increasingly being recognized that formal designations of institutional boundaries can hide a lot of variation in actual rules in use (Cox et al. 2010).
Thus, a mere documentation of formal institutions and management boundaries is not sufficient (Agrawal 2014; Cox et al. 2010). Within what is formally designated as a particular institutional management category, such as a Tiger Reserve (TR) or community forest, there is often substantial variation in the actual practices of management, rules in use, and institutional structures that impact the outcomes of forest management (Gibson et al. 2000; Hayes 2006). For instance, factors such as the involvement of local forest users in crafting rules of management, group size and the degree of local monitoring are known to impactforest condition and change (Chhatre and Agrawal 2008; Nagendra 2007; Shyamsundar and Ghate 2011). Examinations of multiple institutions at a landscape-scale are limited however. Some studies in Nepal and Indonesia indicate that landscape-scale approaches that incorporate different institutional types including strict Protected Areas (PAs) and community forests, can strengthen the resilience of forest corridors and promote biodiversity (Linkie et al. 2006; Wikramanayake et al. 2011). Yet there is limited research on institutions within a landscape context in other parts of the world, and a particular gap from India (Ostrom and Nagendra 2006). Detailed examinations of landcoverchange across different tenure regimes and rule systems can help to provide policy inputs for appropriately managing LULCC, landscapefragmentation and ecosystem services at a landscape-scale (Ostrom and Nagendra 2006; Persha et al. 2011). Figure 1.1 provides a conceptual diagram of the role of institutions and other human drivers of change on LULCC and landscapefragmentation.
Landsat Thematic Mapper (TM), Landsat Enhanced Thematic Mapper Plus (ETM+) and Landsat 8 Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) remotely sensed data were used to map landcoverchange in Nyungwe-Kibira forest and its landscape. Thus, Landsat satellite images for 1986, 1990, 1995, 2000, 2010 and 2015 were acquired from the U.S Geological Survey (USGS) to evaluate the change in forestcover from 1986 to 2015 in 5 years time-steps. Good quality scenes from Landsat 172 path and 61 row were primarily targeted during this period. However, due to the obscure of clouds over the forests cover and high mountains on the surface of the study area, which may induce changes in surface features’ spectral characteristics, some im- ages were deemed unusable. Thus, images with the lowest cloud cover percentage were screened. Images either full of haze and clouds or affected by the Scan Line Corrector (SLC-off) defections were disqualified; hence, 2005 images and scenes prior to 1986 were precluded from the usable dataset in this particular study. Furthermore, in order to improve the discrimination during classification, only dry season images were se- lected since rainy season images in tropical areas are more complex to distinguish ve- getation cover classes because of higher greenness .
021 while another 20 percent has been degraded. Most of the rest
has been fragmented, leaving only about 15 percent intact. In recent decades, human development pressures have results in conversions of vast tracts of tropical rain forests to agriculture and other land uses. As a result, remaining forests had become a victim of fragmentation and divided into smaller habitats . Any land use change can potentially result in fragmentation and much of the forested landscape was fragmented by land clearing for timber and agriculture, some of the most serious fragmentation has been caused by urban sprawl . Haddad et al. (2015),  revealed that nearly 20% of the world’s remaining forest is within 100 m of an edge in close proximity to agricultural, urban, or other modifi ed environments where impacts on forest ecosystems are most severe and more than 70% of the world’s forests are within 1 km of a forest edge. Where fragmentation continues, Zhu, Xu, Wang, & Li (2004),  observed microclimatic differences which induces buffer effect (edge effect), change of species composition, change in species richness and species (with small population) extinction and parasitic disturbance. Besides Costero (2009), Laurance (2004) [12,13] and Laurance et al. (2011)  discussed about abiotic alteration from forestfragmentation which affects habitats of both fl oral and faunal community. Extinction cascades are likely to occur in landscapes with low native vegetation cover, low landscape connectivity, degraded native vegetation and intensive land use in modifi ed areas, especially if keystone species or entire functional groups of species are lost . Broad-scale destruction and fragmentation of native vegetation is a highly visible result of human induced land use change throughout the world . Multiple regression analysis of a case study showed that human induced land use change is an important determinant of forestfragmentation . However, forests may be fragmented by a number of activities or events, such as road construction, logging, conversion to agriculture, or wildfi re, but ultimately, the fragmenting cause is either anthropogenic or natural in origin .
