text:
We strongly oppose the government's proposals to amend the Hunting Act 2004 using a draft Order. The government proposes to use a statutory instrument to change the exemptions under the Act, in order to use an unlimited number of dogs in exempt cases. At present, the exemptions only apply where a maximum of two dogs are used. The government claims that it is amending the exemptions to bring them into line with the position in Scotland, under the Protection of Mammals (Scotland) Act 2002.
"The use of a draft Order, rather than a Bill to amend, is a good example of 'cherry picking' some of the bits of the Scottish legislation that favour hunters, without also taking on the related obligations. Most notably, the Scottish legislation has the possibility of higher penalties to go with its more liberal approach to the number of dogs used. The power to amend the existing exemptions by Order does not permit amendment of penalties and thus underlines the inappropriateness of the approach of using a draft Order.
It should also be noted that there are only 10 registered hunts in Scotland, compared to the 310 in England and Wales, so the issues of enforcement are hardly comparable.
If the government wishes to amend or repeal the Hunting Act 2004, it should have the guts to bring forward a Bill, as it suggested it would during the election campaign. They are simply running scared of the level of opposition such a move would produce.
80 percent of the electorate is against the repeal of the Hunting Act 2004. The draft Order is a move to avoid the kind of debate that a Bill would engender and to curtail the time allowed for debate on the proposed changes.
The government's supporters have suggested that the Order would only bring the legislation in England in Wales in line with that in Scotland but this isn't the case. Were the Order to be made there would be important differences between the legislation.
I believe this is an attempt to reintroduce hunting by stealth and I strongly oppose it.
The SNP as a party, oppose fox hunting and this latest statement from Nicola Sturgeon is encouraging; 'If 'research' in England and Wales encourages a resurgence in traditional fox hunting simply because prosecutions would be difficult to secure, that could be seen as encouraging Scottish hunts to take a similar route. So we have every right to protect Scottish Laws, and therefore we may vote against government plans'.
Comparing the Protection of Wild Mammals (Scotland) Act 2002, Hunting Act 2004 and 2015 Draft Amendments
The government claims that proposed changes to the Hunting Act 2004 would simply bring parity between Scotland and the rest of Britain are deeply misleading. The Scottish law preceded Westminster's by two years, with stricter exemptions included in the latter as a deliberate improvement.
Indeed, the experience in England and Wales has shown the Hunting Act (2004) to be the better piece of legislation, with more than 400 convictions since its inception. The difficulty in proving intent under the Scottish law has meant little enforcement of the law has happened north of the border. As the Scottish Countryside Alliance said on the 10th anniversary of the Protection of Wild Mammals (Scotland) Act, 'you could be forgiven for thinking little has changed during the course of time'
It is also important to remember that Scotland has only 10 registered hunts, while England and Wales have a total of 310. If parity is to be sought, surely the minority should come in line with the majority. More importantly, the proposed amendments to the Hunting Act 2004 would actually make this the weaker law. The changes and their implications are set out below.
Current exemptions permitted under Hunting Act 2004 and equivalent provisions in PWMA 2002
Stalking and flushing out
HA 2004 Schedule 1 paragraph 1
Currently, two dogs can be used to flush a wild mammal out of cover if undertaken for purpose of reducing serious damage animal would cause to livestock, game birds, crops, timber, fisheries, property or biodiversity; also to obtain meat for human consumption and participate in a field trial for retrieval dogs.
Reasonable steps must be taken to ensure the animal is shot as soon as possible after being flushed and shot by a competent person. Each dog used in the flushing must be kept under sufficient control to ensure it does not interfere with the mammal being shot quickly.
PWMA 2002 section 2:
An unlimited number of dogs can be used to flush a wild mammal from cover for the purposes of protecting livestock, timber, ground-nesting birds, game birds, and crops; to provide food for human consumption; protect human health; prevent the spread of disease; control a pest species; or control number of a species to safeguard welfare of that species.
2015 Draft Amendment
Removes the limitation on the number of dogs to be used under HA 2004, bringing parity with Scotland.
Use of dogs below ground
HA 2004 Schedule 1 paragraph 2
Currently, it is permissible to use one dog below ground to flush out a mammal to be shot if undertaken for purpose of preventing damage to birds kept for the purpose of being shot. The person using this exemption must have written evidence of landowner permission available for inspection by a constable. The mammal must be shot as soon as possible and the dog must be under sufficient control to prevent it interfering with the shooting of mammal. An enforceable code of practice only permits a "soft" terrier to be used to reduce the risk of a fight.
PWMA 2002 section 2(3)
Any number of dogs may be used to flush out a fox or mink from below ground for the same purposes as the PWMA stalking exception above. It must be flushed as soon as possible and shot as soon as possible after being flushed. In limited circumstances, a "hard" terrier is allowed to be used. A single dog may be used below ground to kill an orphaned fox cub.
2015 Draft Amendment
Widens the exemption to include using dogs below ground to protect livestock which brings parity with Scotland. Up to seven days will be allowed to produce written evidence of landowner permission.
Rescue of wild mammal
HA 2004 Schedule 1 paragraph 8
Applies to any mammal. No more than two dogs can be used. The hunt must believe that the animal is or may be injured and the hunting is undertaken to relieve its suffering.
PWMA 2002 section 5
An unlimited number of dogs may be used to locate a seriously injured or orphaned animal, but only if the person "acts to ensure that the mammal, once located, is captured, treated or killed as humanely as possible in order to relieve its suffering".
In Scotland this exemption does not cover below ground retrieval of mammals, save for the below ground retrieval of foxes that are believed to be orphaned and there the exemption applies only if the person "takes reasonable steps to ensure that the fox, once located, is dispatched by a single dog or otherwise killed as humanely as possible" - para 5(3).
2015 Draft Amendment
An unlimited number of dogs may be used, bringing parity with Scotland. The exemption is widened to include diseased animals, which is not included in the Scottish exemption. The draft Order does not introduce the Scottish requirements to act humanely.
Research and observation
HA 2004 Schedule 1 paragraph 9
Up to two dogs are allowed to be used for the purpose of or in connection with the observation or study of a wild mammal.
No such exception.
2015 Draft Amendment
An unlimited number of dogs may be used. Widens the exemption, which has no equivalent in Scotland.
Other differences
a. Meaning
The high court ruled that hunting does not include searching.
PWMA 2002 section 10(1)
Explicitly states that "to hunt" includes to search or to course.
No change in the draft amendment, so England and Wales is not brought into line with Scotland and maintains a weaker provision.
b. Penalties
HA 2004 section 6
Level 5 fine only, on summary conviction.
PWMA 2002 section 8(1)
Up to 6 months imprisonment and/or level 5 fine
No change in the draft amendment so England and Wales is not brought into line with Scotland and maintains a weaker provision.
c. Defence
HA 2004 Part 1(4)
It is a defence for a person to show that he reasonably believed that his hunting was exempt (even if it wasn't).
The same defence is available but only in limited circumstances.
No change in the draft amendment so England and Wales are not brought into line with Scotland and maintain a weaker provision.


text:
Two of the most difficult phrases to speak in the English language are �I�m sorry� and �We messed up.�
President Barack Obama confirmed that Monday with his response to the problems people have encountered trying to sign up for health insurance coverage under the Affordable Care Act.
HealthCare.gov went live Oct. 1, and those who attempted to access it and purchase coverage through its signature exchanges were greeted with crashes, slowdowns and timeouts. Some who got in made it almost through the process before their luck ran out and their registration didn�t take.
The problems haven�t disappeared, to the White House�s consternation, which prompted Obama�s appearance Monday at a staged event in the White House Rose Garden, in front of a group of supporters of the health-care reform package that colloquially bears his name.
Obama said there would be no �excuses� or �sugar-coating� of what�s happened. He said, �Nobody is more frustrated than me,� and insisted the website problems would be solved.
That was it, other than a strong defense of Obama-care�s merits. This president certainly is no Harry Truman as far as where the buck stops.
He�s probably right that the problems will be fixed. The White House has unleashed an army of technical experts from both the governmental and private sectors to straighten the website out, while adding people at Obama-care call centers to give people offline options for signing up.
That doesn�t erase the question of why the portal to the singular accomplishment Obama hopes will anchor his legacy in the history books wasn�t ready to go on Oct. 1.
The early spin was that the website was simply overwhelmed by the number of people seeking insurance. It turns out there were systems structure, software and computer code issues, some of which had manifested themselves before the rollout. Should anyone really be surprised to see problems with something that�s launched with fingers and toes tightly crossed?
