16/06, 2021

Points already planned to be sampled

Objective

  • Find the points furthest away environmentally from the current points
  • Find the most stable, more increase and more decrease of species Richness
  • Candidate points extracted from Novana dataset
  • 46,648 Candidate points

Environmental distance

Methods

  • Furthest points in environmental space
    • Mean anual temperature
    • Temperature seasonality
    • Annual precipitation
    • Precipitation seasonality
    • Topographic wetness index
    • Vegetation density
    • pH Surface
    • pH deep
    • Bin of canopy height (<1,1-3, 3-10, >10)
    • Soil texture (Clay, Sand, Silt)
    • Heat load index
    • Slope

Map of selected points

NMDS of selected points

Environmental space

Selection by species richness change

Method

  • From Novana dataset select the point with at least 4 years of sampling
  • Make a linear regression between Richness (Only positive species), and year
  • If slope is non significative the sampling point is considered to be stable
    • Select the 34 lowest absolute value slope
  • If slope is significative and positive the sampling point is considered to be of increasing richness
    • Select the 34 highest slope value
  • If slope is significative and negative the sampling point is considered to be of decreasing richness
    • Select the 34 lowest slope value

Selected points

Selected points (map)

Habitat

habtype n
7210 97
7230 96
102 93
6210 87
100 86
2 85
6230 85
6410 83
1330 81
2130 81
2190 81
4030 81
7140 81
2250 80
7220 80
2120 79
2140 79
2170 79
4010 79
8220 79
2160 78
2320 76
7120 76
7150 76
5130 72
7110 72
9998 68
1220 59
6120 55
2310 53
2110 48
9999 42
2330 38
9190 35
1340 28
2180 28
9110 23
1210 21
1310 21
1230 19
9150 17
9130 6
1320 5
9120 3

Final map