- Mar 2016
The maps and statistics we present can be used as an initial reference for a number of countries lacking such data, as a spur to capacity building in the establishment of national-scale forest extent and change maps, and as a basis of comparison in evolving national monitoring methods.
The authors' results and analyzed data are a great jumping off point for governments that want to better understand how their country's land is changing with time.
These results can then be used to implement policies that manage or protect land where needed.
To look at the maps of forest change data from Hansen and colleagues, click here.
2005 extratropical cyclone led to a historic blowdown of southern Sweden temperate forests
For more information about Sweden's 2005 Cyclone Gudrun, click here.
Why is carbon storage important? Find out by following this link to explore carbon "sequestration" (just a fancy term for "storage") and how this process can help curb global warming.
Recently reported reductions in Brazilian rainforest clearing over the past decade (5) were confirmed,
Hansen and colleagues are referring to previous work conducted by the Brazilian government, which looked at forest loss in the Amazon.
This report from the Brazilian government shows that Brazil's forest protection laws are effective (i.e., the rate of forest loss in the Amazon is steadily declining).
importance of forest ecosystem services
What are important ecosystem services that forests provide?
First, let's break this down into what an ecosystem service is. These services include any benefit that an ecosystem can provide to people.
So, what can forests provide that benefit people? Here are some examples: Forests provide timber, store carbon, purify air and water, and provide space for recreation (e.g., hiking in the woods!).
The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year.
When comparing across different climate domains (i.e., tropical, subtropical, temperate, or boreal), Hansen and colleagues found that only the tropics showed a clear change in the rate of forest loss during the time that they surveyed (2000–12).
In this case, forests are decreasing rapidly in the tropics and in the next sentence we find out exactly where this decrease is taking place; mainly in Malaysia, Paraguay, Bolivia, Zambia, and Angola.
Take a look at Google Maps to find the location of these countries.
Richness is simply the number of different species.
Biodiversity refers to the diversity of biology (a.k.a. the number of different species).
Putting this all together, we can determine that forests, compared with other types of ecosystems (e.g., deserts), have a lot of different species of plants, animals, bacteria, etc. (this is especially the case in tropical forests).
However, spatially and temporally detailed information on global-scale forest change does not exist; previous efforts have been either sample-based or employed coarse spatial resolution data (2–4).
Hansen and colleagues are building off of previous scientific research that addressed this same issue of trying to figure out how forests are changing around the world.
The main difference between this study and previous work is that technology has improved in such a way that we can now look at the entire globe at a very fine resolution to determine where and how our forests are changing through time.
We mapped global tree cover extent, loss, and gain for the period from 2000 to 2012 at a spatial resolution of 30 m, with loss allocated annually.
Hansen and colleagues looked at satellite images of Earth (see "Landsat data") for every year from 2000 to 2012 and determined how much of Earth is covered in forest, and whether forests increased or decreased in size from year to year.
This method involves a lot of computer processing, because the raw satellite images need to be screened and assessed before they can be used.
Hansen and colleagues performed the computational processing in Google's Earth Engine.
Describes where things are in relation to each other. In this case, the satellite images of Earth provide a clear picture of where forests are located and distributed.
Imagine having spatially explicit data of Earth's surface, all collected at the same time. This is what satellite-based imaging systems do. By examining these pictures over time, we are able to map forest loss and gain. Imagine trying to do this task from the ground. It would be very hard indeed.
being derived through an internally consistent approach that is exempt from the vagaries of different definitions, methods, and data inputs
This sentence is referring to how Hansen and colleagues used Landsat data (e.g., the satellite images of Earth), which is all collected in exactly the same way each time. Thus, there are no inconsistencies between one sampling event (e.g., photo) and another sampling event.
tropical, subtropical, temperate, and boreal
Tropical: Areas near Earth's equator that are warm/hot year-round with consistent or seasonal rainfall.
Subtropical: Areas with hot and humid summers and mild winters.
Temperate: Areas with four seasons (summer, fall/autumn, winter, and spring) divided mainly by differences in temperature.
Boreal: Subarctic areas with long, cold winters and short, cool summers.
Check out where these climate domains/zones are around the world on this map.
"Deforestation dynamics" refers to changes (i.e., dynamics) in forests due to cutting down trees and replacing them with nonforest land uses, such as agriculture or development (houses, buildings, etc.).
statistically significant trend
This wording implies that Hansen and colleagues ran a statistical model to determine whether the loss or gain in forest cover over time was more or less than what you would expect if forest cover did not change.