Obama-care backers have said this is no big deal, that there were similar startup issues with other major social programs such as Medicare. That�s true, but the technological landscape is different and there are many more resources available in 2013 than there were in 1966. Why was the army of technical experts not brought in over the summer, if not earlier, to get this right?
Health and Human Services Secretary Kathleen Sibelius will testify about the situation next week before a congressional committee after initially balking. For Obama, her and other White House personnel to say �I�m sorry� and �We messed up� won�t undo any of what�s happened. It won�t restore the time people have lost on HealthCare.gov. It�s not likely to change people�s minds on Obama-care itself.
However, it might signal a new direction for this administration � a willingness to take responsibility for its actions when they don�t work as planned.
This editorial first appeared in the Gadsden Times, a Halifax Media Group newspaper in Alabama.

subset: commoncrawl


text:
Impact of maximum opening area constraints on profitability and biomass availability in forestry – a large, real world case
Borges P., Bergseng E., Eid T., Gobakken T. (2015). Impact of maximum opening area constraints on profitability and biomass availability in forestry – a large, real world case. Silva Fennica vol. 49 no. 5 article id 1347. https://doi.org/10.14214/sf.1347
The nature areas surrounding the capital of Norway (Oslomarka), comprising 1 700 km2 of forest land, are the recreational home turf for a population of 1.2 mill. people. These areas are highly valuable, not only for recreational purposes and biodiversity, but also for commercial activities. To assess the impacts of the challenges that Oslo municipality forest face in their management, we developed four optimization problems with different levels of management constraints. The constraints consider control of harvest level, guarantee of minimum old-growth forest area and maximum open area after final harvest. For the latter, to date, no appropriate analyses quantifying the impact of such a constraint on economy and biomass production have been carried out in Norway. The problem solved is large due to both the number of stands and number of treatment schedules. However, the model applied demonstrated its relevance for solving large problems involving maximum opening areas. The inclusion of maximum open area constraints caused 7.0% loss in NPV compared to the business as usual case with controlled harvest volume and minimum old-growth area. The estimated supply of 20-30 GWh annual energy from harvest residues could provide a small, but stable supply of energy to the municipality.
area restriction model; green-up; mixed integer programming; forest management planning; bioenergy
Received 7 April 2015 Accepted 10 July 2015 Published 1 September 2015
Views 83066
Available at https://doi.org/10.14214/sf.1347 | Download PDF
Forests provide multiple commodities such as ecosystem services, recreational values and economic gains. Decision-making in forest management, which includes an increasing number of commodities, many decision levels as well as spatial and temporal aspects, is a highly challenging task. Modelling such management is complex, analyses are time consuming and resource demanding, and require sophisticated and efficient solution methods to deal with the large amounts of data involved. The forest areas surrounding the capital of Norway (Oslomarka) are an example of a forest area where management and decision-making take place in a highly complex environment.
Oslomarka, comprising 1700 km2 of forest land located in five different counties (Oslo, Akershus, Buskerud, Oppland and Østfold), is the recreational home for a population of 1.2 mill. people (Ministry of Environment 2013). These areas are highly valuable, not only for recreational purposes and biodiversity, but also for commercial activities related to forestry and other industries. For a forest located close to a large city, potential energy production might be of more interest than the output in terms of volume of sawn wood and pulpwood. Energy from harvest residues could provide a small, but stable supply of energy to the municipalities. Activities relating to nature areas in Oslo and nearby municipalities are regulated by legislation, the Marka law (Act No. 35 of 5th June 2009). The major part of the area (70%) is privately owned, while the remaining areas are managed by municipalities or through commons. Most of the approximately 2 000 forest properties within Oslomarka are very small, but the largest property is a privately owned industrial forest (430 km2) and the second largest is the Oslo municipality forest (about 160 km2). There are obvious user conflicts in Oslomarka between a large population using the forest land for recreational purposes and sporting activities, a strong environmental lobby that wants to preserve as large areas as possible for biodiversity purposes and the forest owners with their commercial interests.
In addition to the Marka law, commercial forestry activities in Oslomarka are influenced by the Forestry Act (Act No. 31 of 27th May 2005). All forestry activities in Oslomarka are, like most of Norway, under the present PEFC certification regime (Norsk Skogsertifisering 2013), which is based on the standard "Living Forests: Standard for sustainable forest management in Norway" (Living Forest 2010). Local preferences are also reflected in the management. For example, the multi-purpose forest management plan for the part of Oslomarka belonging to Oslo municipality clearly states that "economic considerations are inferior to recreational and biological considerations" (Oslo Municipality 2007). Despite the environmental emphasis, roundwood is harvested and provides income for the municipality. Often referred to as the "green city" due to the large share of renewable energy in Oslo, with the municipality itself producing energy at two waste disposal plants, the forest is also a potential source of renewable energy.
The prevalent legislation and certification regime obviously have consequences for forest management and the subsequent possible range of silvicultural treatments, and accordingly also for profitability and quantities of timber and biomass to be harvested. In Norway, many studies have tried to quantify some of these consequences. As a scientific foundation for developing the "Living Forests standards" more than a decade ago, several comprehensive analyses quantified consequences of environmentally oriented constraints at national, regional and property level (Hoen et al. 1998, 2001; Eid et al. 2001, 2002). Later also Ask et al. (2005) and Bergseng et al. (2012, 2013) performed similar analyses focusing on consequences of environmentally oriented constraints on forest management.
The tool applied for all these analyses consists of a growth simulator (GAYA) and an optimization (J) tool controlled from a geographical information system (SGIS). First, GAYA simulates numerous treatment schedules for each stand (Hoen and Eid 1990; Hoen and Gobakken 1997; Gobakken 2003) and then the management problem is solved at forest level by linear programming (LP) using the J algorithm (Lappi 1992, 2003). Connecting GAYA, J and SGIS makes each stand an identifiable polygon with respect to forest characteristics. The environmentally oriented constraints considered in these studies have included for example maximum sustainable harvest levels (or maximum variations in harvest level over time), maintaining minimum proportions of old-growth forest, prolonged rotation cycles, retention trees, selective cutting in buffer zones related to key biotopes and water bodies (rivers and lakes). In the most comprehensive of these studies (Bergseng et al. 2012), the impacts on both economy and biodiversity were analysed based on data from Ski municipality forest with a management reflecting the local preferences as well as the current Norwegian forest certification system. Economic impacts were expressed as changes in net present value (NPV) and harvest level, while impacts on forest structure were expressed by variables such as old-growth proportions, growing stock, number of retention trees, size of buffer zones and amount of dead wood.
All the environmentally oriented constraints considered in these studies have been incorporated by means of simulations and linear programming. In the case of Oslomarka, however, there is an additional modelling challenge related to management as local regulations (Act No. 35 of 5th June 2009) defines that the connected open area after final harvests (clear cutting and seed tree cutting) should not exceed 3 ha. Although not specified in the regulations, this also means that adjacent areas cannot be harvested before the areas have been regenerated and trees have reached a height, which "visually can be considered as a forest". The motivation for including such constraints in forest management may be to reduce the effects of clear cutting on forest fragmentation and ecological processes, to disperse the potential impact on water quality from harvesting or to develop a forest with a variety of different age classes that favour high species richness. However, since Oslomarka is used by so many people, recreational and aesthetic aspects have been a main motivation (Gundersen et al. 2015).
Controlling harvested volume over time is one of the most used requirements in forest planning (Shan et al. 2009). Both in Norway and internationally there has been quite a lot of development to deal with such management. The common approach is a non-declining or even flow of harvested volume (e.g. Daust and Nelson 1993; McDill and Braze 2000; Hoen et al. 2001; Caro et al. 2003). More flexible approaches have also been used, such as allowing variations in the harvested volume, i.e. ensuring that it does not vary more than a certain percentage between consecutive planning periods (e.g. Falcão and Borges 2002; Rebain and McDill 2003; Crowe and Nelson 2005; Constantino et al. 2008; Borges et al. 2014ab) or by letting the model decide the optimal levels of harvest (Martins et al. 2014). Furthermore, requirements for maintaining minimum proportions of old-growth forest have frequently been addressed. This type of management can be implemented by simply requiring a percentage of the total area to be old-growth forest in each planning period or it may be extended by specifying the amount of area in old-growth for each site quality class present in the forest area (e.g. Eid et al. 2001, 2002).
