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Digital Silviculture and Progress in Forestry

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Introduction

Forests are a crucial part of our natural environment. They help provide us with shelter, they help regulate climate, and they provide us with many types of resources which we can use to create products that improve our lives. However, because forests are so important and also because human beings have been cutting down trees for centuries now (which is why deforestation is such a problem), it is important for foresters to know how best to manage the forests that we do have left. One way that foresters have been able to manage their forests better is through digital silviculture—the practice of digitally managing tree growth on an individual basis rather than by using traditional methods like spraying pesticides or fertilizers from above ground level only once in a while.

The history of digital silviculture.

Digital silviculture has come a long way since its conception. The first steps were taken in the mid-2000s when people began to use digital data in forestry management. In the early 2010s, big leaps were made by making the transition from storing and analyzing digital data to integrating it into operational tools such as GIS (geographic information systems). Since then, there have been new developments every year that helped us achieve our goal: automating repetitive tasks and improving decision-making by providing access to all relevant information at once.

The next step is to integrate data from the field into forestry operations. This means that we will be able to use both human and machine intelligence to make better decisions faster. We have already developed a system that integrates digital data with on-site measurements of trees, such as height and diameter at breast height (DBH). By doing this, we can identify which trees are suitable for retention and which ones should be removed from forest stands.

The next step is to use this data in operational tools such as GIS. We will be able to analyze the entire forest stand and determine which trees should be retained and which ones should be removed from forest stands.

The current status of forestry mechanization in South Africa.

South Africa is a major global player in forestry. The country has the largest forestry sector in Africa, and its forest industry is among the most advanced on the continent.

South Africa’s forest area covers roughly 30 million hectares (about 3% of the country), with plantations representing 40% of this total area. These plantations are situated mostly in western South Africa’s five provinces: KwaZulu-Natal, Limpopo, Mpumalanga, Northern Cape and North West Province.

The government’s Department of Forestry & Timber Industry (DoFTI) oversees all public forests managed by private companies or nonprofit entities for commercial purposes such as production of timber and non-timber products (NTFPs). Private owners manage about 22 million hectares under cultivation with trees that produce NTFPs like pine nuts from African blackwood trees or mopane worms from mopani trees – both integral components of traditional cuisine across Southern Africa – as well as fruits such as avocados or macadamia nuts.*

Applications in stand-level silviculture operations and planning.

Digital silviculture is a tool that can be used to improve efficiency, productivity and profitability of forest operations. It can also be used to improve planning and decision making.

Digital applications like remote sensing, geographic information systems (GIS), artificial intelligence (AI) and machine learning are transforming the forestry sector. With the development of advanced sensors and software applications, digital silviculture has become an essential part of modern forestry management practice. These technologies provide decision-makers with valuable insights into an array of ecosystem services such as carbon sequestration or timber production for use in planning activities at stand level (e.g., thinning) that increase resilience against climate change while optimizing profit margins from timber harvesting operations on private lands or government forestlands across North America

Progress in pattern-based silviculture.

Pattern-based silviculture is the process of making decisions about tree spacing, tree species mix and directionality in a stand based on observations of patterns.

The first step in pattern-based silviculture is defining the desired outcome, whether it be timber production or ecosystem protection. Next comes identifying existing patterns within a stand that are associated with desirable outcomes (for example: dense even-aged stands produce more wood than open uneven-aged stands). These patterns can then be predicted using mathematical models to determine how much area should be treated to achieve a certain result (for example: if you want a 50% reduction in density by thinning 10% of your forest how many acres should you treat?). Finally these models can be used when designing new stands from scratch or adding individual trees into existing ones as well as for predicting climate change impacts on forests over large areas such as those found in national parks or reserves

. Pattern-based silviculture can also be used to define the directionality or “shoulders” of a stand, which determines how a stand will grow in future. This is important because it allows foresters and land managers to direct growth in a desired direction as well as increase carbon storage while maintaining timber production

A framework for digital silviculture and learning from data.

The framework for digital silviculture we are proposing is a process of learning from data and knowledge. The first step in this process is collecting information about what and how people are doing things in the forest, which can be done by collecting information directly from people or indirectly from their actions. Then this information needs to be evaluated and analyzed for patterns that indicate opportunities for improvement. These patterns can then lead to new ideas about how to work better together, make better decisions, or otherwise improve the way we work together as a community around our forests. Finally, once these new ideas have been tested and proven effective we need to teach others what they mean so they too can learn how best use them when they return home after their time away working in other places such as cities or offices.

Where are we, what’s been done, what’s next?

There have been advances in the use of stand-level silviculture and forestry mechanization in South Africa. The status of digital silviculture is that it has not been as widely implemented as originally hoped because there are still many issues to be resolved before it becomes a standard practice for all operations.

  • A study was done to determine if the application of digital technology in planning and operational processes will reduce costs or increase productivity, or both?

  • The results showed that these systems have already been implemented successfully on many sites, but most were only partially automated with no integration between different software packages being used. This means that data had to be manually transferred from one system to another before making decisions could be made.

Conclusion

Digital silviculture will not replace human foresters, but it can significantly improve our ability to manage forests. The transition to digital silviculture is already underway, and we are already seeing the benefits of this approach in a number of ways. It will take time before all trees are managed with digital tools, but we believe that this process will eventually lead to better forest management strategies and improved resource utilisation by society at large.