KRISIS AIR, ILLEGAL LOGGING DAN PENEGAKAN HUKUM LINGKUNGAN DI INDONESIA

The protection and preservation of the environment is now perceived as being of crucial importance to the future of mankind, and public bodies both national and international are taking significant steps to- wards the establishment of legislation which will promote the protection of the environment. The number of critical watershed in Indonesia increases from time to time. In 1980’s there were only 22 areas, but in 1990’s it increased into 35 areas and in 2003 it already reached into 69 areas. Almost 70% of these critical areas locate in Java island. One of the weaknesses in the integrated watershed management in Indonesia is the decreasing quality of law enforcement, especially for the regulations pertaining to water resources, spatial planning, and conservation of natural resources together with the ecosystem. Key Words: Water Crisis, Illegal Logging, Environmental Law Enforcemen

Biologically informed ecological niche models for an example pelagic, highly mobile species

Background: Although pelagic seabirds are broadly recognised as indicators of the health of marine systems, numerous gaps exist in knowledge of their at-sea distributions at the species level. These gaps have profound negative impacts on the robustness of marine conservation policies. Correlative modelling techniques have provided some information, but few studies have explored model development for non-breeding pelagic seabirds. Here, I present a first phase in developing robust niche models for highly mobile species as a baseline for further development.Methodology: Using observational data from a 12-year time period, 217 unique model parameterisations across three correlative modelling algorithms (boosted regression trees, Maxent and minimum volume ellipsoids) were tested in a time-averaged approach for their ability to recreate the at-sea distribution of non-breeding Wandering Albatrosses (Diomedea exulans) to provide a baseline for further development.Principle Findings/Results: Overall, minimum volume ellipsoids outperformed both boosted regression trees and Maxent. However, whilst the latter two algorithms generally overfit the data, minimum volume ellipsoids tended to underfit the data. Conclusions: The results of this exercise suggest a necessary evolution in how correlative modelling for highly mobile species such as pelagic seabirds should be approached. These insights are crucial for understanding seabird–environment interactions at macroscales, which can facilitate the ability to address population declines and inform effective marine conservation policy in the wake of rapid global change

Spatial data and modelling for the prioritisation of conservation areas in the Alpine region of the Canton of Vaud

Increasing awareness of the impact of biodiversity loss and natural system instability on human life is changing the societal perception of the environment and the amount of effort put into solving environmental problems. In spatial planning, this translates into a quest for the sustainable use of the territory, allocating areas to their most suitable usage while managing conflicting interests and forces. Conservation areas are the cornerstone of any spatial strategy for nature conservation, but are strongly affected by socio-economic constraints that affect their implementation and maintenance. Prioritising interventions thus becomes fundamental to achieve efficient and effective results. Conservation planning has come a long way since its infancy, gradually putting aside traditional ad hoc reserve selection in favour of a more scientific and systematic approach. This development has been supported by advances in technology, especially in the area of geographic information systems, which allow for improved acquisition and faster treatment of spatial data. Modelling has also became a fundamental scientific activity for conservation planning, offering a better understanding of natural and biological phenomena and generating indispensable data used in emerging conservation planning support software. This dissertation looks at methods for the selection of high-quality areas for conservation, focusing on the maximum cover problem and analysing how traditional strategies translate into spatial differences on the resulting selection. The study area chosen to test our methodology is the Alpine region of the Canton of Vaud, in Switzerland, an area known for its biodiversity and cultural richness. After a thorough analysis of the area, focused on the biodiversity, socio-economic, political, and legal aspects that affect conservation planning, we decided to concentrate on prioritisation for vegetation conservation. Using Zonation v4 — a software package developed to aid conservation planning decision — and taking into account the previous analysis, we assess the spatial differences that result from different decisions, such as privileging rarity or richness, weighting species according to different criteria, or including socio-economic costs. We also examine the logic behind existing protected areas and investigate a possible expansion to benefit vegetation conservation. The outputs and subsequent analysis show the strong influence of both strategic preferences and socio-economic constraints on the priority ranking for potential protected areas. However, regardless of the strategy chosen, some areas are consistently ranked high and are therefore good candidates for further expansion. Furthermore, existing protected areas already show good coverage, and an increase of merely 2% in protected area would suffice to retain almost full representation of the vegetation species under consideration In the end, there are no perfect or universal solution for conservation planning prioritisation: different spatial translations can yield similar results for biodiversity. The process is an exercise in trade-offs in which software like Zonation can be of great assistance, allowing for an easier assessment of different scenarios and conservation strategies.A crescente consciencialização das repercussões da perda de biodiversidade e da disrupção dos sistemas naturais na vida humana tem modificado a percepção dos problemas ambientais e fomentado a mobilização de recursos para os resolver. Em ordenamento do território, esta preocupação traduz-se na procura de uma ocupação sustentável do espaço, tentando gerir forças e interesses muitas vezes opostos e dificilmente conciliáveis. As áreas protegidas são os alicerces de qualquer estratégia para a conservação ao nível territorial, mas a sua implementação e manutenção é fortemente influenciada por limitações contextuais de origem socioeconómica. Priorizar intervenções e investimentos em conservação de forma a torná-la mais eficaz e eficiente torna-se, assim, essencial. A planificação para a conservação ambiental e o método de selecção de reservas por esta empregado têm sido alvo de desenvolvimentos nas últimas décadas, passando de uma abordagem pouco científica a um processo sistemático. Esta mudança de paradigma só foi possível devido ao desenvolvimento paralelo de tecnologias de informação geográfica que vieram possibilitar uma melhor e mais rápida aquisição de dados espaciais e seu tratamento. A modelação tornou-se uma ferramenta científica indispensável no processo de planeamento, permitindo a recolha de informação sobre fenómenos naturais e de dados indispensáveis para a utilização de software de ajuda à decisão. Esta dissertação pretende estudar os métodos empregues na identificação e selecção de áreas a proteger, focando-se no problema da máxima representatividade e na análise de estratégias comuns de priorização na tradução espacial dessa selecção. A área de estudo escolhida para esta análise foi a zona alpina do Cantão de Vaud, na Suíça, uma área conhecida pela sua biodiversidade e riqueza cultural. Depois de uma análise detalhada às características de biodiversidade, socioeconómicas e político-legais locais, decidimos concentrar o nosso estudo na preservação da vegetação. Recorrendo ao programa de apoio à decisão em planeamento de conservação Zonation v4, analisámos as diferenças espaciais resultantes de diferentes opções de conservação e dados de entrada, tais como a preferência pela salvaguarda da raridade ou da riqueza biológica, a atribuição de diferentes pesos às espécies com base em critérios vários ou a inclusão de informação socioeconómica. Tentámos ainda apurar a lógica subjacente à criação das reservas existentes e identificar possibilidades de expansão que beneficiariam a conservação. Concluímos que a tendência para proteger a raridade ou a riqueza tem tradução espacial relevante, sendo, no entanto, as limitações socioeconómicas o maior factor de constrangimento para a salvaguarda de biodiversidade. Independentemente da estratégia usada, certas áreas são consistentemente seleccionadas, mostrando-se boas candidatas para expansão futura. Os resultados revelam ainda que as reservas actuais têm boa cobertura e um aumento de 2% da área seria suficiente para atingir uma representação quase total das espécies consideradas. É possível encontrar soluções interessantes sem comprometer de forma marcante a salvaguarda da biodiversidade. Em planeamento de conservação, não existem soluções perfeitas e universais, tratando-se antes de um constante exercício de concessões. Programas de ajuda à decisão em planeamento de conservação, como o Zonation v4, demonstram grande potencial, permitindo uma melhor compreensão das alternativas e a sua rápida visualização espacial. PALAVRAS-CHAVE: priorização, planeamento de conservação, SIG, Zonation, Vau