The previous requirements are affected by the spatial structure in the landscape, i.e. the relative arrangement of patches or the relative arrangement of harvest areas. In general, there are two different approaches when including spatial considerations in forest planning: the exogenous approach and the endogenous approach. When the exogenous approach is used, no spatial information is included in the optimization algorithm. Instead, the optimization process uses predetermined spatial constraints (e.g. Bergseng et al. 2012). In the endogenous approach, the optimization algorithms include spatial information and the optimization process determines the spatial arrangement of features such as harvested areas or old forest stands (e.g. Murray 1999; Öhman 2000). One advantage of the latter approach is that this approach can evaluate a very large number of spatial arrangements and allow trade-off analyses between different objectives. However, if the endogenous approach is used, effective constraint structures and efficient optimization models must be developed to control the impacts of management activities in one area on the surrounding areas.
A spatial endogenous approach widely used in forest planning is constraining the size of final harvests to a maximum area (e.g. Thompson et al. 1973; Murray 1999; McDill and Braze 2000). This type of constraint is known as adjacency constraints in harvest scheduling and the works of Roise (1990), Nelson and Brodie (1990), Dahlin and Sallnäs (1993), Weintraub et al. (1994) and Borges et al. (1999) were pioneering approaches to model and solve problems involving these constraints. Depending on the size of stands relative to the maximum final harvest area, two approaches can be applied. The unit restriction model (URM) constraints harvest of neighbouring stands while the area restriction model (ARM) constraints the area of final harvests to a maximum area of contiguous stands (Murray 1999). The constraints that prohibits final harvest in stands before final harvested areas have been regenerated is known in forest planning as green-up constraints. The URM and ARM approaches are specific cases of green-up constraints where the green-up time (regeneration of final harvested areas) is one planning period, which coincides with the planning period when the final harvest occurs. In both URM and ARM approaches, extending the green-up time for more than one planning period lead to a more general concept known as maximum opening area (MOA) constraints, where an open area is defined either as an area finally harvested or as an area in a regeneration state (e.g. Boston and Sessions 2006). The aim is then to guarantee that MOA is not exceeded (e.g. Crowe et al. 2003; Gunn and Richards 2005; Goycoolea et al. 2005, 2009; Borges et al. 2015).
Most of the forest planning literature involving green-up constraints assume a fixed length for green-up (Shan et al. 2009). However, modelling green-up constraints with a fixed length for green-up does not reflect entirely the dynamics of forestry. The regeneration strategy (Boston et al. 2009) as well as site productivity of stands (Borges et al. 2015) have influence on the time that a stand needs to regenerate, i.e. time for trees to reach a certain height where the stand is no longer considered as an open area. By considering variable length for the green-up time, the economic impact of such constraints may be reduced (Boston et al. 2009; Borges et al. 2015).
To our knowledge, the studies of Boston et al. (2009) and Borges et al. (2015) are the only ones that have considered a variable length for green-up time. Boston et al. (2009) treated the green-up length as a decision variable and different regeneration efforts were tested. Borges et al. (2015) retrieved the green-up length for each stand from empirical data by considering tree species and site index of each stand. They also used height predicted from a growth model to formulate the MOA constraints. However, only planting was used as regeneration method. This is obviously a simplification of the real situation where natural regeneration is an important option. In Norwegian forest conditions, it is optimal to regenerate using planting only for medium and high site productivity. However, the green-up constraint will also influence the choice of regeneration because shortening the green-up will open the possibility for harvesting neighbouring stands.
The forest problems considered in both of these studies were relatively small in terms of number of stands and respective treatment schedules. Nevertheless, due to the nature of these type of problems (mixed-integer), the respective solution space and solving time can be large even for small problems. Therefore, when addressing "real" and "large" problems with a large number of stands, planning periods and regeneration options, such as in the Oslo municipality forest, it is important to demonstrate alternative problem formulations that can be solved within a reasonable amount of time. Moreover, in Norway, real case studies involving spatial endogenous approaches such as considering maximum opening area constraints in final harvests are scarce. The works from Hasle et al. (2000) and Stølevik et al. (2007) are the fewest in Norway. In both works, the authors used heuristic procedures to solve problems encompassing 700 and 1 541 forest stands.
The main objective of this study is to model and quantify the impact of maximum opening area constraints on profitability and biomass availability for Oslo municipality forest. We combine the ideas and experience from Boston et al. (2009) and Borges et al. (2015) in a large, real world case where the green-up constraints reflect the effects of different regeneration options (planting and natural regeneration), regenerated tree species and site productivity of each stand. Additionally, we explore management options and constraints related to controlled harvest volume and minimum old-growth forest areas, and their effects. In all analyses, we use forest inventory data covering the entire Oslo municipality forest.
The basis for our analyses is a forest inventory from 2010 carried out by the inventory company Foran Norway AS. According to this, the Oslo municipality forest property covers a total area of 15 538 ha, of which 12 508 ha is forest area and 12 084 ha is productive forest area. The tree species distribution (based on volume) are spruce (58%), pine (31%) and deciduous (11%), generating a total volume of 1.84 million m3. The productive forest areas distributed over ages classes and site index classes are shown in Table 1. Site index is presented according to the H40-system, i.e. dominant height in meters at breast height age 40 years (Tveite 1977; Braastad 1980).
|Table 1. Relative distribution of the productive forest area (%) distributed over age class (years) and site index (H40 - m).
|Site index
|Age class
|< 7.5
|[7.5, 9.5[
|[9.5, 12.5[
|[12.5, 15.5[
|[15.5, 18.5[
|[18.5, 21.5[
|≥ 21.5
|> = 121
According to the forest inventory, the productive forest area is divided into 7 081 stands. Due to the constraints on maximum opening areas, we have split all stands larger than 3 ha randomly. The only requirement is that after the splitting, the resulting stands should at least be greater than 100 m2. This area is the minimum area that the growth simulator GAYA accepts for simulation of treatment schedules. After splitting, the total number of stands is thus 8 874, the average stand size is 1.41 ha with minimum 0.01 ha and maximum 2.99 ha. The distribution of the stands over different size classes is shown in Table 2.
|Table 2. Distribution of the stands over size classes.
|Size class (ha)
|0.00– 0.25
|0.25– 0.50
|0.50– 0.75
|0.75– 1.00
|1.00– 1.25
|1.25– 1.50
|1.50– 1.75
|1.75– 2.00
|2.00– 2.25
|2.25– 2.50
|2.50– 2.75
|2.75– 3.00
|No. of stands
The management of the Oslo municipality forest is based on a multi-purpose plan for the period 2007–2015 (Oslo Municipality 2007). The plan is made in cooperation with a stakeholder group consisting of representatives of different user groups like recreationists and nature conservationists. The plan clearly states targets and guidelines for management: conserving natural and cultural aspects is of paramount importance, including enhancement of activities like recreation, skiing, fishing and cycling.
Management has changed dramatically over the years, with a decrease in harvest volumes from 25 000 m3 to 8 500 m3 annually over the past 15 years. This is due to the need for increasing old-growth area and more focus on recreational values. The management plan states that from 2010 the harvest level may be increased to 13 500 m3 per year from 2010. In the medium long term, 15 to 20 years from now, annual harvest of 20 000 m3 is considered realistic.
The growth simulator GAYA (Hoen and Eid 1990; Hoen and Gobakken 1997; Gobakken 2003) was applied to generate treatment schedules. The simulator takes as input data from the stands (age, site index, number of trees and basal area per ha, basal area mean diameter, dominant height, mean height by basal, etc.) and a set of rules which define how and when forest treatments may be applied. The output provides detailed information on common forest state variables (e.g. standing volumes, age) as well as treatments (e.g. harvested volumes) and corresponding economic values (incomes and costs) for each treatment schedule and for all planning periods. In addition, the NPV based on an infinite planning horizon, is provided for each treatment schedule. We applied a 3% real rate of return.
In the present study, we allowed the following treatments; natural regeneration and planting, pre-commercial thinning, conventional thinning and the two final harvest options clear cutting and seed tree cutting. Natural regeneration can also occur after a clear cutting. In seed tree cutting, a certain number of seed trees are left in forest at the time of final harvest. The seed trees are removed a certain number of years later depending on site index. This means that not only final harvests contribute to the harvested volume in a planning period but also seed tree removal and conventional thinning. Additionally, the different regeneration options have different economic efforts and have impact on the height development of a stand. Simulations were performed for ten 5-year planning periods (50 years planning horizon). The total number of treatment schedules generated was 319 033, i.e. an average of about 36 per stand, which produces a solution space of about 368874 solutions.