Bedrock composition in the Mudumalai plot was not uniform, with one of the clearer patterns being significantly greater amphibolite presence at the top of plot topography and the wide- spread occurrence of hornblende-biotite gneisses at lower elevations ( Fig 1a and 1b ; S2 Appen- dix ). This configuration concurs with the one found in the neighboring Mule Hole watershed [ 57 ], located ~17-km NW of the Mudumalai plot. Both sites are located in the Moyar-Bhavani shear zone and exhibit considerable lithological heterogeneity at the local ( <1 km 2 ) scale, share the 1200-1300mm isohyet, and are covered by intact tropicaldry deciduous forest. This allows for direct comparisons and for inferences to be carried over across sites. In Mule Hole, fresh amphibolite is found just below the soil layer, indicating that the saprolite hardly develops on this amphibolite lithology in the present climatic regime, in contrast to gneiss where biotite hydrolysis and greater prevalence of discontinuities [ 58 ] allows faster weathering and the development of a thick saprolite layer [ 39 , 57 ]. On the basis of observations in the Mudumalai plot and geological studies in Mule Hole, we suggest that topography at both sites has been shaped by differential weathering of lithologies, as is also widely observed at the landscape scale in the region [ 59 , 60 ]. According to Gunnell [ 38 ], denudation patterns in the Deccan Pla- teau regolith during the Cenozoic were shaped by the weatherability of rocks, allowing weath- ering-resistant lithologies such as massive charnockites and granites to emerge in the
The Caatinga is a mosaic of scrub vegetation and patches of dryforest , which has been referred to in the literature either as a seasonally drytropicalforest [2, 21, 22, 23] or as a shrubland ecosystem . Despite such disagreement , probably caused by the occurrence of low-stature vegetation stands across the Caatinga region, it has been demonstrated that the Caatinga woody flora (shrubs and trees) consists of dryforest species rather than savanna ones [2, 22, 33, 34]. Because of this marked biogeographic feature, Caatinga is considered here as a SDTF biota following previous authors’ wide concept or perspective of SDTFs [see Portillo-Quintero and Sánchez-Azofeifa for a review+. Entirely disposed within Brazil’s borders (Fig. 1), Caatinga covers over 800,000 km 2 and represents around 10% of the Brazilian landmass. The predominant Caatinga landscape (Fig. 2) refers to flattened depressions (300-500 m a.s.l), which are submitted to a rainfall regime ranging from 240 up to 900 mm/year and a 7-11-mo dry season [33, 34]. Collectively, Caatinga, Pantanal, Cerrado and Campos Sulinos represent a wide range of seasonal ecosystems (from to SDTFs to grasslands), which cover nearly 50% of Brazilian territory (Table 1). Humid or less seasonal ecosystems are represented by two immense blocks of tropicalforest (Amazonia and the Atlantic Forest), which cover the other half of the Brazilian territory . In addition to Caatinga, patches of deciduous forest across the Atlantic Forest region have been also assigned as SDTFs in the Brazilian territory . Caatinga biodiversity yields over 1,000 vascular plant species in addition to 187 bees, 240 fish species, 167 reptiles and amphibians, 516 birds, and 148 mammal species, with endemism levels varying from 9% in birds to 57% in fishes . Current biodiversity scores are several times higher than previous assessments, but equal to or higher than those recorded in other semi-arid biotas around the globe .
Despite TCH peaking in alluvial valleys, we also found that low-lying forests tended to have higher gap fractions at 20 m aboveground compared to ones at mid elevations and above, where canopy structure became more uniform and compact (Fig. 5b). This pattern further highlights how subtle differ- ences in elevation can contribute to driving strong changes in the composition and dynamics of communities within the landscape (Werner & Homeier 2015), which ultimately under- pin the variation in canopy structure seen in the ALS data (Fig. 1b). Low-lying, alluvial valleys in Bornean forests are home to a wide variety of tree species (Fig. 1c), including fast-growing dipterocarps that invest heavily in height growth to escape shaded understories and can become exceptionally tall (exceeding 90 m in rare cases; Ghazoul 2016). However, in addition to being highly productive (Banin et al. 2014), these forests also exhibit high turnover rates (Stephenson et al. 2005; Russo et al. 2008). In particular, large, emergent dipterocarps – which are susceptible to strong winds and extreme flooding events, due to their large crowns, shal- low root systems and low WD (Proctor et al. 2001; King et al. 2006; Margrove et al. 2015) – can create large canopy gaps when they die. The net result of these demographic pro- cesses is that when nutrients are not limiting to growth, for- ests tend to develop taller, but also more structurally complex canopies.