The tropics experienced a clear increasing rate of forest loss, expressed in units of forest area loss per year, whereas other climate domains (e.g., temperate, boreal, subtropical) all lost and gained forest cover
However, when you add all of the subtropical regions of Earth together, for instance, there isn't a clear net loss or gain in forest cover. This is because of the fact that most forest change in the subtropics is due to forestry land uses where trees are grown as a crop. In forestry land uses, trees are continuously grown and cut down to make products such as lumber and paper.
The converging rates of forest disturbance of Indonesia and Brazil are shown in Fig. 3
Hansen and colleagues use linear models (y=mx+b) to test whether the trends in forest loss in Indonesia and Brazil are both significant through time. What did they find?
Subtropical forests experience extensive forestry land uses where forests are often treated as a crop and the presence of long-lived natural forests is comparatively rare (8). As a result, the highest proportional losses of forest cover and the lowest ratio of loss to gain (1.2 for >50% of tree cover) occurred in the subtropical climate domain.
Many subtropical forests are treated like crops (e.g., corn, soybean). As such, the trees are cut down and harvested for timber and then replanted for the next harvest season.
Thus, this climate domain experienced the most forest loss while also having the lowest ratio of loss to gain (because the trees that were harvested were subsequently replanted).
To see an example of this, check out an article on forest landowners in Mississippi here.
short-cycle tree planting and harvesting
This statement refers to "short rotation forestry," which is a type of forestry that densely plants fast-growing tree species (e.g., poplar trees).
Once these trees reach a certain size (e.g., stems that are 10–20 cm in diameter at breast height), they are then cut down and harvested for lumber, pulp, and paper products, or energy.
The trees then regrow from the stumps, sending up new trunks. This process of cutting down a tree to stimulate regrowth is called "coppice."
Russia has the most forest loss globally.
Out of all countries, Russia lost the most forest cover from 2000 to 2012. Why do you think Russia has lost more forest cover than any other country?
Look at this forest loss on this map (click on Forest Cover Loss 2000-2014).
The proportion of total aggregate forest change emphasizes countries with likely forestry practices by including both loss and gain in its calculation, whereas the proportion of loss to gain measure differentiates countries experiencing deforestation or another loss dynamic without a corresponding forest recovery signal.
By looking at the forest loss with or without subsequent forest gain, Hansen and colleagues can determine whether a country may have forestry programs or some other type of deforestation.
To explain, forestry programs treat forests as a crop in that the trees are harvested and subsequently replanted/regrown until the next harvest, and so on. Thus, countries that experience forest loss and subsequent gain likely have forestry programs.
Countries that have forest loss without much forest gain probably do not have forestry programs, and thus the deforestation is caused by some other factor. What could be some other causes of deforestation?
trends in deforestation
Check out this Landsat time-lapse video from 1984-2012 of Brazil's Amazon Basin.
systematic global image acquisitions
In this context, the authors are describing the satellite images—these images are widespread (e.g., systemic) in that they photograph the entire surface of Earth.
The authors used Google Earth Engine to process the Landsat images.
The Google Earth Engine is a cloud platform, meaning that a network of thousands of computers works together to perform a task that a single computer would take years to do.
Similarly, Google Cloud provides the same features. Google Cloud allows you to store, manage, and process information on computer servers that are accessed through the Google Cloud website.
Cloud computing is especially helpful for processing large amounts of data/information.
Hansen and colleagues processed 700,000 images of Earth. Processing this information through the Google Earth Engine with 10,000 computers took approximately 15 days. If the authors only had one computer to work with, these calculations would have taken a few years!
efficiently process and characterize global-scale time-series data sets in quantifying land change
Hansen and colleagues are illustrating how the work they conducted in this study can be applied and used by governments around the globe to monitor changes in land cover over time.
Also, to clarify, "time-series data sets" refers to how their data (forest cover measurements) were collected, i.e., in this case in a series of collections through time (one collection of satellite images of Earth for each year from 2000 to 2012).
Science is collaborative and support from scientific research can come from many different sources. Check out which organizations helped to fund this research.
Several recent studies have found that greater political conservatism predicts higher levels of self-reported happiness and life satisfaction in the United States
This means that previous research studies have found that an individual's happiness/life satisfaction can be statistically predicted, based on how conservative or liberal that person is; the more conservative people are, the happier they say they are.
personality dimensions related to defensive forms of motivated social cognition
In a meta-analysis, Jost, Glaser, Kruglanski, and Sulloway (2003) found that political conservatism was associated with a number of individual differences (such as openness to experience and fear of threat and loss) that relate to the motivation to manage uncertainty and threat.