Compared to most previous works (see e.g. Murray and Church 1996; McDill and Braze 2000; Richards and Gunn 2000; Bettinger et al. 2002; Boston and Bettinger 2006; Tóth et al. 2013), where clear cutting is the only final harvest option, our approach include two final harvest options. It is also important to note that the two final harvest options have different implications for the regeneration costs and regeneration lag (time from harvest to establishment of new forest). The lag for a stand to regenerate after seed tree cutting may be 10–15 years depending on site index and tree species while planting takes place immediately after clear cutting. However, in seed tree cutting there is only a small or no direct regeneration costs while for planting both plant purchase costs and labour costs are included.
Forest fuel for energy purposes, i.e. harvest residues from roundwood harvests, are quantified using biomass expansion factors from Lehtonen et al. (2004). Following the procedures of Rørstad et al. (2010), we arrive at an estimate for retrievable amount of harvest residues. Cost of residue extraction (EUR ton–1) is estimated at stand level according to Nurmi (2007) and Rørstad et al. (2010), where estimates of productivity (ton h–1) are combined with machine costs (EUR h–1). To convert biomass into energy, we assume a fixed lower heating value equal to 5320 kWh ton–1 dead matter (d.m.). (19.2 GJ ton–1 d.m.) and 30% moisture content (of green weight). This means that the effective heating value delivered end user, i.e. exclusive of energy use efficiency, is 5029 kWh ton–1 d.m. (18.1 GJ ton–1 d.m.). By multiplying supply by this factor we get the supply in kWh (GJ).
The general model maximizes NPV. Only one treatment schedule was allowed within a stand. The general model also account for the harvested volume and the total area of old-growth forest in each planning period. Thus, the mathematical formulation was as follows:
N is the set of stands
TSi is the set of treatment schedules within stand i
T is the set of planning periods
PAi is the productive area of stand i
Ai is the area of stand i
Oit is the set of treatment schedules of stand i that produce an old-growth forest area in planning period t
HVt is total harvested volume in planning period t
OGt is total old-growth forest area in planning period t
hvikt is harvested volume in planning period t in stand i when treated by treatment schedule k
npvik is the NPV associated with stand i when treated by treatment schedule k
The decision variables yik takes the value 1 if treatment schedule k is applied to stand i, and 0otherwise. Thus, equation (1) defines the objective function which maximizes NPV, equation (2) defines the NPV, equations (3) and (6) secures that only one treatment schedule is allowed per stand, equation (4) and (5) define the total harvested volume and the total old-growth forest area in each planning period, respectively. Finally, (6) defines the domain of the decision variables. Moreover, the set Oit (old-growth forest area) was built taking into consideration both the age and the site quality (Eid et al. 2001, 2002). Thus, a stand is considered to be an old-growth forest area if the age ≥ 78, 91, 104, 117 130, 143 and 156 years, respectively, for site index H40 ≥ 21.5 m, 18.5 m ≤ H40 < 21.5 m, 15.5 m ≤ H40 < 18.5 m, 12.5 m ≤ H40 < 15.5 m, 9.5 m ≤ H40 < 12.5 m, 7.5 m ≤ H40 < 9.5 m and H40 < 7.5 m.
We developed four problems to assess the impacts of the challenges that the Oslo municipality face in their forest management (Table 3). These problems are constructed by successively adding constraints one at the time. The first problem is a "non-constrained" (Nc) optimization problem. The types of constraints successively added are "controlled harvest volume" (Ch), "minimum old-growth forest area" (Og) and "maximum open area" (Oa). We obtained the solutions of the four problems by using CPLEX 12.5 in an Intel(R) Xeon(R) X5650 with 2.67GHz CPU. Maximum run time allowed was 14 400 seconds and the number of threads was set to four.
|Table 3. List of problems and the respective types of constraints added successively to the general model.
|Type of constraint
|Controlled harvest volume
|Minimum old-growth forest area
|Maximum open area
|1- Non Constrained (Nc)
|2- Controlled harvest volume (Ch)
|3- Controlled harvest volume + Minimum old-growth forest area (ChOg)
|4- Controlled harvest volume + Minimum old-growth forest area + Maximum open area (ChOgOa)
The four problems and their respective formulations were as follows;
Problem 1. Non-Constrained (Nc):
The non-constrained problem formulation is described by the general model. Although termed non-constrained, the general model requires that only one treatment schedule is selected for each stand. This is formulated as a constraint in the model. As no other constraints are included, the treatment schedule with the highest NPV is selected for each stand.
Problem 2. Controlled harvest volume (Ch):
For Problem 2, we follow the implementation described by Borges et al. (2015) where the harvest volume in a planning period t (HVt) is not allowed to change more than a certain percentage from the harvested volume in the previous planning period. This implementation also forces the harvest volume in period 1 to be constrained by the harvest volume in the last planning period. This prevents a unique trend (usually decreasing in old forests) in the flow of the harvested volume over the planning horizon to occur. For this problem, the following set of inequalities was added to the general model;
where inequalities (7) and (8) define the variation allowed for the harvested volume between consecutive planning periods. The values of α1 and α2 define the levels of allowed variation in harvests and were set to 0.9 and 1.1, respectively, and correspond to a 10% allowed variation.
Problem 3. Controlled harvest volume + Minimum old-growth forest area (ChOg):
This problem extends Problem 2 by also requiring a minimum percentage of old-growth forest to be present in all planning periods. Thus, in addition to the constraints defined for Problem 2, the following inequality was added to the general model;
The values of βt define the percentage of the total area in planning period t that should be in an old-growth forest state. β was set to 0.2 for each period t meaning that at least 20% of the total forest area should be old-growth forest at all times. However, because the potential maximum amount of old-growth forest in the first four planning periods is below 20% of the total forest area (2 502 ha), i.e. 916, 1 202, 1 657 and 2 055 ha respectively in periods 1, 2, 3 and 4, we only consider this constraint for . This means that old-growth forest areas should increase over time until period 5.
Problem 4. Controlled harvest volume + Minimum old-growth forest area + Maximum open area (ChOgOa):
Problem 4 extends Problem 3 by adding a constraint on maximum open area. Since the simulation performed considers different final harvest options, i.e. clear cutting followed by planting or natural regeneration and seed tree cutting followed by natural regeneration, a formulation suggested by Borges et al. (2015) using tree height information (retrieved from the simulations) was applied. This approach has two advantages. First, it allows different green-up times (i.e. time from the final harvest until new trees are established and have reached a certain height) needed for the different regeneration options (planting and natural regeneration) without the need for additional decision variables (binary) to describe which regeneration option applied (see Boston et al. 2009). Second, this formulation indirectly considers the site index of the stands, i.e. the height information given by the GAYA simulator is a function of site index (Strand 1967; Tveite 1977; Braastad 1980).
Thus, the additional sets of constraints to be added to Problem 3 are as follows;
where, Zit is the set of treatment schedules of stand i producing a final harvest in planning period t, is the set of treatment schedules of stand i producing a height less or equal to µ meter in planning period t but not final harvest, Λ is the set of all minimally infeasible clusters. A minimally infeasible cluster is a set of stands with combined area greater than the MOA, and if a stand is removed from the cluster, the remaining stands in the cluster(s) will have a combined area less than or equal to the MOA (McDill et al. 2002).
The decision variables zit takes the value 1 if stand i is finally harvested in planning period t, and 0otherwise. The decision variables wit takes the value 1 if stand i is less than µ meter at planning period t but not from a final harvest in the same period and 0otherwise. Also the decision variable xit takes the value 1 if stand i is in an open state (areas larger than the maximum limit of 3 ha with a tree height below the minimum requirement of 2 meters) in planning period t, and 0otherwise. There is no need to declare these variables as binary, since the formulation will naturally force them to be either zero or one (for details, see Borges et al. 2015). Equations (11) and (12) relate variables yik with variables zit and wit, respectively. Equation (13) defines the open state of a stand i in planning period t, where open state occurs due to final harvested or if tree height is below the minimum requirement. Inequality (14) defines MOA constraints, i.e. the path constraints as described by McDill et al. (2002). For each minimally infeasible cluster, it is necessary to ensure that at least one stand of the cluster is not selected to avoid forming an open area (area in open state). In the present study, MOA and µ were set to 3 ha and 2 meters, respectively.