Hyperspectral imagers are instruments that measure the complete spectrum of reflected solar energy for each pixel of spatial coverage. These technologies have demonstrated the power to provide ecological information that is unavailable with other technologies (Ustin et al., 2004). Previous studies have shown positive correlations between leaf reflectance and leaf constitue nts like pigments, water, and nitrogen for tropical and temperate forest ecosystems (Asner & Vitousek, 2005; Asner & Martin, 2008; Blackburn, 1999; Castro-Esau et al., 2006; Kokaly et al., 2009). Nonetheless, these hyperspectral data do not reflect the leaf constituent concentrations obtained from the species of the Guánica DryForest. Although we did not find any correlation between reflectance data and leaf pigment concentrations, we find a reflectance region that had high variability among species related to leaf water and nitrogen concentrations.
The main objectives of this study were to detecting the land use and landcoverchange (LULC), us- ing remote sensing techniques, then identify the reasons for rangeland and tree cover degradation in El Rawashda Forest, Gadarif State, Sudan. The study has conducted field experiment developed on an area of 20 feddans that was affected by deterioration in the forest and to assess the best method for rehabilitation of the vegetation cover in the area of study. The experimental area was divided into 5 blocks; each block consisted of 4 treatments: grass seeds and Talih (Acacia seyal var. seyal); sowing seeds just before autumn, sowing seeds after disc ploughing, sowing seeds using water harvesting technique and control (no seeding). In the present study an attempt has been made to analyze and monitor the LULC changes using multi-temporal Landsat data deterioration in the forest and to assess the best method for restoration of the vegetation. In the present study, an attempt has been made to analyze and monitor the LULC changes using multi-temporal Landsat data for years 1984, 1994 and 2013. LULC grades in the classification scheme are: Trees, Mecha- nized Rain-fed Agriculture (MRA), Grasses and Bare land. Individual classifications based on maxi- mum likelihood of algorithm were used and the results showed a significant that extensive change of LULC patterns has occurred in all decades in the study area. The results also show Trees class was decreased, while MRA, Grasses and Bare land were increased. The seeding of the forage and Talih seeds after disc plowing gave the best results compared to the other treatments, followed by forage and Talih seed sowing under the water harvesting technique and broadcasting of forage and Talih seeds and finally the control.
Findings presented in Chapter 2 indicate that dam-induced fragmentation leads to an extinction debt for reservoir islands, which is supported by other studies reporting extinction debts in fragmented systems (Kuussaari et al. 2009; Metzger et al. 2009). In a recent study of vertebrate extinctions across the Balbina archipelago, it was found that a relatively large island size of 475 ha was needed to sustain >80 % of vertebrate species, but that only 0.7 % of the >3500 islands created by the Balbina dam met this size criterion (Benchimol & Peres 2015b). The fact that the vast majority of islands could not support a species-rich vertebrate community characteristic of mainland environments lends further support for the globally applicable findings presented in Chapter 2: reservoir islands cannot support a full complement of species post-isolation. Moreover, we show that all islands are effectively too isolated for species populations to be buffered by the ‘rescue effect’ and metapopulation dynamics (Hanski & Ovaskainen 2000). In our analysis, island isolation distance did not explain patterns in island species richness. We therefore demonstrate that principles of the Island Biogeography Theory (IBT; MacArthur and Wilson, 1967) do not
cern if planners need quantiﬁcation of the expected impact of surface-cover management interventions. While the research presented in this paper focussed on a few general land-coverchange types and patterns, any speciﬁc spatial pattern of land-coverchange can be modeled and assessed as long as the land-cover data and the relationship between the surface roughness and land-cover type are provided in the basin of concern. However, further work on relationships between overland ﬂow velocities and landcover would be needed for broader application of this modeling method. The roughness for each type of vegetation cover controls the overland ﬂow velocity parameter in the model which is the critical factor representing the impact of each vegetation cover type on overland ﬂow movement in the distributed TOPMODEL. The roughness of each land-cover type in this paper is deﬁned as relative roughness to an Eriophorum rough- ness in the model. This relationship between the roughness parameters of Sphagnum, Eriophorum, and bare peat is based on the research of Holden et al. , in which an empirical overland ﬂow velocity forecast- ing model was built through ﬁeld data from peatlands. However, data for a greater variety of land-cover types would be welcome including those on mineral soil systems. Laboratory experiments and in situ sur- veys with new approaches may be necessary as such ﬁeld data collection can be laborious.
Nowadays, more than 40% of the population lives in Chinese cities. The rapid urbanization process brought about many eco- environmental problems, such as the drastic change of land use and development of urban heat island. Three Landsat TM and ETM+ images data of Beijing acquired on April 9, 1995 and April 30, 2000 were selected to this research. The land surface temperature (LST) and land use and landcover (LULC) classes were retrieved and extracted. The temperature-vegetation index (TVX) space was constructed to investigate the influence of land changes over LST. The result showed that the land use change was an important driver for LST increase, the temporal trajectory of pixels in the TVX space migrated from the dense-vegetation- low temperature condition to the sparse vegetation-high temperature condition.