Arbeitspapier "Operationalisierung funktionierende Ökologische Infrastruktur"

Die Ökologische Infrastruktur (ÖI) ist für die Erhaltung und Förderung der Biodiversität unerlässlich und stellt lebenswichtige Leistungen für den Menschen bereit. ÖI basieren auf natürlichen und halbnatürlichen Lebensräumen. Die Entwicklung und der Schutz solcher ÖI wurden als zentrale Schritte für den Erfolg der Strategie Biodiversität Schweiz (SBS) identifiziert. Konzepte wie «Grüne Infrastruktur» oder «Naturbasierte Lösungen (Nature-based Solutions)», die sich auf ÖI beziehen, haben sich in den letzten Jahrzehnten zunehmend etabliert. Ihre teils unterschiedlichen Sichtweisen erschweren jedoch eine klare Anwendung in der Praxis. Dieses Arbeitspapier ist eine literaturbasierte Auslegeordnung und stellt verschiedene Zugänge zur Operationalisierung einer «funktionierenden» ÖI vor. Für das Projekt ValPar.CH ist das Arbeitspapier eine wichtige Grundlage für ein gemeinsames Begriffsverständnis im Projektteam. Das Forschungsteam wird das Funktionieren einer ÖI sowohl aufgrund ökologischer Aspekte (Module A), wie auch basierend auf den gesellschaftlichen und wirtschaftlichen Nutzen der ÖI (Module B) und deren langfristige Sicherung durch verschiedene «policy»-Mechanismen (Module D) beurteilen. Darauf aufbauen wird das Team Empfehlungen für die Sicherstellung einer funktionierenden ÖI erarbeiten. Ecological infrastructure (EI) is essential for the conservation and promotion of biodiversity and provides vital services for humans. EI is based on natural and semi-natural habitats. The development and protection of EI have been identified as key steps for the success of the Swiss Biodiversity Strategy (SBS). Concepts such as "Green Infrastructure" or "Nature-based Solutions", which refer to EI, have become increasingly established in recent decades. However, their partly different perspectives make application in practice difficult. This working paper is a literature-based overview and presents different approaches to the operationalization of a "functioning" EI. For the ValPar.CH project, this working paper is an important basis for arriving at a common understanding of the term within the project team. The research team will assess the functioning of an EI based on ecological aspects (Module A), as well as based on the societal and economic benefits of the EI (Module B) and its long-term safeguarding through different "policy" mechanisms (Module D). Based on this, the team will develop recommendations for ensuring a functioning EI