Net present value of Problem 1 (Non-constrained) was 67.8 mill. EUR while NPV of Problem 4 (Controlled harvest volume, minimum old-growth area and maximum open area) was 53.0 mill. EUR. The relative difference between these two problems in NPV, i.e. NPV-loss, was 21.8% (Table 4). When adding the MOA constraint to the other constraints, i.e. when comparing Problem 3 and 4, the NPV-loss was 7.0%.
|Table 4. NPV of each problem and NPV-loss between problems.
|NVP-loss between problems (%)
|(mill. EUR)
|2- Ch
|3 - ChOg
|4- ChOgOa
|1- Nc
|2- Ch
|3- ChOg
|4- ChOgOa
Harvested volumes for the different harvest options over planning periods and problems are displayed in Fig. 1. In the non-constrained problem (Problem 1-Nc), the first-period harvest is very large compared to other periods and compared to the other problems. This is due to the large areas of present old forest (see Table 1). Harvest volumes for period 1, and in total over all period, generally decrease when more constraints are added (Nc → Ch → ChOg → ChOgOa). Furthermore, over the first four periods harvest volumes generally decrease. After that, the pattern is less clear. In Problem 1, harvest volumes fluctuate according to how much mature forest area available in the respective periods. The other problems show a similar increasing trend in harvest volumes, with an exception of Problem 4, where the harvest volume decreases slightly in the last period.
Fig. 2 shows how areas allocated to regeneration method vary over planning periods and problems. Generally the amount of regenerated areas is closely correlated to harvests (Fig. 1) resulting in decreasing areas when more constraints are added. When considering all problems, the proportions of area allocated to planting and natural regeneration are varying in the interval between 20–80% over the periods. For Problem 4, the proportions of area regenerated by planting are constantly higher than natural regeneration for the first eight planning periods. For the last two planning periods, however, more than 70% of the harvested area is regenerated naturally. For Problems 1, 2 and 3, however, no particular regeneration patterns occur over planning periods.
The areas of old-growth increase when the requirement for old-growth areas is implemented (Problems 3 and 4) (see also Table 3). From planning period 5, the required 20% of old-growth forest is fulfilled for both problems and is held constant for the remaining periods. No accumulation of old-growth forest is observed in Problems 1 and 2. Table 5 shows the percentage of area in old-growth forest that remains as old-growth over the planning periods for Problems 3 and 4. For example, out of the 768 ha of old-growth forest present in period 1 in Problem 3, 100% still exist in period 5 before it decreases from 97% to 87% over the last five periods. Generally for both problems, almost all the existing old-growth forest from planning periods 1 to 4 also remains in period 5. From planning period 5 and onwards, at least 90% of the old-growth forest remains from one period to the next. The percentage of old-growth forest existing in planning period 5 that still exist in period 10, is 81% and 72% for Problems 3 and 4, respectively.
|Table 5. Old-growth forest areas (ha) over the planning periods, and share of old-growth forest that remain over planning periods for Problems 3 and 4.
| Old-growth forest
area (ha)
| Planning
|3- ChOg
|4- ChOgOa
Fig. 3 shows how the amount of areas in open state develops over periods. For Problem 4, where the open area and height requirements are implemented, there are still open areas in the first five planning periods (94, 33, 24, 24 and 8 ha, respectively) caused by already existing open areas before the simulations started. The amount of open areas from planning period 6 is zero. For the other problems, the open areas generally accumulate over the first periods, then stabilize and partly decrease again.
For a selected part of the municipality forest, Fig. 4 shows open state and old-growth forest areas in planning period 5 for Problems 3 and 4. For both problems, much of the old-growth forest area is the same. However, the patches of open areas are reduced considerably when introducing the MOA constraints (Problem 4).
The maximum energy potential for the different problems in different periods is shown in Fig. 5. The potential in period 1 for Problem 4 is 26.5 GWh. The energy potential closely follows harvest patterns (Fig. 1), and all problems with constraints on the harvest volume (2, 3 and 4), show the same general pattern with a slight decrease in the first periods and then an increase. For Problem 4, where all the constraints are implemented, the forest is able to provide 20–30 GWh annually from harvest residues over the 50-year period.
The present study models and investigates the effects of certain constraints on forest management in a large, area real world urban forest case covering the entire Oslo municipality forest. The constraints comprise a controlled level of harvest flow over time, a minimum requirement of areas with old-growth forest and a requirement of maximum open area (MOA). The constraints on maximum size of open area are statutory, and impose a series of adjacency dependencies that directly effects harvest options. The modelling of such management constraints is challenging to handle in an optimization framework, and analyses are time consuming and resource demanding, especially because our case study area is large. In this study, we combine ideas and experiences from Boston et al. (2009) and Borges et al. (2015), and mimic the management associated with this forest when solving the optimization problem. In the following, we first discuss some of the modelling challenges and then elaborate on some of the practical effects related to the management.
The initial distribution of stands with respect to size and site characteristics (see Table 2) is important when there is a requirement for MOA. Previous studies such the ones from Barret (1997) and, Borges and Hoganson (1999, 2000) have shown that the way stands are split to address MOA constraints have influence in both economic and spatial features (e.g. old growth area , types of edge). However, no specific rules regarding the way stands should be split are stated in the Marka law (Act No. 35 of 5th June 2009) and future work can be performed in this direction. The random splitting applied has increased the number of stands by 20% leading to a forest where 34% of the stands have an area lower than 1ha. This also influence the respective optimization problems since they can become difficult to solve if there are several clusters (contiguous stands) with many stands that can potentially form open areas in the same planning period. This is the case when the size of a typical stand is relatively small compared to the size of the MOA (e.g. McDill et al. 2002; Goycoolea et al. 2009). These concerns relate to the procedures that detect all the needed constraints, which are usually time demanding to compute, and to the time to solve the problem as well as the quality of the respective solution (McDill et al. 2002; Tóth et al. 2013). In our case study, the total number of adjacency constraints was 142 206 and the number of stands within these constraints varied between two and nine. This could make the problem very difficult to solve.
The amount of data incorporated into our case study is large due to both the number of stands, and due to the total number of treatment schedules, and respective final harvest and regeneration options. However, within the maximum time allowed (4 hours), in the worst case the solution value deviated at maximum 0.01% from the true optimum value. This must be considered as a very high quality solution and thus a good indication of the usefulness of the model described by Borges et al. (2015) in solving large problems involving MOA in forest planning.
The constraints on harvest flow and maximum open areas together with the requirement for old-growth forest area has a cost of ~20% in NPV (Problem 4, Table 4). The constraint on harvest flow is by itself fairly inexpensive, and also more realistic than the harvest pattern in the non-constrained problem. The largest reduction in NPV comes from conserving old-growth forest. The latter directly influence on forest area available for harvest and reduces the harvest potential accordingly. Bergseng et al. (2012) found that an old-growth requirement of 20% of the area gave a 9.5% decrease in NPV. Eid et al. (2002) showed that 10% old-growth forest gave a 3.5% decrease in NPV. These results are in line with the present results.
The situation in Oslo municipality forest, with a large initial proportion of old forest (Table 1), reflects the general conditions in Norwegian forests (e.g. Hoen et al. 2001). The loss in NPV will, when comparing different management problems as we have done in the present study, obviously be influenced by the initial distribution of the stands with respect to site characteristics. Eid et al. (2001) found large variations in NPV loss when imposing the same constraints on eight properties with very different initial conditions. A main lesson from this study, however, was that patterns between NPV loss and initial conditions were very hard to spot because of the combinatorial effects of the different constraints. Generally, NPV loss because of restrictions on MOA should be larger for forests dominated by old forest, but the constraints on harvest flow and MOA in combination makes it hard to judge on the effects of the age class distribution.
The gross annual harvest volume over the planning horizon is roughly 44 000 m3 (Problem 4, Fig. 1). With a 20% reduction due to bark, tops and other waste, annual sales volume equals approximately 35 000 m3. This is more than the 20 000 m3 medium to long-term harvest level suggested in the present management plan for Oslo municipality forest. The difference is to some extent probably caused by a very conservative suggestion in the management plan since focus is on recreation and conservation and our result is an upper limit to the potential harvest. Also, the management plan is based on a "rough" analysis of harvest potential without any efforts to model the true effects of the constraints on management. Furthermore, there may be other management constraints the municipality imposes on themselves that we have not modelled. This may lead us to an overestimation of the harvest potential. For instance, the results obtained would be influenced if selective cutting in border zones was included. Note that introducing selective cutting in border zones can be seen as a spatial exogenous approach. These zones are usually designed according to some criteria before the optimization process takes place and consequently become new stands with restricted treatment possibilities and might be contributing to the total amount of old-growth and reducing potential formation of open areas.