Abstract: Assessments of forestcover, forest carbon stocks and carbon emissions from deforestation and degradation are increasingly important components of sustainable resource management, for combating biodiversity loss and in climate mitigation policies. Satellite remote sensing provides the only means for mapping global forestcover regularly. However, forest classification with optical data is limited by its insensitivity to three-dimensional canopy structure and cloud cover obscuring many forest regions. Synthetic Aperture Radar (SAR) sensors are increasingly being used to mitigate these problems, mainly in the L-, C- and X-band domains of the electromagnetic spectrum. S-band has not been systematically studied for this purpose. In anticipation of the British built NovaSAR-S satellite mission, this study evaluates the benefits of polarimetric S-band SAR for forest characterisation. The Michigan Microwave Canopy Scattering (MIMICS-I) radiative transfer model is utilised to understand the scattering mechanisms in forest canopies at S-band. The MIMICS-I model reveals strong S-band backscatter sensitivity to the forest canopy in comparison to soil characteristics across all polarisations and incidence angles. Airborne S-band SAR imagery over the temperate mixed forest of Savernake Forest in southern England is analysed for its information content. Based on the modelling results, S-band HH- and VV-polarisation radar backscatter and the Radar Forest Degradation Index (RFDI) are used in a forest/non-forest Maximum Likelihood classification at a spatial resolution of 6 m (70% overall accuracy, κ = 0.41) and 20 m (63% overall accuracy, κ = 0.27). The conclusion is that S-band SAR such as from NovaSAR-S is likely to be suitable for monitoring forestcover and its changes.
Interestingly, within the continuous forest, the shape of the secondary forest proﬁle is more sim- ilar to the intact forest than the logged forest (Fig. 3a–d). Below 10 m height, there is very little difference between the secondary and intact pro- ﬁles while there is considerably more light trans- mission in the logged plot, with signiﬁcantly higher T at 10 m height in logged plot 37.6% 23.1% (mean SD) than in the secondary, intact- K, and intact-M plots with 13.3 9.9, 14.8 12.3, and 13.3 9.1, respectively (ANOVA, F = 7.1, df = 3, P < 0.001 with logged signiﬁcantly to other plots in Tukey’ s post hoc test). This is sur- prising considering that regrowth from clear fell- ing could be considered a greater disturbance than selective logging and that the secondary plot contains ~68% of the intact plot biomass (Marchiori et al. 2016). This shows that despite recovery of some characteristics (e.g., biomass), logged forest can still show structural differences long after the logging event. Further, despite the difference in biomass between the secondary and intact plots, the conditions for the understory may be quite similar. While logged forests will have a composition more similar to intact forest than secondary forest (Gibson et al. 2011), the mid-canopy light conditions can be brighter and may be less conducive to the growth of shade- tolerant species than the darker mid-canopy of a recovering secondary forest. Further understand- ing is needed on patterns of structural forest recovery after disturbance and the consequences for the vertical light environment and tree growth.
4.0 DISCUSSIONS AND CONCLUSION A comparison of pre-European and modern day land surface parameters showed a strong decrease in vegetation fraction, LAI and surface roughness over eastern Australia and southwest Australia, and an increase in albedo for all regions were landcoverchange had occurred. The direct changes in surface roughness due to the reduction of woody vegetation has increased strength of surface winds by reducing aerodynamic drag (Lawrence 2004), while changes in stomatal resistance has modified surface evaporation, latent and sensible heat fluxes and planetary boundary layer properties (Sellers 1992). The impact of decreased surface roughness is an increase in surface wind strengths and sensible heat fluxes. The increase in near- surface wind amplified the shift from moist northeast tropical air to cooler and drier southeast flow from the Tasman Sea, resulting in the decreased rainfall. Results showed that the regional perturbation of vegetation can possibly magnify the impact of natural mode of individual El Niños, which together with rainfall deficiency, could have a strong impact on climate conditions (e.g. droughts) in eastern Australia. Hence, the replacement of native vegetation with seasonal cropping and improved pastures is likely to be contributing to more severe droughts and increased demand for water.