Self-enhancing tendencies are not evenly distributed across populations
Heine, Kitayama, and Hamamura (2007) show support for the idea that people from Western/individualist cultures self-enhance significantly more than people from Eastern/collectivist cultures.
A bootstrapped mediation analysis revealed that, as hypothesized, self-deceptive enhancement fully mediated the ideology–life satisfaction association [indirect effect:b = 0.05, P < 0.001, 95% confidence interval (CI) = (0.03, 0.07)
These results indicate that the relationship between political conservatism and life satisfaction can be statistically explained by self-deceptive enhancement.
With this kind of mediation analysis, the effect is said to be significant when the 95% confidence interval (in this case, from 0.03 to 0.07) does not include zero within its range. See this website for some more information.
Greater conservatism was associated with a small but significant decrease in positive affect word use (β = –0.16, P < 0.001). Conservatism was not significantly associated with the use of negative affect words, joviality-related words, or sadness-related words (Table 2).
The results from this analysis indicate that, as political conservatism (according to voting record) increases, use of positive affect words decreases.
There is no statistical relationship between political conservatism and use of negative affect words, joviality words, or sadness words.
Critical thinking: Why do you think there was a relationship for positive affect, but not joviality?
Logistic regressions predicting the presence or absence of emotion words/emoticons at the tweet level were conducted, with political party followed as the independent variable
The researchers examined whether or not an individual's usage of positive/negative words and emoticons in tweets could be statistically predicted based on that individual's assumed political party affiliation (either Democrat or Republican).
In study 4, we analyzed 457 publicly available photographs of individuals from LinkedIn, a business-oriented social networking Web site.
This study is essentially the same as the one that examined photographs of members of Congress (Study 2), but this one uses photographs from a business setting, rather than a political one.
analysis of each politician’s voting record
You can check out these "legislative scorecards" yourself, here.
A key difference is that these previous accounts would predict happiness-related behavior to correspond with self-report evidence of greater conservative happiness. Our self-enhancement-based account explains this discrepancy.
The authors point out that previous research would suggest that self-reported happiness should match behavioral indications of happiness; the fact that their studies show the opposite finding, they argue, can be explained through self-enhancement.
Connects to Vision and Change Core Competency #1: ability to apply the process of science.
The authors look beyond their own conclusions and consider additional questions that should be investigated in the future.
inform public policy
Connects to Vision and Change Core Competency #6: ability to understand the relationship between science and society.
The authors relate their findings to the link between psychological research and public policy.
nonrandomized groups (e.g., cultures, nations, and religious groups)
The experiments in this article also use nonrandomized groups (i.e., participants cannot be randomly assigned to be a member of the Democratic or Republican party).
How might you run a similar study using randomized groups? What would this add to our understanding of happiness?
This connects to Science Practices for AP Biology Practice 3: The student can engage in scientific questioning to extend thinking or to guide investigations within the context of the AP course.
S. E. Taylor, J. D. Brown , Illusion and well-being: A social psychological perspective on mental health. Psychol. Bull. 103, 193–210 (1988).
In this paper, the authors argue that positive self-biases (overly positive self-evaluations, illusion of personal control, and unrealistic optimism) are characteristic of normal human thought.
In addition, the authors say that these positive illusions are adaptive and beneficial for mental health, in that they promote more satisfying connections with others, greater productivity, and greater resilience in response to negative feedback.
Others portray conservatism as a protective or even defensive mechanism that serves the palliative function of justifying troubling societal inequalities
This research, by Napier and Jost (2008), found that the happiness gap between conservatives and liberals could be explained by the fact that political conservatives are more likely than liberals to rationalize inequality.
In one study, the researchers looked at U.S. economic inequality over time (from 1974 to 2004), and found that, in general, more inequality was associated with lower well-being, but that conservatives seemed to be somewhat buffered from this effect. As inequality goes up, well-being goes down a lot for liberals, but only a little for conservatives.
Other research (for example, Jost and Hunyady, 2002) also shows that conservatives are generally more likely to view the status quo (or, the way things are now) as being fair.