It is interesting to note that the inclusion of MOA requirements in Problem 4 had some impact on the proportions of area allocated to planting and natural regeneration (Fig. 2). Clearly, planting is used as much as possible in earlier planning periods to reduce green-up time, allowing more final harvests to occur that would be impossible with natural regeneration. In later periods, the proportion of planted areas decreases because the effect of green-up time becomes less important, i.e. at this stage little economic gain from final harvest activities will be obtained by reducing the green-up time. Consequently, the areas naturally regenerated increase, becoming the dominant regeneration method for the last two planning periods.
Since the study area is highly valuable not only for commercial forestry, but also for recreational purposes and biodiversity, we use the temporal overlap of old-growth forest throughout the planning periods, i.e. the percentage of area in old-growth forest that continues as old-growth over the planning periods, as a performance measure (Table 5). The results shows that introducing MOA constraints (Problem 4) lead to a lower rate of temporal overlaps as compared to Problem 3. Since the total amount of old-growth forest areas are similar in both Problems 3 and 4, this might also indicate that introducing MOA constraints are fragmenting old-growth forest areas (Figs. 3 and 4). However, this is not a major problem since the majority of the initial old-growth forest is largely scattered through the forest area with very few large patches (contiguous areas) of old-growth areas. Nevertheless, there is room for many future investigations such as introducing additional spatial requirements. For instance, requirements limiting the spatial dispersal of final harvests, maintaining or increasing the existing patches of old-growth forest. These may reduce fragmentation of old-growth forest areas and enhance biodiversity (e.g. Öhman and Eriksson 1998; Öhman 2000; Falcão and Borges 2002; Rebain and McDill 2003; Martins et al. 2005; Tóth and McDill 2007; Wei and Hoganson 2006, 2008; Öhman and Wikström 2008). Other possible management goals could be to cluster harvest activities to reduce machine transportation (e.g. Öhman and Eriksson 2010). Incorporating all these aspects may potentially lead to more realistic estimates for the harvest potential. However, they may also increase the difficulty in finding high quality solutions for the problem in a reasonable time. Therefore, the use of heuristics to obtain an initial lower bound for the problem may improve the solution time.
The total production of renewable energy in Oslo is 840 GWh of hot water for district heating and 160 GWh for electricity. With an estimated supply of 20–30 GWh annually from the most restrictive problem (Problem 4, Fig. 5), energy from harvest residues could provide a small, but stable supply of energy to the municipality. If more energy is needed from forest resources, roundwood may be used for energy purposes. Based on the above results for harvesting, using all pulp wood for energy purposes could provide 40–50 GWh annually. Depending on roundwood prices and energy prices, this could be a good strategy especially with respect to stability in energy production. Using forest resources for energy also provides flexibility, because unlike municipal waste, harvests can be moved easily in time and space. Forest based energy could hence constitute a raw-material buffer for production in the local energy system.
The problem solved in our case study is large due to both the number of stands and the total number of treatment schedules and respective final harvest options. Within the maximum time allowed, the solution value at maximum deviated 0.01% from the true optimum value, demonstrating the relevance of the model applied for solving large problems involving MOA in forest planning. The inclusion of MOA constraints as part of the planning for Oslo municipality forest caused 7.0% reduction in NPV compared to the case with only controlled harvest volume and minimum old-growth area. When including the MOA constraints, in addition the others, the estimated annual supply of 20–30 GWh energy from harvest residues, and 40–50 GWh if all pulpwood is used, could provide a small, but stable supply of energy to the municipality.
This work is funded by the Research Council of Norway, a number of industrial partners and participating research institutions, among them Norwegian University of Life Sciences, through the Norwegian Bioenergy Innovation Centre (CenBio). We are also grateful to Oslo Municipality for providing forest inventory data. We also would like to thank Karin Öhman, John Sessions and the anonymous reviewers for their valuable comments that improved the content of this manuscript.
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Stølevik M., Hasle G., Kloster O. (2007). Solving the long-term forest treatment scheduling problem. In: Hasle G., Lie K.A., Quak E. (ed.). Geometric Modelling, Numerical Simulation, and Optimization. Springer, Berlin, Heidelberg. p. 437–473. http://dx.doi.org/10.1007/978-3-540-68783-2_13.
Thompson E.F., Halterman B.G., Lyon T.J., Miller R.L. (1973). Integrating timber and wildlife management planning. Forestry Chronicle 49(6): 247–250. http://dx.doi.org/10.5558/tfc49247-6.
Tóth S.F., McDill M.E. (2007). Promoting large, compact mature forest patches in harvest scheduling models. Environmental Modeling & Assessment 13(1): 1–15. http://dx.doi.org/10.1007/s10666-006-9080-4.
Tóth S.F., McDill M.E., Könnyü N., George S. (2013). Testing the use of lazy constraints in solving area-based adjacency formulations of harvest scheduling models. Forest Science 59(2): 157–176.
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Wei Y., Hoganson H.M. (2006). Spatial information for scheduling core area production in forest planning. Canadian Journal of Forest Research 36(1): 23–33. http://dx.doi.org/10.1139/x05-233.
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Total of 69 references.


text:
I just bought a ne Mainboard ( Asus A7N8X-X).
I installed for the nforce devices the intel_8x0 for sound and forcedeth for networking.
Now I hear strange sound when I move the mouse, load data fron HDD or DVD. Even moving the curser with the arrowkey will make such sound.
What have I to mute such sounds?
my modules
soundcore 10848 1 snd
snd_page_alloc 10244 2 snd_intel8x0,snd_pcm
tsdev 8384 0
usbhid 48416 0
usb_storage 66752 1
ehci_hcd 37256 0
ohci_hcd 23044 0
uhci_hcd 33808 0
tvaudio 24356 0
msp3400 27816 0
bttv 160016 0
video_buf 22660 1 bttv
i2c_algo_bit 9864 1 bttv
v4l2_common 6272 1 bttv
btcx_risc 5384 1 bttv
tveeprom 13592 1 bttv
i2c_core 22784 5 tvaudio,msp3400,bttv,i2c_algo_bit,tveeprom
videodev 10368 1 bttv
forcedeth 20480 0
usbcore 127740 6 usbhid,usb_storage,ehci_hcd,ohci_hcd,uhci_hcd
rtc 14156 0
evdev 10240 0
thank you
try muting mic or other audio inputs.
It also helps if you have shielded cables
There's a similar problem with Via8235 onboard audio, actually. Try reducing your CD volume and see where that gets you.
thank you
muting the cd input makes things better but the problemn is still there.
i mute the bttv, this works on my system
[14:52] [sven@linux ~]$ dmesg
Jabber-ID: firstname.lastname@example.com
thank you
muting the cd input makes things better but the problemn is still there.
tried muting every other input? mic and others?
Wait a minute... Play an MP3 or something and reduce the Master volume while it's playing. Does the volume of the audio go down, or does it seem as though nothing has happened?
Do you have on-board sound? Then it might happen just because it's crappy. Try running glxgears. Do you hear something?
You can alleviate the problem by:
1) downclocking - by 50% you will get a good noise reduction
2) run kernel with "no-hlt" option (prevents from turning on and off the cpu, so the power supply is more stable)
Have you looked into the official nVIDIA sound drivers? I use them for the nVIDIA SoundStorm that came with my nForce2 and get Dolby Digital and hardware mixing. I am not sure if they work with later models, but they should. To do this, do `pacman -S nforce` And make sure no other sound modules are loaded or no other sound support exists in the kernel other than the basic sound support. Then load nvsound.
With this you get nvmixer for adjusting the volume. You can use nvmix-reg in order to store/restore the mixer settings. Cheers.
Man, this is nothing. On my system (Soltek nvidia mobo), I can see tiny-little noise on the screen when the CPU usage goes high. I tried changing video cables, shielding everything, playing with bios settings... it's still there. Fortunately it doesn't seem to affect stability.
It's the last time I invested my money in this nvidia bullshit. Hopefully I'll get a matrox G550 soon. Closed drivers = bad thing (Yes, apart from the noise I sometimes experience the infamous nvidia bug)
Open Source Software Operations/Nokia
michael.kostrzewa (at) nokia.com
I have this problem too on my asus A7N8X-deluxe, but I have 2 solutions for this problem
On my gentoo box I solved it with the following command:
setpci -s 0:00.0 6F.B=0F
I found it somewhere on a forum, it disables cpu disconnect or something like that. Anyway, it works nice, so I created a bootup script to execute it every bootup
But I installed archlinux a week ago and I used the latest nvidia drivers this time (they are in the extra repository) and I do not have the problem anymore. I can clearly hear the noise untill I type "modprobe nvsound", then it all disappears
If you can hear the CD player spinning away, you might want to remove the CD-in cable - it's no longer necessary for using CD audio.