Human beings have been altering the face of the earth for the last few centuries but with the introduction of machines, the landcover of the earth has changed drastically in the last three centuries. The debate about the relationship between human population dynamics and the availability of natural resources dates back to more than 200 years when Malthus (1798) put forward his argument that population growth would eventually outstrip the production capacity of the land. It was only in the second half of the 20th century when the probability of the Malthusian projection seemed to be a reality, that sincere efforts to study the human population–environment relation were undertaken. The scientific study and analysis of land use and landcoverchange involves a quantitative estimation of land use and landcover at a particular location and time. In this regard, remote sensing plays a major role in giving a synoptic view of the spatial extent of land use and landcover at a particular point of time. The Human use of land resources gives rise to land use which varies with the purpose it serves, whether it be food production, provision of shelter, recreation, extraction and processing of materials, and the biophysical characteristics of the land itself. In the developing countries, due to population pressure and in a bid to extract the maximum output from the available sources, the impact of degradation can be worse than in other countries and adversely affect the landcover of the region.
B elgium Denmark Netherlands Luxembo urg Germany Czech Republic Hugary Slo venia A ustria Cro atia P o rtugal Switzerland Slo vakia France B ulgaria Ireland P o land United Kingdo m Yugo slavia Spain Italy B o snia and Herzego wina M acedo nia Ro mania Greece A lbania Latvia No rway Lithuania Sweden Esto nia Finland
– and provides water, ecosystem services, and the basis for liveli- hoods to a population of around 210.53 million people in the region. The basins of these rivers provide water to 1.3 billion people, a ﬁfth of the world’s population (Schild, 2008). Endowed with a rich variety of gene pools and species, and ecosystems of global impor- tance (Chettri, Shakya, Thapa, & Sharma, 2008), the region hosts parts of four Global Biodiversity Hotspots: Himalaya, Indo-Burma, Mountains of South-West China, and Mountains of Central Asia (Mittermeier et al., 2004). Approximately 39% of the HKH is com- prised of grassland, 20% forest, 15% shrub land, and 5% agricultural land. The remaining 21% are barren land, rocky outcrops, built-up areas, snow cover, and water bodies (Chettri et al., 2008). With 20% coverage, forest is one of the most important ecosystems in terms of habitat for ﬂagship species (Chettri, Sharma, & Zomer, 2012; Kandel et al., 2015) and as a source of provisioning, regulatory, cultural and supporting services (Badola et al., 2010; Kubiszewski, Costanza, Dorji, Thoennes, & Tshering, 2013; Pant, Rasul, Chettri, Rai, & Sharma, 2012). However, the region has witnessed signiﬁ- cant deforestation in the past (Ives & Messerli, 1989) which is still ongoing in many areas (Pandit, Sodhi, Koh, Bhaskar, & Brook, 2007). Although the HKH has witnessed signiﬁcant progress in conser- vation, with 39% of land in protected areas (Chettri et al., 2008), the region is still facing challenges with the effectiveness of pro- tected area management (Oli, Chaudhary, & Sharma, 2013), and protected areas are often isolated as conservation islands (Chettri et al., 2008). The conservation agenda is facing additional chal- lenges with climate change (Singh, Singh, & Skutsch, 2010) and high rates of absolute poverty in some parts (Gerlitz, Hunzai, & Hoermann, 2012). Moreover, the region is poorly researched and the information available on biodiversity, landcoverchange, and climate change is far less than required. The fourth and ﬁfth reports of the Intergovernmental Panel on Climate Change (IPCC) explicitly pointed to the HKH as a data deﬁcit area (IPCC, 2007, 2014; Solomon
Additional file 2. Metadata and spreadsheet of the data used to map the historical (1870s to 1880s) vegetation (prairie, savanna, forest) in the Palouse prairie –forest ecotone. We interpreted the field notes from General Land Office (GLO) surveys of the external lines of each township, and the internal lines subdividing each township into 36 sections for Washington, USA ( www.blm.gov/or/landrecords/survey/yGrid_ORWA. php?state=WA&ln=10000000 , accessed April to November 2018), and Idaho, USA ( glorecords.blm.gov/default.aspx , accessed April to November 2018). We used the species and number of bearing trees (0 to 4) at each of the section and quarter section corners to calculate the percent pine. The surveys were mostly completed between 1869 and 1916 (98% of the 2793 GLO section corners in the ecotone with accessible records were surveyed between 1869 and 1883), and we excluded the Coeur d ’Alene Indian Reservation lands as they were not surveyed until many years later. GLO surveyors recorded species and stem diameter at breast height (1.3 m) plus direction and distance from the section corner for up to four bearing trees within 60.2 m of each section corner with one in each quadrant (up to two trees for each quarter section corner, one in each half). Where there were no trees in a quadrant (section corners) or half (quarter section corners), they dug a pit instead from which they re- corded direction and distance to the corner. Methods for GLO surveys are described by Bourdo ( 1956 ).