that we are at least able to identify erosion ‘hotspots’.
In terms of explanation of erosion, the greatest need is for a full recognition of the importance of socio-economic drivers. The accession of new countries to the EU with different economic and land-use histories emphasises this need. Too often we have left people, especially the farmers, out of the picture. Our approach could be characterised as ‘data-rich and people-poor’.
Answer: George Greenville's view on the debt issue was to impose new taxes on the colonies, which led to the American revolution after the colonies to stop working with Britain
Explanation:
George Greenville's view on the debt issue was to impose new taxes on the colonies, which led to the American revolution after the colonies to stop working with Britain. He devised a plan for new alcohol, paper notes and tea that were imported from the colonies. All these was a set up for the colonies to reject working with them.
It was not really right although it was needed for Britain to clear up their devt from the war. They would have imposed it with better measures having in mind the colonies.
My answer would be false.
Humans are not always subjected to the same limited factors because they
have intellect. They find ways to get by
when the need to solve these limits arises.
They do not let themselves be controlled by the elements but find ways
to get around these factors.
Pratap Singh Shah was the king of the Nepal. He couldn't continue the unification so long because of the political obstacles.
<h3>When did Pratap Singh Shah became king?</h3>
Pratap Singh Shah became the ruler of Nepal in 1775. Pratap Singh Shah ruled for for 36 months, from 1777 to 1779, before passing away at the age of 26 from natural causes. Rana Bahadur Shah, his two-year-old son, succeeded him.
He couldn't unify the territories of the nation because he did not actively participated in the process of the unification like his father who was greatly involved and political crises also didn't allowed to do so.
Learn more about unification here:
brainly.com/question/4979723
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Answer:
The correct answer is : Quicker
Explanation:
Negative stereotypes can have harmful and the quality of social life can be affected. Also, this phenomenon can reduce self-esteem, motivation, and intellectual performance of people. These things are unconscious but they can have a negative impact on people when is not managed properly.