So, the implication is that conservatives seem to be less bothered by inequality.
systematic methodological artifacts due to common method variance
The argument here is that if research relies too much on just one way of doing things (in this case, using self-report), then this single methodology might be overlooking an important issue.
many challenges involved in self-report research
For example, Zou and Schimmack (2013) argue that self-report measures should look at multiple raters; that is, in addition to asking participants about themselves, researchers should also validate those ratings by asking the same questions to people (family, friends) who know the participant well.
it is possible that ideological happiness differences may simply be an example of conservatives’ stronger tendency to evaluate the self favorably.
Connects to NGSS Practice 1 (Asking questions [for science] and defining problems [for engineering]) and Practice 3 (Planning and carrying out investigations).
How would you design a study to evaluate this idea? How do the researchers go about testing their hypotheses?
whether conservatives’ reports of greater subjective well-being, relative to liberals, could be attributed to self-enhancing tendencies
This is the main hypothesis for Study 1. The authors predict that the reason why conservatives report higher levels of well-being is that, compared with liberals, conservatives are more likely to self-enhance.
Non-Duchenne smiling is also less predictive than Duchenne smiling of beneficial long-term psychological and physical health outcomes
For example, research by Harker and Keltner (2001) showed that, compared with non-Duchenne smiles, displays of Duchenne smiling in yearbook photographs were associated with higher levels of personal well-being at ages 21, 27, 43, and 52.
Members of the liberal-leaning Democratic Party used a higher ratio of positive to negative affect words (M = 13.65:1) than members of the conservative-leaning Republican Party (M = 11.50:1), including a higher frequency of positive affect word usage in 17 of 18 years.
Democrats tended to use one negative word for every 13.65 positive words. This negative word usage is less frequent than Republicans, who used one negative word for every 11.5 positive words.
conservatism predicted significantly less intense facial action in the muscles around the eyes that indicate genuine happiness (AU6: β = –0.13, P = 0.031). The odds of displaying non-Duchenne smiles (i.e., action in AU12 but not AU6) were slightly higher for conservatives than for liberals, but this did not reach statistical significance [controlling for demographics: odds ratio (OR) = 1.04, P = 0.206].
That is, the results indicate that although conservatives were not significantly more likely than liberals to not use the orbicularis oculi at all, conservatives were likely to display less muscle activation around the eyes, compared with liberals.
R. E. Nisbett, T. D. Wilson , Telling more than we can know: Verbal reports on mental processes. Psychol. Rev. 84, 231–259 (1977).
Here, Nisbett and Wilson review evidence that supports the idea that people generally have relatively little insight into their own psychological/cognitive processes. When it comes to the process of a stimulus causing/influencing a response, people can be unaware of the stimulus itself, unaware of the response, or unaware of how the stimulus influenced the response.
The authors argue that although people can attempt to report on the mechanisms that underlie their thoughts, decisions, etc., these self-reported explanations are not necessarily accurate, and they rely more on people's lay theories about how cognition should work, as opposed to how it actually does work.
S. P. Wojcik, P. H. Ditto , Motivated happiness: Self-enhancement inflates self-reported subjective well-being. Soc. Psychol. Personal. Sci. 5, 825–834 (2014).
Here, the authors report on the "happier-than-average effect," which shows that greater self-enhancement (either because of individual differences or experimental manipulation) leads to greater reports of subjective well-being.
J. R. Hibbing, K. B. Smith, J. R. Alford , Differences in negativity bias underlie variations in political ideology. Behav. Brain Sci. 37, 297–307 (2014).
Hibbing, Smith, and Alford argue that individuals' reactions, both physiological and psychological, to negative events and stimuli underlie a major part of the differences between political liberals and conservatives. Their argument centers around the idea that, compared with liberals, conservatives display greater responses to negativity.
M. H. Kernis , Toward a conceptualization of optimal self-esteem. Psychol. Inq. 14, 1–26 (2003).
This theoretical paper examines the potential for differences between high self-esteem and "optimal" self-esteem. Kernis makes the argument that high self-esteem can be either fragile (nonoptimal) or secure (optimal), depending on factors such as the defensiveness and stability of that self-esteem.
growing interest in using self-report measures of happiness to inform public policy
In his book, Gross National Happiness, Brooks examines the "happiness gap" in the United States and argues that values such as faith, hard work, and individual liberty cause happiness, whereas factors like secularism and an overreliance on government promote unhappiness.
The book focuses on culture, politics, religion, and economics. Brooks's conclusion includes suggestions on how the U.S. government can help facilitate happiness.