diff --git a/app/Main.hs b/app/Main.hs
index 3d9bf30..a2609a3 100644
--- a/app/Main.hs
+++ b/app/Main.hs
@@ -86,12 +86,13 @@ loop loopAmount = loop' loopAmount 0
       putStrLn ""
       putStrLn $ "Generation " ++ show curLoop ++ " of " ++ show loopAmount ++ ":"
       newPlants <- flip runReaderT e $ do
-          fs <- sequence (fitness <$> plants)
+          ! fs <- sequence (fitness <$> plants)
           let fps = zip plants fs -- gives us plants & their fitness in a tuple
               sumFitness = sum fs
           pe <- asks possibleEnzymes
-          tc <- fmap fst <$> asks toxicCompounds
+          tc <- asks toxicCompounds
           liftIO $ printPopulation tc pe fps
+          liftIO $ hFlush stdout
           -- generate 100 new plants.
           sequence . flip fmap [1..100] $ \_ -> do
                 parent' <- liftIO $ randomRIO (0,sumFitness)
@@ -140,7 +141,7 @@ main = do
 generatePredators :: Double -> EnzymeTree s (Double,Compound) -> IO [Predator]
 generatePredators threshold t = do
     ps <- mapM generatePredators' $ getSubTrees t
-    return $ concat ps
+    return $ filter ((/= []) . irresistance) $ concat ps -- filter out predators that are resistant to everything because this does not make sense in our model.
   where
       generatePredators' :: (EnzymeTree s (Double, Compound)) -> IO [Predator]
       generatePredators' t = do -- not fully resistant to t, but fully resistant to everything in ts
@@ -162,15 +163,17 @@ printEnvironment (Environment soil pred metaIter maxComp toxic possEnz) =
     putStrLn $ "Compounds: " ++ show ((toEnum <$> [0..maxComp]) :: [Compound])
     putStrLn $ "Toxic:     " ++ show toxic
 
-printPopulation :: [Compound] -> [Enzyme] -> [(Plant,Double)] -> IO ()
+printPopulation :: [(Compound, Amount)] -> [Enzyme] -> [(Plant,Double)] -> IO ()
 printPopulation toxins es ps = do
   let padded i str = take i $ str ++ repeat ' '
   putStr $ padded 50 "Population:"
   forM_ ps $ \(_,f) -> putStr (printColor f '█')
   putStrLn colorOff
   forM_ es $ \e -> do
-    putStr $ if (fst . snd . synthesis $ e) `elem` toxins then "\ESC[31m" ++ padded 50 (show (enzymeName e)) ++ "\ESC[0m"
-                                                          else padded 50 (show (enzymeName e))
+    putStr $ case Data.List.find (\(t,_) -> (t==) . fst . snd . synthesis $ e) toxins of
+               Just (_,toxicity) -> "\ESC[38;5;" ++ show (16 + 36*5 + 6*floor (5*(1-toxicity)) + 0) ++ "m" -- yellow -> red rainbow for tocixity 0 -> 1
+                                 ++ padded 50 (show (enzymeName e)) ++ "\ESC[0m"
+               Nothing           -> padded 50 (show (enzymeName e))
     forM_ ps $ \(Plant g _,_) -> do
       let curE = sum $ map (\(_,q,a) -> fromIntegral q*a)
                      . filter (\(e',_,_) -> e == e')
diff --git a/src/Environment.hs b/src/Environment.hs
index c241f92..36d0bd7 100644
--- a/src/Environment.hs
+++ b/src/Environment.hs
@@ -151,7 +151,15 @@ fitness p = do
   products <- produceCompounds p nutrients -- produce compounds
   survivalRate <- deterPredators products  -- defeat predators with produced compounds
   let sumEnzymes = sum $ (\(_,q,a) -> fromIntegral q*a) <$> genome p -- amount of enzymes * activation = resources "wasted"
-      costOfEnzymes = 0.99 ** sumEnzymes
+      staticCostOfEnzymes = 1 - 0.01*sumEnzymes -- static cost of creating enzymes
+      -- primaryEnzymes = filter (\(e,_,_) -> case (fst.fst.synthesis) e of -- select enzymes which use substrate
+      --                                        Substrate _ -> True
+      --                                        otherwise   -> False)
+      --                         (genome p)
+  nutrientsAvailable <- fmap snd <$> asks soil
+  let nutrientsLeft = [products ! i | i <- [0..fromEnum (maxBound :: Nutrient)]]
+      nutrientRatio = minimum $ zipWith (/) nutrientsLeft nutrientsAvailable
+      costOfEnzymes = max 0 $ staticCostOfEnzymes - nutrientRatio * 0.1 -- cost to keep enzymes are static costs + amount of nutrient sucked out of the primary cycle
   return $ survivalRate * costOfEnzymes
   -- can also be written as, but above is more clear.
   -- fitness p = absorbNutrients p >>= produceCompounds p >>= deterPredators
@@ -174,16 +182,22 @@ produceCompounds (Plant genes _) substrate = do
   return final
 
 
+-- TODO:
+-- - choose predators beforehand, then only apply those who appear in full force.
+-- - dampen full-force due to auto-mimicry-effect. => Fitness would not depend on single plant.
 deterPredators :: Vector Amount -> World Probability
 deterPredators cs = do
   ps <- asks predators
   ts <- asks toxicCompounds
+  ds <- liftIO $ randoms <$> newStdGen
   let
+     appearingPredators = fmap fst . filter (\((_,p),r) -> p > r) $ zip ps ds -- assign one probability to each predator, filter those who appear, throw random data away again.
+                                                                              -- appearingPredators is now a sublist of ps.
      deter :: Predator -> Double
          -- multiply   (toxicity of t with 100% effectiveness at l| for all toxins t | and t not in p's irresistance-list)
      deter p = product [1 - min 1 (cs ! fromEnum t / l)           | (t,l) <- ts,       t `elem` irresistance p]
          -- multiply  (probability of occurence * intensity of destruction / probability to deter predator | for all predators)
-  return $ product ([min 1 ((1-prob) * fitnessImpact p / deter p) | (p,prob) <- ps] `using` parList rdeepseq)
+  return $ product ([min 1 ((1-prob) * fitnessImpact p / deter p) | (p,prob) <- appearingPredators])
 
 -- Mating & Creation of diversity
 -- ------------------------------