text:
WASHINGTON (AP) -- It's the morning after and the controversy over how to sell emergency contraception still looms.
The Obama administration's top health official stopped plans Wednesday to let the Plan B morning-after pill move onto drugstore shelves next to the condoms.
Overruling scientists at the Food and Drug Administration, Health and Human Services Secretary Kathleen Sebelius decided that young girls shouldn't be able to buy the pill on their own, saying she was worried about confusing 11-year-olds.
For now, Plan B will stay behind pharmacy counters, available without a prescription only to those 17 and older who can prove their age.
It was the latest twist in a nearly decade-long push for easier access to pills that can prevent pregnancy after unprotected sex, and one with election-year implications. The move shocked women's health advocates, a key part of President Barack Obama's Democratic base, as well as major doctors groups that argue over-the-counter sales could lower the nation's high number of unplanned pregnancies.
"Secretary Sebelius took this action after careful review," Obama spokesman Nick Papas said. "As the secretary has stated, Plan B will remain available to all women who need it, and the president supports the secretary's decision."
Sebelius' decision is "medically inexplicable," said Dr. Robert Block of the American Academy of Pediatrics.
"I don't think 11-year-olds go into Rite Aid and buy anything," much less a single pill that costs about $50, added fellow AAP member Dr. Cora Breuner, a professor of pediatric and adolescent medicine at the University of Washington.
Instead, putting the morning-after pill next to the condoms and spermicides would increase access for those of more sexually active ages "who have made a serious error in having unprotected sex and should be able to respond to that kind of lack of judgment in a way that is timely as opposed to having to suffer permanent consequences," she said.
The move will anger many Democrats. Sen. Patty Murray of Washington, a member of the Senate leadership, already was asking Sebelius to explain her decision. But it also could serve to illustrate to independents, whose support will be critical in next fall's presidential election, that Obama is not the liberal ideologue Republicans claim.
Nor will this end the emergency contraception saga. In 2009, a federal judge said the FDA had let politics, not science, drive its initial behind-the-counter age restrictions and said it should reconsider. At a hearing scheduled in federal court in New York next Tuesday, the Center for Reproductive Rights will argue the FDA should be held in contempt.
Sebelius' decision pleased conservative critics.
"Take the politics out of it and it's a decision that reflect the concerns that many parents in America have," said Wendy Wright, an evangelical activist who helped lead the opposition to Plan B.
"This is the right decision based on a lack of scientific evidence that it's safe to allow minors access to this drug, much less over-the-counter," said Sen. Chuck Grassley, R-Iowa.
FDA Commissioner Dr. Margaret Hamburg made clear that the decision is highly unusual. She said her agency's drug-safety experts had carefully considered the question of young girls and she had agreed that Plan B's age limit should be lifted.
"There is adequate and reasonable, well-supported and science-based evidence that Plan B One-Step is safe and effective and should be approved for nonprescription use for all females of child-bearing potential," Hamburg wrote.
Pediatrician Breuner said taking Plan B, which contains a higher dose of the female progestin hormone that is in regular birth control pills, wouldn't harm even young adolescents.
Sebelius didn't raise safety concerns. She said maker Teva Pharmaceuticals hadn't proved that the very youngest girls who might try Plan B would understand how to use it properly.
A Teva-funded study tracked 11- to 17-year-olds who came to clinics seeking emergency contraception. Nearly 90 percent of them used Plan B safely and correctly without professional guidance, said Teva Vice President Amy Niemann. But Teva wouldn't say how many of the youngest girls were part of the study.
The company was determining its next steps.
Taking Plan B within 72 hours of rape, condom failure or just forgetting regular contraception can cut the chances of pregnancy by up to 89 percent. But it works best within the first 24 hours. There are two other emergency contraception pills: a two-pill generic version named Next Choice that also is sold behind the counter, and a prescription-only pill named ella.
If a woman already is pregnant, the morning-after pill has no effect. It prevents ovulation or fertilization of an egg. According to the medical definition, pregnancy doesn't begin until a fertilized egg implants itself into the wall of the uterus. Still, some critics say Plan B is the equivalent of an abortion pill because it may also be able to prevent a fertilized egg from attaching to the uterus.
Associated Press writer Ricardo Alonso-Zaldivar contributed to this report.


text:
GENEVA -- Could the Opel Cascada convertible unveiled at the show here today be headed to Buick showrooms in North America?
General Motors Vice Chairman Steve Girsky wouldn't say for sure, but offered this grist for the rumor mill:
"The Cascada is dynamite -- it looks great. That's what [GM CEO Dan] Akerson said also," Girsky told Automotive News after the soft top's unveiling. "He says the Buick dealers would really like that in their showroom."
GM is rumored to be mulling the addition of a coupe or convertible to Buick's U.S. lineup under the Verano nameplate -- or maybe even badged as a Riviera. The Cascada is an Opel Astra variant and shares a platform with the Verano compact sedan, launched in the United States in late 2011.
Unwrapped today by Girsky and new Opel CEO Karl-Thomas Neumann, the two-door, four-seat Cascada has a folding soft top roof that can be opened in 17 seconds at speeds up to 31 mph. It will be offered in Europe with a new 1.6-liter turbocharged gasoline engine and later a 2.0-liter diesel.
Pricing will start at 24,945 euros, or about $32,500.
Buick dealers are happy that GM has covered its bases by filling the lineup in key segments with entries such as the Verano and the Encore small crossover. Now many would like to add a little spice with a variant or halo car.
But Girsky tempered expectations for a U.S. berth for the Cascada, which is Spanish for waterfall.
"It was designed for Europe. Could there be some other markets for it? Yes," he said. "But it's a low-volume vehicle. It's a halo vehicle. It's expensive. It would have to be amalgamated for the U.S., which adds cost and complexity."
In Europe, Girsky believes the Cascada, which will be launched in April, will offer a viable competitor to the Audi A5 convertible "for more than 10 thousand euro cheaper."


text:
Bipartisan immigration reform framework announced
Sen. Charles E. Schumer (D-N.Y.) and Sen. Lindsey O. Graham (R-S.C.) have laid out the framework for a comprehensive, bipartisan immigration reform bill that would include tougher border enforcement, creation of biometric Social Security cards and a path to legalization for the nation's estimated 11 million undocumented immigrants.
The announcement of the plan, which brought immediate praise from President Obama, comes days before a pro-immigration march scheduled for the nation's capital on Sunday.
"It thoughtfully addresses the need to shore up our borders, and demands accountability from both workers who are here illegally and employers who game the system," Obama said in a prepared statement.
"A critical next step will be to translate their framework into a legislative proposal, and for Congress to act at the earliest possible opportunity."
The plan includes four basic pillars, including the creation of biometric Social Security cards to ensure illegal workers cannot get jobs in the future; fulfilling and strengthening border security and interior enforcement; creating a process for admitting temporary workers; and implementing a tough but fair path to legalization for those already here.
-- Anna Gorman
Photo: Border Patrol Agent Munga Wechsler, 26, looks for signs of illegal entry into the U.S. along the border fence near Antelope Wells, N.M. Credit: Don Bartletti / Los Angeles Times


text:
Virginia unifies IT security policies and infrastructure across five major areas.
The fight for comprehensive IT security seems never-ending . The enemy storms government territories every day with as many types of malware as there are pebbles on a beach -- too many to deal with easily.
Yesterday, the "man-in-the-middle" attack on the county network stole credentials to the treasury funds. This afternoon, the Trojan deleted files from the governor's desktop. And tomorrow, some exotic new code no one's heard of will pop up somewhere unexpected. In these battles, CIOs and their staffs must operate like a machine: Teamwork should exist between the standards and policy writers, data center operators, network administrators, programmers, the help desk staff and others -- seamless coordination.
That's probably what Virginia's technology executives were aiming for when they implemented the Interlocking Spheres of Collaborative Protection project, a complicated endeavor with one simple goal: to unify the policies, infrastructure and culture across state IT that are responsible for keeping data secure. These spheres represent the technology groups that need a common strategy in the unending security war.
John Green, the state's chief information security officer, noted that the end result is rather impressive. "It highlights the amazing things that can be achieved when you get a group of dedicated people together," he said. "I'm talking about all of the employees and information security officers -- when you get a group of dedicated people together focused on the same goal and mission."