Analysis of the Tapanuli orangutan (Pongo tapanuliensis) population in other land use areas, Arse sub-district, South Tapanuli Regency

Tapanuli Orangutan (Pongo tapanuliensis) is a globally critical species (critically endangered) due to the decreasing area of natural habitat. Orangutans can reach out of their natural habitat outside the forest and into community fields for feeding. Orangutans make the other land use not only a place to stopover but also a home range and living area marked by nests. The study aims to obtain information on the characteristics of nests and the estimated population of the Tapanuli orangutan (TO) in the other land-use area. This research method uses line transects placed by systematic sampling with a distance between lines of 3 km and population data analysis using calculations from the van Schaik formula. From the results of the 11 research lines, 14 nests were obtained consisting of 3 class B nests, 5 class C nests, 3 class D nests, and 3 class E nests. The characteristics of the most dominant nests were class C with the most preferred positions II and III and nest finding highest in Quercus maingayi tree. The research found that the density of the TO was eight individuals/1000 ha

ANALYSIS OF SAND DUNES DAMAGES USING REMOTE SENSING METHOD IN PARANGTRITIS KRETEK BANTUL

ABSTRAKIndonesia passed the equator make Indonesia get some kind of wind. The wind helps the formation ofsand dunes such as those on parangtritis. Human population is growing and is not supported by theincrease of the land, then the existence of sand dunes began to interfere with land transfer function for thefulfillment of human needs. The purpose of this research is to determine the extent of damage andreduction of the sand dune area in parangtritis and the cause of its damage. The method used in thisresearch is the extraction of information from spatial data in each year of data recording then analyzed toobtain data or information regarding changes in sand dunes area. The interpretation results show that thearea of sand dunes in 2003 was 277,083 Ha, while the area of sand dunes with visual interpretation of theimage of 2015 shows that the current sand dune area is 169.378 Ha. The results of both areas of the sanddunes experienced a reduction of 107,705 hectares or it can be said that the sand dunes area over the yearspan experienced a reduction of 47.4%.Key Word: Sand dunes; Spatial Data; Land Transfer Function

Economic mapping and assessment of Cymodocea nodosa meadows as nursery grounds for commercially important fish species. A case study in the Canary Islands

Cymodocea nodosa seagrass meadows provide several socio-economically ecosystem services, including nurseries for numerous species of commercial interest. These seagrasses are experiencing a worldwide decline, with global loss rates approaching 5% per year, mainly related to coastal human activities. Cymodocea nodosa, the predominant seagrass in the Canary Archipelago (Spain), is also exposed to these threats, which could lead to habitat loss or even local disappearance. In this case study, we estimated the potential economic value of Cymodocea nodosa seagrass meadows for local fisheries at an archipelago scale. Habitat suitability maps were constructed using MAXENT 3.4.1, a software for modelling species distributions by applying a maximum entropy machine-learning method, from a set of environmental variables and presence and background records extracted from historical cartographies. This model allows characterising and assessing the C. nodosa habitat suitability, overcoming the implicit complexity derived from seasonal changes in this species highly dynamic meadows and using it as a first step for the mapping and assessment of ecosystem services. In a second step, value transfer methodologies were used, along with published economic valuations of commercially-interesting fish species related to C. nodosa meadows. We estimate that the potential monetary value of these species can add up to more than 3 million euros per year for the entire Archipelago. The simplicity of the proposed methodology facilitates its repeatability in other similar regions, using freely available data and hence, being suitable for data-scarce scenarios.En prens

Performance Evaluation of Cetacean Species Distribution Models Developed Using Generalized Additive Models and Boosted Regression Trees

Species distribution models (SDMs) are important management tools for highly mobile marine species because they provide spatially and temporally explicit information on animal distribution. Two prevalent modeling frameworks used to develop SDMs for marine species are generalized additive models (GAMs) and boosted regression trees (BRTs), but comparative studies have rarely been conducted; most rely on presence-only data; and few have explored how features such as species distribution characteristics affect model performance. Since the majority of marine species BRTs have been used to predict habitat suitability, we first compared BRTs to GAMs that used presence/absence as the response variable. We then compared results from these habitat suitability models to GAMs that predict species density (animals per km2) because density models built with a subset of the data used here have previously received extensive validation. We compared both the explanatory power (i.e., model goodness of fit) and predictive power (i.e., performance on a novel dataset) of the GAMs and BRTs for a taxonomically diverse suite of cetacean species using a robust set of systematic survey data (1991–2014) within the California Current Ecosystem. Both BRTs and GAMs were successful at describing overall distribution patterns throughout the study area for the majority of species considered, but when predicting on novel data, the density GAMs exhibited substantially greater predictive power than both the presence/absence GAMs and BRTs, likely due to both the different response variables and fitting algorithms. Our results provide an improved understanding of some of the strengths and limitations of models developed using these two methods. These results can be used by modelers developing SDMs and resource managers tasked with the spatial management of marine species to determine the best modeling technique for their question of interest