Rangelands Vegetation Mapping at Species Composition Level Using the \u3cb\u3eSPiCla\u3c/b\u3e Method: \u3cb\u3eS\u3c/b\u3eDM Based \u3cb\u3ePi\u3c/b\u3exel \u3cb\u3eCla\u3c/b\u3essification and Fuzzy Accuracy. A New Approach of Map Making

Vegetation maps have been made since centuries. The vegetation cover was represented as homogeneous mapping units (polygons), representing different vegetation types, where each type consists a combination of different plant species (floristic composition). More recent, with the use of satellite imagery, the polygons have been replaced by pixels with similar content as the polygon maps. In both approaches, field-observations were linked to the mapping units (polygons or pixels) often resulting in a complex of different vegetation types per mapping unit. In our new approach field data (sample points) on presence and abundance of individual grass species are spatially extrapolated based on a set of environmental layers, using the species distribution modelling approach (SDM). When combined, each pixel will contain its own set of information about the vegetation structure and its floristic composition. This new methodology (SPiCla) results in a very accurate and detailed vegetation map at pixel level, allowing extraction of very detailed, accurate and easy to update spatial information on e.g., forage production and quality (palatability) for rangelands management. As no exact boundaries exist, but only gradients, we introduced fuzzy accuracy. The resolution mainly depends on the resolution of (or one of) the environmental layers used, scale of interest and workability. The methodology is generic and applicable to any other region in the world

MARIS: Scalable Online Scenario Development Tool for Rangeland Conservancy Managers Using High Spatial-Temporal Resolution Carrying Capacity Maps and Livestock Market Data

Although the management of livestock numbers within the bounds of carrying capacity of African rangelands is a way to manage risks, both scientists and practitioners, caution against a momentary and local use of carrying capacity as a management indicator. Carrying capacity should be seen in wider spatial and temporal/seasonal context as well as in a social and economic context. Given the large numbers of conservancies across Kenya, and its Maasai Mara region in particular, with many more landowner members, it is difficult for conservancies’ managers to contextualize phenomena such as carrying capacity and market price over space and time. We report the results of an investigation in the Maasai Mara rangelands, into functional characteristics a tool for spatial-temporal carrying capacity assessment and livestock markets prices monitoring should have to provide relevant management information to conservancy managers and conservancy members. A scalable web-application called the Mara Rangeland Information System, or MARIS, was developed, which assesses, at 23 meter resolution and 10 day historic or 1-day near-future intervals, both grassland dry matter production, and consumption by 19 wildlife and livestock species, as well as rangeland carrying capacity. MARIS facilitates managers to develop scenarios by varying input variables of either grass production or consumption, or by drawing different management blocks on a carrying capacity map assessing different management practices under scenarios of rainfall. Managers can relate the carrying capacity scenarios to offtake prices at different markets that MARIS monitors over time. After testing MARIS in 6 workshop iterations across the whole development process, Maasai Mara rangeland managers concluded that the prototype is ready for pilot use in management plan development

Effect of Strain Magnitude on the Tissue Properties of Engineered Cardiovascular Constructs

Mechanical loading is a powerful regulator of tissue properties in engineered cardiovascular tissues. To ultimately regulate the biochemical processes, it is essential to quantify the effect of mechanical loading on the properties of engineered cardiovascular constructs. In this study the Flexercell FX-4000T (Flexcell Int. Corp., USA) straining system was modified to simultaneously apply various strain magnitudes to individual samples during one experiment. In addition, porous polyglycolic acid (PGA) scaffolds, coated with poly-4-hydroxybutyrate (P4HB), were partially embedded in a silicone layer to allow long-term uniaxial cyclic mechanical straining of cardiovascular engineered constructs. The constructs were subjected to two different strain magnitudes and showed differences in biochemical properties, mechanical properties and organization of the microstructure compared to the unstrained constructs. The results suggest that when the tissues are exposed to prolonged mechanical stimulation, the production of collagen with a higher fraction of crosslinks is induced. However, straining with a large strain magnitude resulted in a negative effect on the mechanical properties of the tissue. In addition, dynamic straining induced a different alignment of cells and collagen in the superficial layers compared to the deeper layers of the construct. The presented model system can be used to systematically optimize culture protocols for engineered cardiovascular tissues

Quantification of the Temporal Evolution of Collagen Orientation in Mechanically Conditioned Engineered Cardiovascular Tissues

Load-bearing soft tissues predominantly consist of collagen and exhibit anisotropic, non-linear visco-elastic behavior, coupled to the organization of the collagen fibers. Mimicking native mechanical behavior forms a major goal in cardiovascular tissue engineering. Engineered tissues often lack properly organized collagen and consequently do not meet in vivo mechanical demands. To improve collagen architecture and mechanical properties, mechanical stimulation of the tissue during in vitro tissue growth is crucial. This study describes the evolution of collagen fiber orientation with culture time in engineered tissue constructs in response to mechanical loading. To achieve this, a novel technique for the quantification of collagen fiber orientation is used, based on 3D vital imaging using multiphoton microscopy combined with image analysis. The engineered tissue constructs consisted of cell-seeded biodegradable rectangular scaffolds, which were either constrained or intermittently strained in longitudinal direction. Collagen fiber orientation analyses revealed that mechanical loading induced collagen alignment. The alignment shifted from oblique at the surface of the construct towards parallel to the straining direction in deeper tissue layers. Most importantly, intermittent straining improved and accelerated the alignment of the collagen fibers, as compared to constraining the constructs. Both the method and the results are relevant to create and monitor load-bearing tissues with an organized anisotropic collagen network