The Virginia Information Technologies Agency (VITA) led the charge with cooperation from state leadership, the agencies it serves and Northrop Grumman, which manages Virginia's government IT infrastructure and services. They focused on five areas and separated them into spheres.
The top-down sphere represents the state's movers and shakers, including the governor, state CIO George Coulter, Green, the Legislature and agency leaders -- many of whom were instrumental in creating compliance standards and urging groups to meet them. The Information Technology Investment Board, which oversees Virginia's IT reform, can withhold project funds from agencies that don't keep pace.
In the peer-to-peer sphere, employees join groups to train, share information and network in the name of better security.
In the IT security program sphere, agencies are required to develop risk assessment and management programs for systems with sensitive information.
The infrastructure sphere covers most hardware and software changes, including the opening of a new data center, and the external sphere involves educating citizens about their personal IT security.
The five spheres represent a staggering amount of work for Virginia. And there's always more to do. "Eventually who knows? It may change," said Michael Watson, VITA's director of security incident management. "We may have to add additional input as time goes on. Technology's never a static thing. It evolved into this as we went along with the process."
And the struggle for strong security is everlasting.
"Like anything else, security is a journey. We don't expect to accomplish it all at once," Watson said. "We've grown and introduced the security culture into the different agencies and the rest of the government, and helped propagate the idea that it's a priority within the state. And as time has gone on, we've developed it."
Before the interlocking spheres project began in 2006, Virginia's IT landscape looked much different. The state had more than 90 disparate IT departments within individual agencies, and 60 percent of the state's equipment was between 8 and 10 years old. Even Virginia's primary data center was a security risk. The state's auditor of public accounts reported that 17 percent of 104 agencies lacked an information security program and 63 percent had an inadequately documented program.
Virginia's leadership decided change was due. "The Legislature, the governor and various governing
officials took a look across the commonwealth," Green said. "We noticed that the infrastructure was certainly aging. There were some issues with older systems as a result of technology being out of date." Green said he suspects some of the security controls in place to safeguard those legacy systems also were antiquated.
Fortunately lawmakers and the executive branch understood the importance of security and passed legislation that became the foundation for the information security program. Among those were policies that empowered the state CIO to develop standards and procedures for security across Virginia. In 2007, the Virginia General Assembly passed legislation requiring the CIO to direct the development of these policies and procedures and gave the Information Technology Investment Board the power to withhold funds if necessary.
Thanks to these efforts, agencies had a mandate to perform risk assessments and use the policies and tools to make that happen -- activities that fall into the IT security program sphere.
Those who spoke to Government Technology about the security project said it wasn't terribly problematic getting the work done, although John Willinger, information security officer for the state Department of Behavioral Health and Developmental Services, hinted at reluctance some agencies had with the changes.
"It's just a matter of getting those agencies that have been used to doing business in a certain way to step up and say, 'OK, we do need a change,'" he said. "I think that's probably the biggest issue -- just agencies being reluctant to take the step."
The state government invested $270 million upfront to transform the robust infrastructure sphere. These changes were spurred by coordination among Virginia's leadership, VITA and other state agencies, with substantial help from Northrop Grumman, their private-sector partner.
"Northrop Grumman was integral in the infrastructure sphere," said Matt Slaight, manager of computer systems security for the company. Northrop Grumman helped with the technology consolidation, the new data center and backup facilities for support.
The primary data center, the 192,000-square-foot Commonwealth Enterprise Solutions Center, opened in July 2007 in Chester, Va., at Tier 3 capability with power from two separate substations and an alternate water supply. According to the TIA-942 standards established by the Telecommunications Industry Association, a Tier 3 data center can have maximum annual downtime of 1.6 hours and must have multiple power and cooling distribution paths. The facility houses more than 600 Northrop Grumman and VITA employees.
Soon after the data center opened, an additional remote recovery site was completed in Lebanon, Va. This facility is 101,000 square-feet, with a help desk and backup capabilities staffed in part by employees from nearby counties and cities.
"By the December [2007] time frame, we were completed with southwest Lebanon's facility, and in the March-April [2008] time frame, we executed the first full disaster recovery test for the commonwealth, utilizing both of those facilities. So it was a very fast turnaround," said Mike Elkins, Northrop Grumman's director of infrastructure services.
Virginia now has standard security tools and policies for more than 23,000 PCs, and a single, statewide network and secure Internet gateway. The state can centrally scan e-mails and endpoints for spam and viruses, a much easier task than it was in a fragmented IT environment.
"There are certainly some benefits that we've seen in our ability to measure and monitor things happening on the network -- our ability to collectively respond more quickly when something does go wrong -- and that can either be a typical security-type incident or an incident with respect to availability of some type. It gives us more visibility," Green said.
But Green's analysis could be understated. Willinger said the process was transformative. "When I say transformation, I mean from the desktop to servers to e-mail to everything. It's a huge undertaking just for our agency alone," Willinger said. "When you
look at the entire commonwealth, it can be overwhelming."
Technology alone doesn't enhance security. People also do, which is where the peer-to-peer sphere comes in. This area is all about sharing the wealth -- knowledge, training and experiences -- through three groups: the Commonwealth Information Security Council, the Information Security Officers Advisory Group and the Information Security Orientation program. They're go-to zones for personnel looking to gain some security IQ.
The Information Security Officers Advisory Group is a monthly meet-up for top security officials. The group was originally meant to influence government IT projects and policy, but membership grew too large, with 100 to 150 people chiming in. Today state information security officers use the group to share information about emerging security trends, technologies and occurrences that could affect local IT.
The Information Security Council is much smaller, with roughly 12 representatives from universities and every branch of state government, including local governments, who meet monthly. This group zeroes in on policy and strategic directions that affect security.
Participants in the Information Security Orientation program learn security strategies that will make their agencies compliant with state standards.
The sphere also includes orientation and training for new information security officers. This training is open to other personnel who want to learn about compliance.
The changes brought forth by the interlocking spheres project aren't only evident in the back-end data center and networks. Changes also are apparent on the VITA Web site.
The information security incident reporting form allows state personnel to inform VITA about anything from site defacements and viruses to inappropriate use of technology and hacks. This reporting structure complies with a crucial requirement: Executive branch agencies must report these issues to the CIO within 24 hours of when they were discovered or should have been discovered.
"That form is one of the methods we use for our agencies to communicate to us that an incident has occurred," Green said, "and the mission of that form is to activate our incident response team."
VITA also helps government workers and citizens practice good computer hygiene by offering tips and resources via the online Information Security Awareness Toolkit, a site with information and software code for visitors to take if they wish. There's a video, posters, brochures, a calendar, crossword puzzles and more -- all designed to plant the seeds of secure computing in the minds of those willing to be educated. The site's advice and links connect employees and the public to outside security resources, which is defined as part of the external sphere of interlocking security.
The toolkit was developed before the interlocking spheres project began, so these educational offerings will be fine-tuned, according to Nakita Albritton, who serves in as VITA's manager of information security and continuity of operations coordinator.
"There's going to be a section [geared] toward executive information security awareness," she said. "It'll include security articles that basically give a little snapshot of some of their responsibilities and standards. It'll have presentations in there, and as we find other ways of distributing information to them, we'll add those things."
The toolkit's YouTube video, The Duhs of Security, is a quirky 13-minute production that covers basic security steps that everyone should know. Actor Garet Chester's humorous narration features a bevy of celebrity impressions -- no doubt intended to save viewers from boredom -- as they're educated about the benefits of deleting mysterious e-mails and changing passwords. The video may need some updating: Some of Chester's characterizations, like one based on Peter Falk's portrayal of Lt. Columbo from decades past, may not register with modern audiences.
Yet the toolkit will be mercurial regardless. "We're looking to develop it a lot more, and it will be dynamic," Albritton said.
And because developing robust security takes time and stamina, officials involved in the interlocking spheres project say it will need to evolve dynamically, too.
"Security is really a continuous life cycle," Slaight said. "It's never complete. The threat is always evolving. There are always new tools coming out -- new exploits, new vulnerabilities -- and it takes constantly staying up to date and on top of the threat, and adjusting the defensive posture of the infrastructure."
Willinger feels much better about Virginia's security now that the spheres are in place. "We're a lot better off now than we were three years ago, most definitely," he said. "When you feel a little more confident in your poker hand, you feel better off about what you have."


text:
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this is the very intersting poem.
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dont always depand on others suggetions...
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hw iz ur lyfstyle....
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World is not a nice place to live in.
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this a poem i made about heaven"s door
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